diff --git a/.gitignore b/.gitignore index d340a43..b9bdf52 100644 --- a/.gitignore +++ b/.gitignore @@ -1,6 +1,7 @@ # Ignore the build and lib dirs build/ lib/ +vs/ # Ignore any executables bin/ @@ -18,3 +19,299 @@ nbproject/ *.xcworkspacedata *.xcuserstate *.xcsettings + +## Ignore Visual Studio temporary files, build results, and +## files generated by popular Visual Studio add-ons. +## +## Get latest from https://github.com/github/gitignore/blob/master/VisualStudio.gitignore + +# User-specific files +*.suo +*.user +*.userosscache +*.sln.docstates + +# User-specific files (MonoDevelop/Xamarin Studio) +*.userprefs + +# Build results +[Dd]ebug/ +[Dd]ebugPublic/ +[Rr]elease/ +[Rr]eleases/ +x64/ +x86/ +bld/ +[Bb]in/ +[Oo]bj/ +[Ll]og/ + +# Visual Studio 2015 cache/options directory +.vs/ +# Uncomment if you have tasks that create the project's static files in wwwroot +#wwwroot/ + +# MSTest test Results +[Tt]est[Rr]esult*/ +[Bb]uild[Ll]og.* + +# NUNIT +*.VisualState.xml +TestResult.xml + +# Build Results of an ATL Project +[Dd]ebugPS/ +[Rr]eleasePS/ +dlldata.c + +# Benchmark Results +BenchmarkDotNet.Artifacts/ + +# .NET Core +project.lock.json +project.fragment.lock.json +artifacts/ +**/Properties/launchSettings.json + +*_i.c +*_p.c +*_i.h +*.ilk +*.meta +*.obj +*.pch +*.pdb +*.pgc +*.pgd +*.rsp +*.sbr +*.tlb +*.tli +*.tlh +*.tmp +*.tmp_proj +*.log +*.vspscc +*.vssscc +.builds +*.pidb +*.svclog +*.scc + +# Chutzpah Test files +_Chutzpah* + +# Visual C++ cache files +ipch/ +*.aps +*.ncb +*.opendb +*.opensdf +*.sdf +*.cachefile +*.VC.db +*.VC.VC.opendb + +# Visual Studio profiler +*.psess +*.vsp +*.vspx +*.sap + +# TFS 2012 Local Workspace +$tf/ + +# Guidance Automation Toolkit +*.gpState + +# ReSharper is a .NET coding add-in +_ReSharper*/ +*.[Rr]e[Ss]harper +*.DotSettings.user + +# JustCode is a .NET coding add-in +.JustCode + +# TeamCity is a build add-in +_TeamCity* + +# DotCover is a Code Coverage Tool +*.dotCover + +# Visual Studio code coverage results +*.coverage +*.coveragexml + +# NCrunch +_NCrunch_* +.*crunch*.local.xml +nCrunchTemp_* + +# MightyMoose +*.mm.* +AutoTest.Net/ + +# Web workbench (sass) +.sass-cache/ + +# Installshield output folder +[Ee]xpress/ + +# DocProject is a documentation generator add-in +DocProject/buildhelp/ +DocProject/Help/*.HxT +DocProject/Help/*.HxC +DocProject/Help/*.hhc +DocProject/Help/*.hhk +DocProject/Help/*.hhp +DocProject/Help/Html2 +DocProject/Help/html + +# Click-Once directory +publish/ + +# Publish Web Output +*.[Pp]ublish.xml +*.azurePubxml +# TODO: Comment the next line if you want to checkin your web deploy settings +# but database connection strings (with potential passwords) will be unencrypted +*.pubxml +*.publishproj + +# Microsoft Azure Web App publish settings. Comment the next line if you want to +# checkin your Azure Web App publish settings, but sensitive information contained +# in these scripts will be unencrypted +PublishScripts/ + +# NuGet Packages +*.nupkg +# The packages folder can be ignored because of Package Restore +**/packages/* +# except build/, which is used as an MSBuild target. +!**/packages/build/ +# Uncomment if necessary however generally it will be regenerated when needed +#!**/packages/repositories.config +# NuGet v3's project.json files produces more ignorable files +*.nuget.props +*.nuget.targets + +# Microsoft Azure Build Output +csx/ +*.build.csdef + +# Microsoft Azure Emulator +ecf/ +rcf/ + +# Windows Store app package directories and files +AppPackages/ +BundleArtifacts/ +Package.StoreAssociation.xml +_pkginfo.txt +*.appx + +# Visual Studio cache files +# files ending in .cache can be ignored +*.[Cc]ache +# but keep track of directories ending in .cache +!*.[Cc]ache/ + +# Others +ClientBin/ +~$* +*~ +*.dbmdl +*.dbproj.schemaview +*.jfm +*.pfx +*.publishsettings +orleans.codegen.cs + +# Since there are multiple workflows, uncomment next line to ignore bower_components +# (https://github.com/github/gitignore/pull/1529#issuecomment-104372622) +#bower_components/ + +# RIA/Silverlight projects +Generated_Code/ + +# Backup & report files from converting an old project file +# to a newer Visual Studio version. Backup files are not needed, +# because we have git ;-) +_UpgradeReport_Files/ +Backup*/ +UpgradeLog*.XML +UpgradeLog*.htm + +# SQL Server files +*.mdf +*.ldf +*.ndf + +# Business Intelligence projects +*.rdl.data +*.bim.layout +*.bim_*.settings + +# Microsoft Fakes +FakesAssemblies/ + +# GhostDoc plugin setting file +*.GhostDoc.xml + +# Node.js Tools for Visual Studio +.ntvs_analysis.dat +node_modules/ + +# Typescript v1 declaration files +typings/ + +# Visual Studio 6 build log +*.plg + +# Visual Studio 6 workspace options file +*.opt + +# Visual Studio 6 auto-generated workspace file (contains which files were open etc.) +*.vbw + +# Visual Studio LightSwitch build output +**/*.HTMLClient/GeneratedArtifacts +**/*.DesktopClient/GeneratedArtifacts +**/*.DesktopClient/ModelManifest.xml +**/*.Server/GeneratedArtifacts +**/*.Server/ModelManifest.xml +_Pvt_Extensions + +# Paket dependency manager +.paket/paket.exe +paket-files/ + +# FAKE - F# Make +.fake/ + +# JetBrains Rider +.idea/ +*.sln.iml + +# CodeRush +.cr/ + +# Python Tools for Visual Studio (PTVS) +__pycache__/ +*.pyc + +# Cake - Uncomment if you are using it +# tools/** +# !tools/packages.config + +# Tabs Studio +*.tss + +# Telerik's JustMock configuration file +*.jmconfig + +# BizTalk build output +*.btp.cs +*.btm.cs +*.odx.cs +*.xsd.cs \ No newline at end of file diff --git a/CMakeLists.txt b/CMakeLists.txt new file mode 100644 index 0000000..018e88f --- /dev/null +++ b/CMakeLists.txt @@ -0,0 +1,78 @@ +cmake_minimum_required(VERSION 3.6) +project(jMetalCpp) +set(CMAKE_CXX_STANDARD 11) + +function (ListToString result delim) + list(GET ARGV 2 temp) + math(EXPR N "${ARGC}-1") + foreach(IDX RANGE 3 ${N}) + list(GET ARGV ${IDX} STR) + set(temp "${temp}${delim}${STR}") + endforeach() + set(${result} "${temp}" PARENT_SCOPE) +endfunction(ListToString) + + +define_property(GLOBAL PROPERTY SOURCE_LIST BRIEF_DOCS "Global list of source code" FULL_DOCS "Global list of source code") +set_property(GLOBAL PROPERTY SOURCE_LIST "") + +macro(LIST_APPEND var) + set_property(GLOBAL APPEND PROPERTY SOURCE_LIST "${var}") +endmacro(LIST_APPEND) + +define_property(GLOBAL PROPERTY HEADER_LIST BRIEF_DOCS "Global list of header code" FULL_DOCS "Global list of header code") +set_property(GLOBAL PROPERTY HEADER_LIST "") + +macro(LIST_APPEND_HEADER var) + set_property(GLOBAL APPEND PROPERTY HEADER_LIST "${var}") +endmacro(LIST_APPEND_HEADER) + +include_directories( + ${PROJECT_SOURCE_DIR}/src + ${PROJECT_SOURCE_DIR}/src/core + ${PROJECT_SOURCE_DIR}/src/encodings + ${PROJECT_SOURCE_DIR}/src/encodings/solutionType + ${PROJECT_SOURCE_DIR}/src/encodings/variable + ${PROJECT_SOURCE_DIR}/src/experiments + ${PROJECT_SOURCE_DIR}/src/experiments/main + ${PROJECT_SOURCE_DIR}/src/experiments/settings + ${PROJECT_SOURCE_DIR}/src/experiments/util + ${PROJECT_SOURCE_DIR}/src/main + ${PROJECT_SOURCE_DIR}/src/metaheuristics + ${PROJECT_SOURCE_DIR}/src/metaheuristics/gde3 + ${PROJECT_SOURCE_DIR}/src/metaheuristics/mochc + ${PROJECT_SOURCE_DIR}/src/metaheuristics/moead + ${PROJECT_SOURCE_DIR}/src/metaheuristics/nsgaII + ${PROJECT_SOURCE_DIR}/src/metaheuristics/omopso + ${PROJECT_SOURCE_DIR}/src/metaheuristics/paes + ${PROJECT_SOURCE_DIR}/src/metaheuristics/singleObjective + ${PROJECT_SOURCE_DIR}/src/metaheuristics/singleObjective/cmaes + ${PROJECT_SOURCE_DIR}/src/metaheuristics/singleObjective/cmaes/utils + ${PROJECT_SOURCE_DIR}/src/metaheuristics/singleObjective/differentialEvolution + ${PROJECT_SOURCE_DIR}/src/metaheuristics/singleObjective/geneticAlgorithm + ${PROJECT_SOURCE_DIR}/src/metaheuristics/singleObjective/particleSwarmOptimization + ${PROJECT_SOURCE_DIR}/src/metaheuristics/smpso + ${PROJECT_SOURCE_DIR}/src/metaheuristics/smsemoa + ${PROJECT_SOURCE_DIR}/src/operators + ${PROJECT_SOURCE_DIR}/src/operators/crossover + ${PROJECT_SOURCE_DIR}/src/operators/mutation + ${PROJECT_SOURCE_DIR}/src/operators/selection + ${PROJECT_SOURCE_DIR}/src/problems + ${PROJECT_SOURCE_DIR}/src/problems/DTLZ + ${PROJECT_SOURCE_DIR}/src/problems/LZ09 + ${PROJECT_SOURCE_DIR}/src/problems/singleObjective + ${PROJECT_SOURCE_DIR}/src/problems/singleObjective/cec2005Competition + ${PROJECT_SOURCE_DIR}/src/problems/ZDT + ${PROJECT_SOURCE_DIR}/src/qualityIndicator + ${PROJECT_SOURCE_DIR}/src/qualityIndicator/fastHypervolume + ${PROJECT_SOURCE_DIR}/src/qualityIndicator/main + ${PROJECT_SOURCE_DIR}/src/qualityIndicator/util + ${PROJECT_SOURCE_DIR}/src/util + ${PROJECT_SOURCE_DIR}/src/util/archive + ${PROJECT_SOURCE_DIR}/src/util/comparators + ${PROJECT_SOURCE_DIR}/src/util/wrapper + ) +add_subdirectory(${PROJECT_SOURCE_DIR}/src) +get_property(my_source_list GLOBAL PROPERTY SOURCE_LIST) +get_property(my_header_list GLOBAL PROPERTY HEADER_LIST) +add_library(${PROJECT_NAME} ${my_source_list} ${my_header_list}) diff --git a/src/CMakeLists.txt b/src/CMakeLists.txt new file mode 100644 index 0000000..babc786 --- /dev/null +++ b/src/CMakeLists.txt @@ -0,0 +1,9 @@ +add_subdirectory(core) +add_subdirectory(encodings) +add_subdirectory(experiments) +add_subdirectory(main) +add_subdirectory(metaheuristics) +add_subdirectory(operators) +add_subdirectory(problems) +add_subdirectory(qualityIndicator) +add_subdirectory(util) diff --git a/src/core/Algorithm.cpp b/src/core/Algorithm.cpp index ff53e0c..c6e9c66 100644 --- a/src/core/Algorithm.cpp +++ b/src/core/Algorithm.cpp @@ -20,7 +20,6 @@ // You should have received a copy of the GNU Lesser General Public License // along with this program. If not, see . - #include @@ -28,16 +27,18 @@ * Constructor * @param problem **/ -Algorithm::Algorithm(Problem *problem) { - problem_ = problem; +Algorithm::Algorithm(Problem *problem) +{ + problem_ = problem; } /** * Destructor */ -Algorithm::~Algorithm() { - delete problem_; +Algorithm::~Algorithm() +{ + delete problem_; } // ~Algorithm @@ -48,8 +49,9 @@ Algorithm::~Algorithm() { * @param name The operator name * @param operator The operator **/ -void Algorithm::addOperator(string name, Operator * operator_) { - operators_[name] = operator_; +void Algorithm::addOperator(std::string name, Operator * operator_) +{ + operators_[name] = operator_; } @@ -60,8 +62,9 @@ void Algorithm::addOperator(string name, Operator * operator_) { * @param name The operator name * @return The operator if exists, null in another case. **/ -Operator * Algorithm::getOperator(string name) { - return operators_[name]; +Operator * Algorithm::getOperator(std::string name) +{ + return operators_[name]; } @@ -74,8 +77,9 @@ Operator * Algorithm::getOperator(string name) { * @param object Object that represent a parameter for the * algorithm. **/ -void Algorithm::setInputParameter(string name, void *value) { - inputParameters_[name] = value; +void Algorithm::setInputParameter(std::string name, void *value) +{ + inputParameters_[name] = value; } @@ -86,8 +90,9 @@ void Algorithm::setInputParameter(string name, void *value) { * @return Object representing the parameter or null if the parameter doesn't * exist or the name is wrong **/ -void * Algorithm::getInputParameter(string name) { - return inputParameters_[name]; +void * Algorithm::getInputParameter(std::string name) +{ + return inputParameters_[name]; } @@ -99,8 +104,9 @@ void * Algorithm::getInputParameter(string name) { * @param name The output parameter name * @param object Object representing the output parameter **/ -void Algorithm::setOutputParameter(string name, void *value) { - outputParameters_[name] = value; +void Algorithm::setOutputParameter(std::string name, void *value) +{ + outputParameters_[name] = value; } @@ -111,8 +117,9 @@ void Algorithm::setOutputParameter(string name, void *value) { * @return Object representing the output parameter, or null if the parameter * doesn't exist or the name is wrong. **/ -void * Algorithm::getOutputParameter(string name) { - return outputParameters_[name]; +void * Algorithm::getOutputParameter(std::string name) +{ + return outputParameters_[name]; } @@ -120,6 +127,7 @@ void * Algorithm::getOutputParameter(string name) { * Returns the problem to solve * @return Problem The problem to solve **/ -Problem * Algorithm::getProblem() { - return problem_; +Problem * Algorithm::getProblem() +{ + return problem_; } diff --git a/src/core/Algorithm.h b/src/core/Algorithm.h index d9db7ea..59937c5 100644 --- a/src/core/Algorithm.h +++ b/src/core/Algorithm.h @@ -23,6 +23,7 @@ #ifndef __ALGORITHM__ #define __ALGORITHM__ +#include "JMetalHeader.h" #include #include #include @@ -35,26 +36,30 @@ * The class declares an abstract method called execute, which * defines the behavior of the algorithm. **/ -class Algorithm { + +using namespace JMetal; + +class Algorithm +{ public: - Algorithm(Problem *problem); - virtual ~Algorithm(); - virtual SolutionSet * execute() = 0; // this launch the execution - // of an algorithm - void addOperator(string name, Operator *operator_); - Operator * getOperator(string name); - void setInputParameter(string name, void *value); - void * getInputParameter(string name); - void setOutputParameter(string name, void *value); - void * getOutputParameter(string name); - Problem * getProblem(); + Algorithm(Problem *problem); + virtual ~Algorithm(); + virtual SolutionSet * execute() = 0; // this launch the execution + // of an algorithm + void addOperator(std::string name, Operator *operator_); + Operator * getOperator(std::string name); + void setInputParameter(std::string name, void *value); + void * getInputParameter(std::string name); + void setOutputParameter(std::string name, void *value); + void * getOutputParameter(std::string name); + Problem * getProblem(); protected: - Problem *problem_; - map operators_; - map inputParameters_; - map outputParameters_; + Problem *problem_ = nullptr; + MapOfStringOperatorPtr operators_; + MapOfStringFunct inputParameters_; + MapOfStringFunct outputParameters_; }; // Algorithm diff --git a/src/core/CMakeLists.txt b/src/core/CMakeLists.txt new file mode 100644 index 0000000..ca3372a --- /dev/null +++ b/src/core/CMakeLists.txt @@ -0,0 +1,3 @@ +file(GLOB SOURCES "*.cpp" "*.h") +ListToString(SOURCES ";" ${SOURCES}) +LIST_APPEND("${SOURCES}") diff --git a/src/core/JMetalHeader.h b/src/core/JMetalHeader.h new file mode 100644 index 0000000..20964a0 --- /dev/null +++ b/src/core/JMetalHeader.h @@ -0,0 +1,37 @@ +#ifndef __JMETAL_HEADER__ +#define __JMETAL_HEADER__ + +#ifdef MSVC + #ifdef _DEBUG + #define snew new ( _NORMAL_BLOCK , __FILE__ , __LINE__ ) + #endif +#else + #define snew new +#endif + +#include +#include +#include + +class Operator; +class Solution; + +namespace JMetal +{ + using MapOfStringFunct = std::map; + using MapOfStringOperatorPtr = std::map; + using MapOfStringDouble = std::map; + using MapOfStringBool = std::map; + using VectorOfSolutionPtr = std::vector; + using VectorOfDouble = std::vector; + using MatrixOfDouble = std::vector; + using VectorOfInteger = std::vector; + using MatrixOfInteger = std::vector; + using VectorOfBoolean = std::vector; + using MatrixOfBoolean = std::vector; + using VectorOfString = std::vector; + using VectorOfShort = std::vector; + using MatrixOfShort = std::vector; +} + +#endif \ No newline at end of file diff --git a/src/core/Operator.cpp b/src/core/Operator.cpp index fdc5952..6487052 100644 --- a/src/core/Operator.cpp +++ b/src/core/Operator.cpp @@ -27,15 +27,17 @@ /** * Constructor. **/ -Operator::Operator() { +Operator::Operator() +{ } // Operator /** * Constructor. **/ -Operator::Operator(map parameters) { - parameters_ = parameters; +Operator::Operator(MapOfStringFunct parameters) +{ + parameters_ = parameters; } // Operator @@ -50,8 +52,9 @@ Operator::~Operator() { /* do nothing */ } * @param name The parameter name. * @param value Object representing the parameter. **/ -void Operator::setParameter(string name, void *value) { - parameters_[name] = value; +void Operator::setParameter(std::string name, void *value) +{ + parameters_[name] = value; } // setParameter @@ -60,7 +63,8 @@ void Operator::setParameter(string name, void *value) { * @param name The parameter name. * @return the parameter. **/ -void * Operator::getParameter(string name) { - return parameters_[name]; +void * Operator::getParameter(std::string name) +{ + return parameters_[name]; } diff --git a/src/core/Operator.h b/src/core/Operator.h index 2e1c044..bd555fb 100644 --- a/src/core/Operator.h +++ b/src/core/Operator.h @@ -23,30 +23,31 @@ #ifndef __OPERATOR__ #define __OPERATOR__ -#include -#include +#include "JMetalHeader.h" #include -using namespace std; - /** * Stores the current operator parameters. * It is defined as a Map of pairs <String, Object>, * and it allow objects to be accessed by their names, which are specified * by the string. **/ -class Operator { + +using namespace JMetal; + +class Operator +{ protected: - map parameters_; - + MapOfStringFunct parameters_; + public: - Operator (); - Operator (map parameters); - virtual ~Operator() = 0; - virtual void *execute(void *) = 0; - void setParameter(string name, void *value); - void *getParameter(string name); + Operator (); + Operator (MapOfStringFunct parameters); + virtual ~Operator() = 0; + virtual void *execute(void *) = 0; + void setParameter(std::string name, void *value); + void *getParameter(std::string name); }; // Operator diff --git a/src/core/Problem.cpp b/src/core/Problem.cpp index 2759f9e..ee49b0a 100644 --- a/src/core/Problem.cpp +++ b/src/core/Problem.cpp @@ -30,16 +30,18 @@ const int Problem::DEFAULT_PRECISSION = 16; /** * Constructor. */ -Problem::Problem() { - solutionType_ = NULL; +Problem::Problem() +{ + solutionType_ = nullptr; } // Problem /** * Constructor. */ -Problem::Problem(SolutionType * solutionType) { - solutionType_ = solutionType ; +Problem::Problem(SolutionType * solutionType) +{ + solutionType_ = solutionType ; } // Problem @@ -56,16 +58,18 @@ Problem::~Problem() { } // ~Problem * Gets the number of decision variables of the problem. * @return the number of decision variables. */ -int Problem::getNumberOfVariables() { - return numberOfVariables_; +int Problem::getNumberOfVariables() +{ + return numberOfVariables_; } // getNumberOfVariables /** * Sets the number of decision variables of the problem. */ -void Problem::setNumberOfVariables(int numberOfVariables) { - numberOfVariables_ = numberOfVariables; +void Problem::setNumberOfVariables(int numberOfVariables) +{ + numberOfVariables_ = numberOfVariables; } // setNumberOfVariables @@ -73,30 +77,34 @@ void Problem::setNumberOfVariables(int numberOfVariables) { * Gets the the number of objectives of the problem. * @return the number of objectives. */ -int Problem::getNumberOfObjectives() { - return numberOfObjectives_; +int Problem::getNumberOfObjectives() +{ + return numberOfObjectives_; } // getNumberOfObjectives /** * Sets the the number of objectives of the problem. */ -void Problem::setNumberOfObjectives(int numberOfObjectives) { - numberOfObjectives_ = numberOfObjectives; +void Problem::setNumberOfObjectives(int numberOfObjectives) +{ + numberOfObjectives_ = numberOfObjectives; } // setNumberOfObjectives - + /** * Gets the lower bound of the ith variable of the problem. * @param i The index of the variable. * @return The lower bound. */ -double Problem::getLowerLimit(int i) { - if ((lowerLimit_ == NULL) || (i >= numberOfVariables_)) { - cout << "Error: lower limits have been not initialized or accessing to a variable out of range" << endl; - // exit(-1); - } - return lowerLimit_[i]; +double Problem::getLowerLimit(int i) +{ + if ((lowerLimit_ == nullptr) || (i >= numberOfVariables_)) + { + std::cout << "Error: lower limits have been not initialized or accessing to a variable out of range" << std::endl; + // exit(-1); + } + return lowerLimit_[i]; } // getLowerLimit @@ -105,12 +113,14 @@ double Problem::getLowerLimit(int i) { * @param i The index of the variable. * @return The upper bound. */ -double Problem::getUpperLimit(int i) { - if ((upperLimit_ == NULL) || (i >= numberOfVariables_)) { - cout << "Error: upper limits have been not initialized or accessing to a variable out of range" << endl; - //exit(-1); - } - return upperLimit_[i]; +double Problem::getUpperLimit(int i) +{ + if ((upperLimit_ == nullptr) || (i >= numberOfVariables_)) + { + std::cout << "Error: upper limits have been not initialized or accessing to a variable out of range" << std::endl; + //exit(-1); + } + return upperLimit_[i]; } // getUpperLimit @@ -118,8 +128,9 @@ double Problem::getUpperLimit(int i) { * Gets the number of side constraints in the problem. * @return the number of constraints. */ -int Problem::getNumberOfConstraints() { - return numberOfConstraints_ ; +int Problem::getNumberOfConstraints() +{ + return numberOfConstraints_ ; } // getNumberOfConstraints @@ -128,9 +139,10 @@ int Problem::getNumberOfConstraints() { * object. * @param solution The Solution to evaluate. */ -void Problem::evaluateConstraints(Solution * solution) { - // The default behavior is to do nothing. Only constrained problems have to - // re-define this method +void Problem::evaluateConstraints(Solution * solution) +{ + // The default behavior is to do nothing. Only constrained problems have to + // re-define this method } // evaluateConstraints @@ -139,8 +151,9 @@ void Problem::evaluateConstraints(Solution * solution) { * variables * @return the number of bits. */ -int Problem::getPrecision(int var) { - return precision_[var] ; +int Problem::getPrecision(int var) +{ + return precision_[var] ; } // getPrecision @@ -149,8 +162,9 @@ int Problem::getPrecision(int var) { * binary-real variables. * @return the number of bits. */ -int * Problem::getPrecision() { - return precision_; +int * Problem::getPrecision() +{ + return precision_; } // getPrecision @@ -159,8 +173,9 @@ int * Problem::getPrecision() { * binary-real variables. * @param precision The array */ -void Problem::setPrecision(int * precision) { - precision_ = precision; +void Problem::setPrecision(int * precision) +{ + precision_ = precision; } // setPrecision @@ -168,23 +183,27 @@ void Problem::setPrecision(int * precision) { * Returns the length of the variable. * @return the variable length. */ -int Problem::getLength(int var) { - if (length_ == NULL) { - return DEFAULT_PRECISSION; - } - return length_[var] ; +int Problem::getLength(int var) +{ + if (length_ == nullptr) + { + return DEFAULT_PRECISSION; + } + return length_[var] ; } // getLength /** * Returns the number of bits of the solutions of the problem * @return The number of bits solutions of the problem */ -int Problem::getNumberOfBits() { - int result = 0; - for (int var = 0; var < numberOfVariables_; var++) { - result += getLength(var); - } - return result; +int Problem::getNumberOfBits() +{ + int result = 0; + for (int var = 0; var < numberOfVariables_; var++) + { + result += getLength(var); + } + return result; } // getNumberOfBits @@ -195,14 +214,15 @@ int Problem::getNumberOfBits() { //int Problem::getNumberOfConstraints() { // return numberOfConstraints_; //} // getNumberOfConstraints - + /** * Sets the type of the variables of the problem. * @param type The type of the variables */ -void Problem::setSolutionType(SolutionType * type) { - solutionType_ = type; +void Problem::setSolutionType(SolutionType * type) +{ + solutionType_ = type; } // setSolutionType @@ -210,8 +230,9 @@ void Problem::setSolutionType(SolutionType * type) { * Returns the type of the variables of the problem. * @return type of the variables of the problem. */ -SolutionType * Problem::getSolutionType() { - return solutionType_; +SolutionType * Problem::getSolutionType() +{ + return solutionType_; } // getSolutionType @@ -219,7 +240,8 @@ SolutionType * Problem::getSolutionType() { * Returns the problem name * @return The problem name */ -string Problem::getName() { - return problemName_; +std::string Problem::getName() +{ + return problemName_; } // getName - + diff --git a/src/core/Problem.h b/src/core/Problem.h index db32a9e..38f2864 100644 --- a/src/core/Problem.h +++ b/src/core/Problem.h @@ -23,57 +23,57 @@ #ifndef __PROBLEM__ #define __PROBLEM__ +#include "JMetalHeader.h" #include #include #include #include #include -using namespace std; - class SolutionType; class Solution; /** * Abstract class representing a multiobjective optimization problem */ -class Problem { +class Problem +{ private: - static const int DEFAULT_PRECISSION; + static const int DEFAULT_PRECISSION; protected: - int numberOfVariables_; - int numberOfObjectives_; - int numberOfConstraints_; - string problemName_; - SolutionType *solutionType_; - double *lowerLimit_; - double *upperLimit_; - int *precision_; - int *length_; - + int numberOfVariables_; + int numberOfObjectives_; + int numberOfConstraints_; + std::string problemName_; + SolutionType *solutionType_; + double *lowerLimit_; + double *upperLimit_; + int *precision_; + int *length_; + public: - Problem(); - Problem(SolutionType * solutionType); - virtual ~Problem() = 0; - int getNumberOfVariables(); - void setNumberOfVariables(int numberOfVariables); - int getNumberOfObjectives(); - void setNumberOfObjectives(int numberOfObjectives); - double getLowerLimit(int i); - double getUpperLimit(int i); - virtual void evaluate(Solution * solution) = 0; - int getNumberOfConstraints(); - virtual void evaluateConstraints(Solution * solution); - int getPrecision(int var); - int * getPrecision(); - void setPrecision(int * precision); - int getLength(int var); - void setSolutionType(SolutionType * type); - SolutionType * getSolutionType(); - string getName(); - int getNumberOfBits(); + Problem(); + Problem(SolutionType * solutionType); + virtual ~Problem() = 0; + int getNumberOfVariables(); + void setNumberOfVariables(int numberOfVariables); + int getNumberOfObjectives(); + void setNumberOfObjectives(int numberOfObjectives); + double getLowerLimit(int i); + double getUpperLimit(int i); + virtual void evaluate(Solution * solution) = 0; + int getNumberOfConstraints(); + virtual void evaluateConstraints(Solution * solution); + int getPrecision(int var); + int * getPrecision(); + void setPrecision(int * precision); + int getLength(int var); + void setSolutionType(SolutionType * type); + SolutionType * getSolutionType(); + std::string getName(); + int getNumberOfBits(); }; // Problem diff --git a/src/core/Solution.cpp b/src/core/Solution.cpp index d7fe6fa..7f8431e 100644 --- a/src/core/Solution.cpp +++ b/src/core/Solution.cpp @@ -27,17 +27,18 @@ /** * Constructor. */ -Solution::Solution () { - problem_ = NULL; - marked_ = false; - overallConstraintViolation_ = 0.0; - numberOfViolatedConstraints_ = 0; - numberOfVariables_ = 0; - numberOfObjectives_ = 0; - type_ = NULL; - variable_ = NULL; - objective_ = NULL; - rank_ = 0; +Solution::Solution () +{ + problem_ = nullptr; + marked_ = false; + overallConstraintViolation_ = 0.0; + numberOfViolatedConstraints_ = 0; + numberOfVariables_ = 0; + numberOfObjectives_ = 0; + type_ = nullptr; + variable_ = nullptr; + objective_ = nullptr; + rank_ = 0; } //Solution @@ -48,17 +49,19 @@ Solution::Solution () { * This constructor is used mainly to read objective values from a file to * variables of a SolutionSet to apply quality indicators */ -Solution::Solution (int numberOfObjectives) { - overallConstraintViolation_ = 0.0; - numberOfObjectives_ = numberOfObjectives; - numberOfVariables_ = 0; - variable_ = NULL; - objective_ = new double[numberOfObjectives_]; - if (objective_ == NULL) { - cout << "ERROR GRAVE: Impossible to reserve memory for storing objectives in class Solution" << endl; - exit(-1); - } - rank_ = 0; +Solution::Solution (int numberOfObjectives) +{ + overallConstraintViolation_ = 0.0; + numberOfObjectives_ = numberOfObjectives; + numberOfVariables_ = 0; + variable_ = nullptr; + objective_ = snew double[numberOfObjectives_]; + if (objective_ == nullptr) + { + std::cout << "ERROR GRAVE: Impossible to reserve memory for storing objectives in class Solution" << std::endl; + exit(-1); + } + rank_ = 0; } @@ -67,28 +70,30 @@ Solution::Solution (int numberOfObjectives) { * @param problem The problem to solve * @throws ClassNotFoundException */ -Solution::Solution (Problem *problem) { - problem_ = problem; - type_ = problem_->getSolutionType(); - overallConstraintViolation_ = 0.0; - numberOfObjectives_ = problem_->getNumberOfObjectives(); - numberOfVariables_ = problem_->getNumberOfVariables(); - - // creating the objective vector - objective_ = new double[numberOfObjectives_]; - if (objective_ == NULL) { - cout << "ERROR GRAVE: Impossible to reserve memory for storing objectives in class Solution" << endl; - exit(-1); - } - // at this point objective vector has been created successfully - - // Setting initial values - fitness_ = 0.0; - kDistance_ = 0.0; - crowdingDistance_ = 0.0; - distanceToSolutionSet_ = std::numeric_limits::max(); - variable_ = type_->createVariables(); - rank_ = 0; +Solution::Solution (Problem *problem) +{ + problem_ = problem; + type_ = problem_->getSolutionType(); + overallConstraintViolation_ = 0.0; + numberOfObjectives_ = problem_->getNumberOfObjectives(); + numberOfVariables_ = problem_->getNumberOfVariables(); + + // creating the objective vector + objective_ = snew double[numberOfObjectives_]; + if (objective_ == nullptr) + { + std::cout << "ERROR GRAVE: Impossible to reserve memory for storing objectives in class Solution" << std::endl; + exit(-1); + } + // at this point objective vector has been created successfully + + // Setting initial values + fitness_ = 0.0; + kDistance_ = 0.0; + crowdingDistance_ = 0.0; + distanceToSolutionSet_ = std::numeric_limits::max(); + variable_ = type_->createVariables(); + rank_ = 0; } // Solution @@ -96,20 +101,21 @@ Solution::Solution (Problem *problem) { * Constructor * @param problem The problem to solve */ -Solution::Solution (Problem * problem, Variable ** variables) { - problem_ = problem; - type_ = problem->getSolutionType(); - numberOfObjectives_ = problem->getNumberOfObjectives(); - numberOfVariables_ = problem_->getNumberOfVariables(); - objective_ = new double[numberOfObjectives_] ; - - // Setting initial values - fitness_ = 0.0; - kDistance_ = 0.0; - crowdingDistance_ = 0.0; - distanceToSolutionSet_ = std::numeric_limits::max(); - variable_ = variables; - rank_ = 0; +Solution::Solution (Problem * problem, Variable ** variables) +{ + problem_ = problem; + type_ = problem->getSolutionType(); + numberOfObjectives_ = problem->getNumberOfObjectives(); + numberOfVariables_ = problem_->getNumberOfVariables(); + objective_ = snew double[numberOfObjectives_] ; + + // Setting initial values + fitness_ = 0.0; + kDistance_ = 0.0; + crowdingDistance_ = 0.0; + distanceToSolutionSet_ = std::numeric_limits::max(); + variable_ = variables; + rank_ = 0; } // Solution @@ -117,54 +123,58 @@ Solution::Solution (Problem * problem, Variable ** variables) { * Copy constructor. * @param solution Solution to copy. */ -Solution::Solution (Solution *solution) { - problem_ = solution->problem_; - type_ = solution->type_; - numberOfObjectives_ = solution->getNumberOfObjectives(); - numberOfVariables_ = solution->getNumberOfVariables(); - - // creating the objective vector - objective_ = new double[numberOfObjectives_]; - if (objective_ == NULL) { - cout << "ERROR GRAVE: Impossible to reserve memory for storing objectives in class Solution" << endl; - exit(-1); - } - for (int i = 0; i< numberOfObjectives_; i++) { - objective_[i] = solution->objective_[i]; - } - - variable_ = type_->copyVariables(solution->variable_) ; - overallConstraintViolation_ = solution->getOverallConstraintViolation(); - numberOfViolatedConstraints_ = solution->getNumberOfViolatedConstraints(); - distanceToSolutionSet_ = solution->getDistanceToSolutionSet(); - crowdingDistance_ = solution->getCrowdingDistance(); - kDistance_ = solution->getKDistance(); - fitness_ = solution->getFitness(); - marked_ = solution->isMarked(); - rank_ = solution->getRank(); - location_ = solution->getLocation(); - - // create the variables - //old fashion of copying variables - //decisionVariables_ = (Variable *)new Variable*[numberOfVariables_]; - //for (i = 0; i < numberOfVariables_; i++) { - // decisionVariables_[i] = another_->decisionVariables_[i].deepCopy() - //} - //new fashion of copying variables - //decisionVariables_ = solutionType_->copyVariables(another->decisionVariables_); - +Solution::Solution (Solution *solution) +{ + problem_ = solution->problem_; + type_ = solution->type_; + numberOfObjectives_ = solution->getNumberOfObjectives(); + numberOfVariables_ = solution->getNumberOfVariables(); + + // creating the objective vector + objective_ = snew double[numberOfObjectives_]; + if (objective_ == nullptr) + { + std::cout << "ERROR GRAVE: Impossible to reserve memory for storing objectives in class Solution" << std::endl; + exit(-1); + } + for (int i = 0; i< numberOfObjectives_; i++) + { + objective_[i] = solution->objective_[i]; + } + + variable_ = type_->copyVariables(solution->variable_) ; + overallConstraintViolation_ = solution->getOverallConstraintViolation(); + numberOfViolatedConstraints_ = solution->getNumberOfViolatedConstraints(); + distanceToSolutionSet_ = solution->getDistanceToSolutionSet(); + crowdingDistance_ = solution->getCrowdingDistance(); + kDistance_ = solution->getKDistance(); + fitness_ = solution->getFitness(); + marked_ = solution->isMarked(); + rank_ = solution->getRank(); + location_ = solution->getLocation(); + + // create the variables + //old fashion of copying variables + //decisionVariables_ = (Variable *)new Variable*[numberOfVariables_]; + //for (i = 0; i < numberOfVariables_; i++) { + // decisionVariables_[i] = another_->decisionVariables_[i].deepCopy() + //} + //new fashion of copying variables + //decisionVariables_ = solutionType_->copyVariables(another->decisionVariables_); + } // Solution /** * Destructor */ -Solution::~Solution() { - delete[]objective_ ; - if (variable_ != NULL) - for (int i = 0; i < numberOfVariables_; i++) - delete variable_[i] ; - delete [] variable_ ; +Solution::~Solution() +{ + delete[]objective_ ; + if (variable_ != nullptr) + for (int i = 0; i < numberOfVariables_; i++) + delete variable_[i] ; + delete [] variable_ ; } // ~Solution @@ -173,7 +183,8 @@ Solution::~Solution() { * The value is stored in distanceToSolutionSet_. * @param distance The distance to a solutionSet. */ -void Solution::setDistanceToSolutionSet(double distance) { +void Solution::setDistanceToSolutionSet(double distance) +{ distanceToSolutionSet_ = distance; } // setDistanceToSolutionSet @@ -184,8 +195,9 @@ void Solution::setDistanceToSolutionSet(double distance) { * setDistanceToPopulation. * @return the distance to a specific solutionSet. */ -double Solution::getDistanceToSolutionSet() { - return distanceToSolutionSet_; +double Solution::getDistanceToSolutionSet() +{ + return distanceToSolutionSet_; } // getDistanceToSolutionSet @@ -194,8 +206,9 @@ double Solution::getDistanceToSolutionSet() { * a SolutionSet. The value is stored in kDistance_. * @param distance The distance to the k-nearest neighbor. */ -void Solution::setKDistance(double distance) { - kDistance_ = distance; +void Solution::setKDistance(double distance) +{ + kDistance_ = distance; } // setKDistance @@ -206,8 +219,9 @@ void Solution::setKDistance(double distance) { * after calling setKDistance. * @return the distance to k-nearest neighbor. */ -double Solution::getKDistance() { - return kDistance_; +double Solution::getKDistance() +{ + return kDistance_; } // getKDistance @@ -216,8 +230,9 @@ double Solution::getKDistance() { * The value is stored in crowdingDistance_. * @param distance The crowding distance of the solution. */ -void Solution::setCrowdingDistance(double distance) { - crowdingDistance_ = distance; +void Solution::setCrowdingDistance(double distance) +{ + crowdingDistance_ = distance; } // setCrowdingDistance @@ -228,8 +243,9 @@ void Solution::setCrowdingDistance(double distance) { * setCrowdingDistance. * @return the distance crowding distance of the solution. */ -double Solution::getCrowdingDistance() { - return crowdingDistance_; +double Solution::getCrowdingDistance() +{ + return crowdingDistance_; } // getCrowdingDistance @@ -238,8 +254,9 @@ double Solution::getCrowdingDistance() { * The value is stored in fitness_. * @param fitness The fitness of the solution. */ -void Solution::setFitness(double fitness) { - fitness_ = fitness; +void Solution::setFitness(double fitness) +{ + fitness_ = fitness; } // setFitness @@ -250,8 +267,9 @@ void Solution::setFitness(double fitness) { * setFitness(). * @return the fitness. */ -double Solution::getFitness() { - return fitness_; +double Solution::getFitness() +{ + return fitness_; } // getFitness @@ -260,13 +278,15 @@ double Solution::getFitness() { * @param i The number identifying the objective. * @param value The value to be stored. */ -void Solution::setObjective(int i, double value) { - if (i < 0 || i >= numberOfObjectives_) { - cout << "Solution::setObjective: objective index out of range: " << i - << endl; - exit(-1); - } - objective_[i] = value; +void Solution::setObjective(int i, double value) +{ + if (i < 0 || i >= numberOfObjectives_) + { + std::cout << "Solution::setObjective: objective index out of range: " << i + << std::endl; + exit(-1); + } + objective_[i] = value; } // setObjective @@ -274,13 +294,15 @@ void Solution::setObjective(int i, double value) { * Returns the value of the i-th objective. * @param i The value of the objective. */ -double Solution::getObjective(int i) { - if (i < 0 || i >= numberOfObjectives_) { - cout << "Solution::getObjective: objective index out of range: " << i - << endl; - exit(-1); - } - return objective_[i]; +double Solution::getObjective(int i) +{ + if (i < 0 || i >= numberOfObjectives_) + { + std::cout << "Solution::getObjective: objective index out of range: " << i + << std::endl; + exit(-1); + } + return objective_[i]; } // getObjective @@ -288,8 +310,9 @@ double Solution::getObjective(int i) { * Returns the number of objectives. * @return The number of objectives. */ -int Solution::getNumberOfObjectives() { - return numberOfObjectives_; +int Solution::getNumberOfObjectives() +{ + return numberOfObjectives_; } // getNumberOfObjectives @@ -297,34 +320,38 @@ int Solution::getNumberOfObjectives() { * Returns the number of decision variables of the solution. * @return The number of decision variables. */ -int Solution::getNumberOfVariables() { - return numberOfVariables_; +int Solution::getNumberOfVariables() +{ + return numberOfVariables_; } // getNumberOfVariables /** - * Returns a string representing the solution. + * Returns a std::string representing the solution. * @return The string. */ -string Solution::toString() { - string aux = ""; - - for (int i = 0; i < numberOfVariables_; i++) { - std::ostringstream stringStream; +std::string Solution::toString() +{ + std::string aux = ""; + + for (int i = 0; i < numberOfVariables_; i++) + { + std::ostringstream stringStream; // stringStream << this->getDecisionVariables()[i]->getValue() ; - stringStream << this->getDecisionVariables()[i]->toString() ; - aux = aux + stringStream.str() + " "; - } - aux = aux + " | " ; - for (int i = 0; i < numberOfObjectives_; i++) { - std::ostringstream stringStream; - stringStream << this->getObjective(i) ; - // aux = aux + string(this->getDecisionVariables()[i]->getValue()) + " "; - // aux = aux + string(0.03) + " "; - aux = aux + stringStream.str() + " "; - } - - return aux; + stringStream << this->getDecisionVariables()[i]->toString() ; + aux = aux + stringStream.str() + " "; + } + aux = aux + " | " ; + for (int i = 0; i < numberOfObjectives_; i++) + { + std::ostringstream stringStream; + stringStream << this->getObjective(i) ; + // aux = aux + string(this->getDecisionVariables()[i]->getValue()) + " "; + // aux = aux + string(0.03) + " "; + aux = aux + stringStream.str() + " "; + } + + return aux; } // toString @@ -333,8 +360,9 @@ string Solution::toString() { * @return the DecisionVariables object representing the decision * variables of the solution. */ -Variable ** Solution::getDecisionVariables() { - return variable_; +Variable ** Solution::getDecisionVariables() +{ + return variable_; } // getDecisionVariables @@ -343,8 +371,9 @@ Variable ** Solution::getDecisionVariables() { * @param decisionVariables The DecisionVariables object * representing the decision variables of the solution. */ -void Solution::setDecisionVariables(Variable **variables) { - variable_ = variables ; +void Solution::setDecisionVariables(Variable **variables) +{ + variable_ = variables ; } // setDecisionVariables @@ -354,24 +383,27 @@ void Solution::setDecisionVariables(Variable **variables) { * that, the method unmarked hasn't been called. False in other * case. */ -bool Solution::isMarked() { - return marked_; +bool Solution::isMarked() +{ + return marked_; } // isMarked /** * Establishes the solution as marked. */ -void Solution::mark() { - marked_ = true; +void Solution::mark() +{ + marked_ = true; } // mark /** * Established the solution as unmarked. */ -void Solution::unMark() { - marked_ = false; +void Solution::unMark() +{ + marked_ = false; } // unMark @@ -379,8 +411,9 @@ void Solution::unMark() { * Sets the rank of a solution. * @param value The rank of the solution. */ -void Solution::setRank(int rank) { - rank_ = rank ; +void Solution::setRank(int rank) +{ + rank_ = rank ; } // setRank @@ -390,8 +423,9 @@ void Solution::setRank(int rank) { * setRank(). * @return the rank of the solution. */ -int Solution::getRank() { - return rank_; +int Solution::getRank() +{ + return rank_; } // getRank @@ -399,8 +433,9 @@ int Solution::getRank() { * Sets the overall constraints violated by the solution. * @param value The overall constraints violated by the solution. */ -void Solution::setOverallConstraintViolation(double value) { - overallConstraintViolation_ = value; +void Solution::setOverallConstraintViolation(double value) +{ + overallConstraintViolation_ = value; } // setOverallConstraintViolation @@ -410,8 +445,9 @@ void Solution::setOverallConstraintViolation(double value) { * overallConstraintViolation. * @return the overall constraint violation by the solution. */ -double Solution::getOverallConstraintViolation() { - return overallConstraintViolation_; +double Solution::getOverallConstraintViolation() +{ + return overallConstraintViolation_; } // getOverallConstraintViolation @@ -419,8 +455,9 @@ double Solution::getOverallConstraintViolation() { * Sets the number of constraints violated by the solution. * @param value The number of constraints violated by the solution. */ -void Solution::setNumberOfViolatedConstraints(int number) { - numberOfViolatedConstraints_ = number; +void Solution::setNumberOfViolatedConstraints(int number) +{ + numberOfViolatedConstraints_ = number; } // setNumberOfViolatedConstraints @@ -430,8 +467,9 @@ void Solution::setNumberOfViolatedConstraints(int number) { * setNumberOfViolatedConstraint. * @return the number of constraints violated by the solution. */ -int Solution::getNumberOfViolatedConstraints() { - return numberOfViolatedConstraints_; +int Solution::getNumberOfViolatedConstraints() +{ + return numberOfViolatedConstraints_; } // getNumberOfViolatedConstraints @@ -439,8 +477,9 @@ int Solution::getNumberOfViolatedConstraints() { * Sets the location of the solution into a solutionSet. * @param location The location of the solution. */ -void Solution::setLocation(int location) { - location_ = location; +void Solution::setLocation(int location) +{ + location_ = location; } // setLocation @@ -450,8 +489,9 @@ void Solution::setLocation(int location) { * setLocation. * @return the location of the solution into a solutionSet */ -int Solution::getLocation() { - return location_; +int Solution::getLocation() +{ + return location_; } // getLocation @@ -459,8 +499,9 @@ int Solution::getLocation() { * Sets the type of the variable. * @param type The type of the variable. */ -void Solution::setType(SolutionType * type) { - type_ = type; +void Solution::setType(SolutionType * type) +{ + type_ = type; } // setType @@ -468,8 +509,9 @@ void Solution::setType(SolutionType * type) { * Gets the type of the variable * @return the type of the variable */ -SolutionType * Solution::getType() { - return type_; +SolutionType * Solution::getType() +{ + return type_; } // getType @@ -477,20 +519,23 @@ SolutionType * Solution::getType() { * Returns the aggregative value of the solution * @return The aggregative value. */ -double Solution::getAggregativeValue() { - double value = 0.0; - for (int i = 0; i < numberOfObjectives_; i++){ - value += objective_[i]; - } - return value; +double Solution::getAggregativeValue() +{ + double value = 0.0; + for (int i = 0; i < numberOfObjectives_; i++) + { + value += objective_[i]; + } + return value; } // getAggregativeValue /** * Returns the problem being solved * @return The problem. */ -Problem * Solution::getProblem() { - return problem_ ; +Problem * Solution::getProblem() +{ + return problem_ ; } // getAggregativeValue diff --git a/src/core/Solution.h b/src/core/Solution.h index fa0b3c0..c53f6dd 100644 --- a/src/core/Solution.h +++ b/src/core/Solution.h @@ -33,7 +33,7 @@ #include -//using namespace std; +// // class Problem ; class Variable ; @@ -43,66 +43,67 @@ class SolutionType ; * @class Solution * @brief Class representing a solution for a problem **/ -class Solution { +class Solution +{ private: - Problem * problem_; - SolutionType * type_; - Variable ** variable_; - int numberOfVariables_; - double *objective_; - int numberOfObjectives_; - double fitness_; - bool marked_; - int rank_; - double overallConstraintViolation_; - int numberOfViolatedConstraints_; - int location_; - double kDistance_; - double crowdingDistance_; - double distanceToSolutionSet_; - + Problem * problem_; + SolutionType * type_; + Variable ** variable_; + int numberOfVariables_ = 0; + double *objective_; + int numberOfObjectives_ = 0; + double fitness_ = 0.0; + bool marked_ = false; + int rank_ = 0; + double overallConstraintViolation_ = 0.0; + int numberOfViolatedConstraints_ = 0; + int location_ = 0; + double kDistance_ = 0.0; + double crowdingDistance_ = 0.0; + double distanceToSolutionSet_ = 0.0; + public: - Solution (); - Solution (int numberOfObjectives); - Solution (Problem * problem); - //getNewsolution (Problem *problem); - Solution(Problem * problem, Variable ** variables); - Solution (Solution * solution); + Solution (); + Solution (int numberOfObjectives); + Solution (Problem * problem); + //getNewsolution (Problem *problem); + Solution(Problem * problem, Variable ** variables); + Solution (Solution * solution); - ~Solution(); + ~Solution(); - void setDistanceToSolutionSet(double distance); - double getDistanceToSolutionSet(); - void setKDistance(double distance); - double getKDistance(); - void setCrowdingDistance(double distance); - double getCrowdingDistance(); - void setFitness(double fitness); - double getFitness(); - void setObjective(int i, double value); - double getObjective(int i); - int getNumberOfObjectives(); - int getNumberOfVariables(); - string toString(); - Variable ** getDecisionVariables(); - void setDecisionVariables(Variable ** variables); - bool isMarked(); - void mark(); - void unMark(); - void setRank(int value); - int getRank(); - void setOverallConstraintViolation(double value); - double getOverallConstraintViolation(); - void setNumberOfViolatedConstraints(int value); - int getNumberOfViolatedConstraints(); - void setLocation(int location); - int getLocation(); - void setType(SolutionType * type); - SolutionType *getType(); - double getAggregativeValue(); - Problem * getProblem() ; - //int getNumberOfBits(); + void setDistanceToSolutionSet(double distance); + double getDistanceToSolutionSet(); + void setKDistance(double distance); + double getKDistance(); + void setCrowdingDistance(double distance); + double getCrowdingDistance(); + void setFitness(double fitness); + double getFitness(); + void setObjective(int i, double value); + double getObjective(int i); + int getNumberOfObjectives(); + int getNumberOfVariables(); + std::string toString(); + Variable ** getDecisionVariables(); + void setDecisionVariables(Variable ** variables); + bool isMarked(); + void mark(); + void unMark(); + void setRank(int value); + int getRank(); + void setOverallConstraintViolation(double value); + double getOverallConstraintViolation(); + void setNumberOfViolatedConstraints(int value); + int getNumberOfViolatedConstraints(); + void setLocation(int location); + int getLocation(); + void setType(SolutionType * type); + SolutionType *getType(); + double getAggregativeValue(); + Problem * getProblem() ; + //int getNumberOfBits(); }; diff --git a/src/core/SolutionSet.cpp b/src/core/SolutionSet.cpp index ef9d3be..b4edde1 100644 --- a/src/core/SolutionSet.cpp +++ b/src/core/SolutionSet.cpp @@ -28,8 +28,9 @@ * Constructor. * Creates an unbounded solution set. */ -SolutionSet::SolutionSet () { - capacity_ = 0; +SolutionSet::SolutionSet () +{ + capacity_ = 0; } // SolutionSet @@ -37,18 +38,21 @@ SolutionSet::SolutionSet () { * Creates a empty solutionSet with a maximum capacity. * @param maximumSize Maximum size. */ -SolutionSet::SolutionSet (int maximumSize) { - capacity_ = maximumSize; +SolutionSet::SolutionSet (int maximumSize) +{ + capacity_ = maximumSize; } // SolutionSet /** * Destructor */ -SolutionSet::~SolutionSet() { - for (int i = 0; i < solutionsList_.size(); i++) { - delete solutionsList_[i]; - } +SolutionSet::~SolutionSet() +{ + for (int i = 0; i < solutionsList_.size(); i++) + { + delete solutionsList_[i]; + } } // ~SolutionSet @@ -58,13 +62,15 @@ SolutionSet::~SolutionSet() { * @return True If the Solution has been inserted, false * otherwise. */ -bool SolutionSet::add(Solution * solution) { - if (solutionsList_.size() >= capacity_) { - cout << "Error in class SolutionSet the maximum capacity of the set has been reached" << endl; - exit(-1); - } - solutionsList_.push_back(solution); - return true; +bool SolutionSet::add(Solution * solution) +{ + if (solutionsList_.size() >= capacity_) + { + std::cout << "Error in class SolutionSet the maximum capacity of the set has been reached" << std::endl; + exit(-1); + } + solutionsList_.push_back(solution); + return true; } // add @@ -75,9 +81,10 @@ bool SolutionSet::add(Solution * solution) { * @return True If the Solution has been inserted, false * otherwise. */ -bool SolutionSet::add(int index, Solution * solution) { - solutionsList_.insert(solutionsList_.begin()+index, solution); - return true; +bool SolutionSet::add(int index, Solution * solution) +{ + solutionsList_.insert(solutionsList_.begin()+index, solution); + return true; } /** @@ -86,12 +93,14 @@ bool SolutionSet::add(int index, Solution * solution) { * @return The Solution at the position i. * @throws IndexOutOfBoundsException. */ -Solution * SolutionSet::get(int i) { - if (i < 0 || i >= solutionsList_.size()) { - cout << "Error in class SolutionSet trying to access to an element out of range" << endl; - exit(-1); - } - return solutionsList_[i]; +Solution * SolutionSet::get(int i) +{ + if (i < 0 || i >= solutionsList_.size()) + { + std::cout << "Error in class SolutionSet trying to access to an element out of range" << std::endl; + exit(-1); + } + return solutionsList_[i]; } // get @@ -99,8 +108,9 @@ Solution * SolutionSet::get(int i) { * Returns the maximum capacity of the solution set * @return The maximum capacity of the solution set */ -int SolutionSet::getMaxSize() { - return capacity_; +int SolutionSet::getMaxSize() +{ + return capacity_; } // getMaxSize @@ -108,20 +118,25 @@ int SolutionSet::getMaxSize() { * Sorts a SolutionSet using a Comparator. * @param comparator Comparator used to sort. */ -void SolutionSet::sort(Comparator * comparator){ - if (comparator == NULL) { - cout << "Error. No criterium for compare exist" << endl; - exit(-1); - } // if - for (int i = 0; i < solutionsList_.size(); i++) { - for (int j = i+1; j < solutionsList_.size(); j++) { - if ((comparator->compare(solutionsList_[i],solutionsList_[j]))==1) { - Solution *tmp = solutionsList_[i]; - solutionsList_[i] = solutionsList_[j]; - solutionsList_[j] = tmp; - } - } - } // At this point the solution set will be sorted +void SolutionSet::sort(Comparator * comparator) +{ + if (comparator == nullptr) + { + std::cout << "Error. No criterium for compare exist" << std::endl; + exit(-1); + } // if + for (int i = 0; i < solutionsList_.size(); i++) + { + for (int j = i+1; j < solutionsList_.size(); j++) + { + if ((comparator->compare(solutionsList_[i],solutionsList_[j]))==1) + { + Solution *tmp = solutionsList_[i]; + solutionsList_[i] = solutionsList_[j]; + solutionsList_[j] = tmp; + } + } + } // At this point the solution set will be sorted } // sort @@ -132,24 +147,28 @@ void SolutionSet::sort(Comparator * comparator){ * @return The index of the best Solution attending to the comparator or * -1 if the SolutionSet is empty */ -int SolutionSet::indexBest(Comparator *comparator) { - if (solutionsList_.empty()) { - return -1; - } - int index = 0; - Solution * bestKnown = solutionsList_[0]; - Solution * candidateSolution; - int flag; - for (int i = 1; i < solutionsList_.size(); i++) { - candidateSolution = solutionsList_[i]; - flag = comparator->compare(bestKnown, candidateSolution); - //cout << "flag: " << flag << endl; - if (flag == 1) { - index = i; - bestKnown = candidateSolution; +int SolutionSet::indexBest(Comparator *comparator) +{ + if (solutionsList_.empty()) + { + return -1; + } + int index = 0; + Solution * bestKnown = solutionsList_[0]; + Solution * candidateSolution; + int flag; + for (int i = 1; i < solutionsList_.size(); i++) + { + candidateSolution = solutionsList_[i]; + flag = comparator->compare(bestKnown, candidateSolution); + //std::cout << "flag: " << flag << std::endl; + if (flag == 1) + { + index = i; + bestKnown = candidateSolution; + } } - } - return index; + return index; } // indexBest @@ -160,13 +179,17 @@ int SolutionSet::indexBest(Comparator *comparator) { * @return The best Solution attending to the comparator or null * if the SolutionSet is empty */ -Solution * SolutionSet::best(Comparator * comparator){ - int indexBest = this->indexBest(comparator); - if (indexBest < 0) { - return NULL; - } else { - return solutionsList_[indexBest]; - } +Solution * SolutionSet::best(Comparator * comparator) +{ + int indexBest = this->indexBest(comparator); + if (indexBest < 0) + { + return nullptr; + } + else + { + return solutionsList_[indexBest]; + } } // best @@ -177,23 +200,27 @@ Solution * SolutionSet::best(Comparator * comparator){ * @return The index of the worst Solution attending to the comparator or * -1 if the SolutionSet is empty */ -int SolutionSet::indexWorst(Comparator * comparator){ - if (solutionsList_.empty()) { - return -1; - } - int index = 0; - Solution * worstKnown = solutionsList_[0]; - Solution * candidateSolution; - int flag; - for (int i = 1; i < solutionsList_.size(); i++) { - candidateSolution = solutionsList_[i]; - flag = comparator->compare(worstKnown, candidateSolution); - if (flag == -1) { - index = i; - worstKnown = candidateSolution; +int SolutionSet::indexWorst(Comparator * comparator) +{ + if (solutionsList_.empty()) + { + return -1; + } + int index = 0; + Solution * worstKnown = solutionsList_[0]; + Solution * candidateSolution; + int flag; + for (int i = 1; i < solutionsList_.size(); i++) + { + candidateSolution = solutionsList_[i]; + flag = comparator->compare(worstKnown, candidateSolution); + if (flag == -1) + { + index = i; + worstKnown = candidateSolution; + } } - } - return index; + return index; } // indexWorst @@ -204,13 +231,17 @@ int SolutionSet::indexWorst(Comparator * comparator){ * @return The worst Solution attending to the comparator or null * if the SolutionSet is empty */ -Solution * SolutionSet::worst(Comparator * comparator){ - int index = indexWorst(comparator); - if (index < 0) { - return NULL; - } else { - return solutionsList_[index]; - } +Solution * SolutionSet::worst(Comparator * comparator) +{ + int index = indexWorst(comparator); + if (index < 0) + { + return nullptr; + } + else + { + return solutionsList_[index]; + } } // worst @@ -218,8 +249,9 @@ Solution * SolutionSet::worst(Comparator * comparator){ * Returns the number of solutions in the SolutionSet. * @return The size of the SolutionSet. */ -int SolutionSet::size() { - return solutionsList_.size(); +int SolutionSet::size() +{ + return solutionsList_.size(); } // size @@ -228,19 +260,22 @@ int SolutionSet::size() { * objects into the set in a file. * @param path The output file name */ -void SolutionSet::printObjectivesToFile(string file){ - std::ofstream out(file.c_str()); - cout.setf(ios::fixed); - for (int i = 0; i < solutionsList_.size(); i++) { - int nObj = solutionsList_[i]->getNumberOfObjectives(); - for (int obj = 0; obj < nObj; obj++) { - out << solutionsList_[i]->getObjective(obj) << " "; - //cout << setprecision(15) << solutionsList_[i]->getObjective(obj) << " "; +void SolutionSet::printObjectivesToFile(std::string file) +{ + std::ofstream out(file.c_str()); + std::cout.setf(ios::fixed); + for (int i = 0; i < solutionsList_.size(); i++) + { + int nObj = solutionsList_[i]->getNumberOfObjectives(); + for (int obj = 0; obj < nObj; obj++) + { + out << solutionsList_[i]->getObjective(obj) << " "; + //std::cout << setprecision(15) << solutionsList_[i]->getObjective(obj) << " "; + } + out << std::endl; + //std::cout << std::endl; } - out << endl; - //cout << endl; - } - out.close(); + out.close(); } // printObjectivesToFile @@ -251,21 +286,27 @@ void SolutionSet::printObjectivesToFile(string file){ * @param append If the objectives will be appended in case a file * already exists */ -void SolutionSet::printObjectivesToFile(string file, bool append){ - if (append) { - std::fstream out(file.c_str(), std::ios::out | std::ios::app); - cout.setf(ios::fixed); - for (int i = 0; i < solutionsList_.size(); i++) { - int nObj = solutionsList_[i]->getNumberOfObjectives(); - for (int obj = 0; obj < nObj; obj++) { - out << solutionsList_[i]->getObjective(obj) << " "; - } - out << endl; +void SolutionSet::printObjectivesToFile(std::string file, bool append) +{ + if (append) + { + std::fstream out(file.c_str(), std::ios::out | std::ios::app); + std::cout.setf(ios::fixed); + for (int i = 0; i < solutionsList_.size(); i++) + { + int nObj = solutionsList_[i]->getNumberOfObjectives(); + for (int obj = 0; obj < nObj; obj++) + { + out << solutionsList_[i]->getObjective(obj) << " "; + } + out << std::endl; + } + out.close(); + } + else + { + this->printObjectivesToFile(file); } - out.close(); - } else { - this->printObjectivesToFile(file); - } } // printObjectivesToFile @@ -274,12 +315,14 @@ void SolutionSet::printObjectivesToFile(string file, bool append){ * solutions objects into the set in a file. * @param path The output file name */ -void SolutionSet::printVariablesToFile(string file) { - std::ofstream out(file.c_str()); - for (int i = 0; i < solutionsList_.size(); i++) { - out << solutionsList_[i]->toString() << endl ; - } - out.close(); +void SolutionSet::printVariablesToFile(std::string file) +{ + std::ofstream out(file.c_str()); + for (int i = 0; i < solutionsList_.size(); i++) + { + out << solutionsList_[i]->toString() << std::endl ; + } + out.close(); } // printVariablesToFile @@ -288,24 +331,30 @@ void SolutionSet::printVariablesToFile(string file) { * solutions objects into the set in a file. * @param path The output file name */ -void SolutionSet::printVariablesToFile(string file, bool append) { - if (append) { - std::fstream out(file.c_str(), std::ios::out | std::ios::app); - for (int i = 0; i < solutionsList_.size(); i++) { - out << solutionsList_[i]->toString() << endl ; +void SolutionSet::printVariablesToFile(std::string file, bool append) +{ + if (append) + { + std::fstream out(file.c_str(), std::ios::out | std::ios::app); + for (int i = 0; i < solutionsList_.size(); i++) + { + out << solutionsList_[i]->toString() << std::endl ; + } + out.close(); + } + else + { + this->printVariablesToFile(file); } - out.close(); - } else { - this->printVariablesToFile(file); - } } // printVariablesToFile /** * Empties the SolutionSet */ -void SolutionSet::clear(){ - solutionsList_.clear(); +void SolutionSet::clear() +{ + solutionsList_.clear(); } // clear @@ -313,12 +362,14 @@ void SolutionSet::clear(){ * Deletes the Solution at position i in the set. * @param i The position of the solution to remove. */ -void SolutionSet::remove(int i) { - if (i < 0 || i >= solutionsList_.size()) { - cout << "Error in class SolutionSet trying to access to an element out of range" << endl; - exit(-1); - } - solutionsList_.erase(solutionsList_.begin() + i); +void SolutionSet::remove(int i) +{ + if (i < 0 || i >= solutionsList_.size()) + { + std::cout << "Error in class SolutionSet trying to access to an element out of range" << std::endl; + exit(-1); + } + solutionsList_.erase(solutionsList_.begin() + i); } // remove @@ -328,16 +379,19 @@ void SolutionSet::remove(int i) { * @param solutionSet SolutionSet to join with the current solutionSet. * @return The result of the union operation. */ -SolutionSet * SolutionSet::join(SolutionSet *another) { - SolutionSet *result = - new SolutionSet(solutionsList_.size()+another->size()); - for (int i=0;iadd(new Solution(this->get(i))); - } - for (int i=0;isize();i++) { - result->add(new Solution(another->get(i))); - } - return result; +SolutionSet * SolutionSet::join(SolutionSet *another) +{ + SolutionSet *result = + new SolutionSet(solutionsList_.size()+another->size()); + for (int i=0; iadd(new Solution(this->get(i))); + } + for (int i=0; isize(); i++) + { + result->add(new Solution(another->get(i))); + } + return result; } // join @@ -346,12 +400,14 @@ SolutionSet * SolutionSet::join(SolutionSet *another) { * @param position The position of the solution to replace * @param solution The new solution */ -void SolutionSet::replace(int position, Solution *solution) { - if (position < 0 || position >= solutionsList_.size()) { - cout << "Error in class SolutionSet trying to access to an element out of range" << endl; - exit(-1); - } - solutionsList_[position] = solution; +void SolutionSet::replace(int position, Solution *solution) +{ + if (position < 0 || position >= solutionsList_.size()) + { + std::cout << "Error in class SolutionSet trying to access to an element out of range" << std::endl; + exit(-1); + } + solutionsList_[position] = solution; } // replace @@ -359,22 +415,27 @@ void SolutionSet::replace(int position, Solution *solution) { * Copies the objectives of the solution set to a matrix * @return A matrix containing the objectives */ -vector > SolutionSet::writeObjectivesToMatrix() { - vector > objectives; - //objectives = new double[size()][get(0).numberOfObjectives()]; - for (int i = 0; i < size(); i++) { - vector list; - for (int j = 0; j < get(0)->getNumberOfObjectives(); j++) { - list.push_back(get(i)->getObjective(j)); +std::vector SolutionSet::writeObjectivesToMatrix() +{ + std::vector objectives; + //objectives = snew double[size()][get(0).numberOfObjectives()]; + for (int i = 0; i < size(); i++) + { + VectorOfDouble list; + for (int j = 0; j < get(0)->getNumberOfObjectives(); j++) + { + list.push_back(get(i)->getObjective(j)); + } + objectives.push_back(list); } - objectives.push_back(list); - } - return objectives; + return objectives; } // writeObjectivesMatrix -void SolutionSet::printObjectives() { - for (int i = 0; i < solutionsList_.size(); i++) { - cout << solutionsList_.at(i)->toString() << endl; - } +void SolutionSet::printObjectives() +{ + for (int i = 0; i < solutionsList_.size(); i++) + { + std::cout << solutionsList_.at(i)->toString() << std::endl; + } } diff --git a/src/core/SolutionSet.h b/src/core/SolutionSet.h index 37f3749..b2ad35b 100644 --- a/src/core/SolutionSet.h +++ b/src/core/SolutionSet.h @@ -23,6 +23,7 @@ #ifndef __SOLUTION_SET__ #define __SOLUTION_SET__ +#include "JMetalHeader.h" #include #include #include @@ -33,7 +34,7 @@ #include #include -using namespace std; +using namespace JMetal; //class Solution ; class Comparator; @@ -42,44 +43,45 @@ class Comparator; * @class SolutionSet * @brief This class is aimed at representing a solution set **/ -class SolutionSet { +class SolutionSet +{ protected: - vector solutionsList_; - int capacity_; + VectorOfSolutionPtr solutionsList_; + int capacity_; public: - SolutionSet(); - SolutionSet(int maximumSize); - ~SolutionSet(); + SolutionSet(); + SolutionSet(int maximumSize); + ~SolutionSet(); - bool add(Solution * solution); - bool add(int index, Solution * solution); - Solution *get(int index); - int getMaxSize(); - void sort(Comparator * comparator); - int indexBest(Comparator * comparator); - Solution * best(Comparator * comparator); - int indexWorst(Comparator * comparator); - Solution * worst(Comparator * comparator); - int size(); - void printObjectivesToFile(string path); - void printObjectivesToFile(string path, bool append); - void printVariablesToFile(string file); - void printVariablesToFile(string file, bool append); - void clear(); - void clear(bool del); - void remove(int i); - void remove(int i, bool del); - SolutionSet * join(SolutionSet * another); - void replace(int position, Solution * solution); - void replace(int position, Solution * solution, bool del); - vector > writeObjectivesToMatrix(); - void printObjectives(); + bool add(Solution * solution); + bool add(int index, Solution * solution); + Solution *get(int index); + int getMaxSize(); + void sort(Comparator * comparator); + int indexBest(Comparator * comparator); + Solution * best(Comparator * comparator); + int indexWorst(Comparator * comparator); + Solution * worst(Comparator * comparator); + int size(); + void printObjectivesToFile(std::string path); + void printObjectivesToFile(std::string path, bool append); + void printVariablesToFile(std::string file); + void printVariablesToFile(std::string file, bool append); + void clear(); + void clear(bool del); + void remove(int i); + void remove(int i, bool del); + SolutionSet * join(SolutionSet * another); + void replace(int position, Solution * solution); + void replace(int position, Solution * solution, bool del); + std::vector writeObjectivesToMatrix(); + void printObjectives(); - //void reset() ; - //string toString(); + //void reset() ; + //std::string toString(); }; diff --git a/src/core/SolutionType.cpp b/src/core/SolutionType.cpp index fee2fcc..7d8b29c 100644 --- a/src/core/SolutionType.cpp +++ b/src/core/SolutionType.cpp @@ -28,8 +28,9 @@ * Constructor * @param problem The problem to solve **/ -SolutionType::SolutionType(Problem *problem) { - problem_ = problem; +SolutionType::SolutionType(Problem *problem) +{ + problem_ = problem; } /** @@ -43,19 +44,22 @@ SolutionType::~SolutionType() { } * @param decisionVariables * @return An array of variables **/ -Variable ** SolutionType::copyVariables(Variable **vars) { - int numberOfVar = problem_->getNumberOfVariables(); - int var; - Variable ** variables = new Variable*[numberOfVar]; +Variable ** SolutionType::copyVariables(Variable **vars) +{ + int numberOfVar = problem_->getNumberOfVariables(); + int var; + Variable ** variables = new Variable*[numberOfVar]; - if (variables == NULL) { - cout << "Error grave: Impossible to reserve memory for allocating a copy of variables" << endl; - exit(-1); - } + if (variables == nullptr) + { + std::cout << "Error grave: Impossible to reserve memory for allocating a copy of variables" << std::endl; + exit(-1); + } - for (var = 0; var < numberOfVar; var++) { - variables[var] = vars[var]->deepCopy(); - } + for (var = 0; var < numberOfVar; var++) + { + variables[var] = vars[var]->deepCopy(); + } - return variables; + return variables; } // copyVariables diff --git a/src/core/SolutionType.h b/src/core/SolutionType.h index 37cf3d4..fc5cad6 100644 --- a/src/core/SolutionType.h +++ b/src/core/SolutionType.h @@ -37,16 +37,17 @@ class Problem; * Advantages: Flexibility for defining different types of solutions * (mixing variable types, etc) **/ -class SolutionType { +class SolutionType +{ protected: - Problem *problem_; + Problem *problem_; public: - SolutionType(Problem *problem); - virtual ~SolutionType(); - virtual Variable **createVariables() = 0; - Variable **copyVariables(Variable **vars); + SolutionType(Problem *problem); + virtual ~SolutionType(); + virtual Variable **createVariables() = 0; + Variable **copyVariables(Variable **vars); }; // SolutionType diff --git a/src/core/Variable.cpp b/src/core/Variable.cpp index 6eb7035..7926a19 100644 --- a/src/core/Variable.cpp +++ b/src/core/Variable.cpp @@ -26,13 +26,13 @@ /** - * This is an abstract class for storing the variables composing a solution. + * This is an abstract class for storing the variables composing a solution. * Some examples of variables can be Real, Binary, etc. There is no guaratee * that those variables are implemented on the current version of this project */ -using namespace std; + ///** @@ -45,8 +45,8 @@ using namespace std; // * must redefine it. // */ //double Variable::getValue() { -// cout << "Class " << typeid(this).name() << " does not implement " << -// "method getValue" << endl; +// std::cout << "Class " << typeid(this).name() << " does not implement " << +// "method getValue" << std::endl; //} // getValue // // @@ -58,8 +58,8 @@ using namespace std; // * must redefine it. // */ //void Variable::setValue(double value) { -// cout << "Class " << typeid(this).name() << " does not implement " << -// "method setValue" << endl; +// std::cout << "Class " << typeid(this).name() << " does not implement " << +// "method setValue" << std::endl; //} // setValue @@ -71,8 +71,8 @@ using namespace std; * Those classes requiring this method must redefine it. */ //double Variable::getLowerBound() { -// cout << "Class " << typeid(this).name() << " does not implement " << -// "method getLowerBound" << endl; +// std::cout << "Class " << typeid(this).name() << " does not implement " << +// "method getLowerBound" << std::endl; //} // getLowerBound @@ -83,8 +83,8 @@ using namespace std; * program is terminated. Those classes requiring this method must redefine it. */ //double Variable::getUpperBound() { -// cout << "Class " << typeid(this).name() << " does not implement " << -// "method getUpperBound" << endl; +// std::cout << "Class " << typeid(this).name() << " does not implement " << +// "method getUpperBound" << std::endl; //} // getUpperBound @@ -100,9 +100,10 @@ Variable::~Variable() { /* do nothing */ } * is considered a fatal error by default and the program is terminated. * Those classes requiring this method must to redefine it. */ -void Variable::setLowerBound(double lowerBound) { - cout << "Class " << typeid(this).name() << " does not implement " << - "method setLowerBound" << endl; +void Variable::setLowerBound(double lowerBound) +{ + std::cout << "Class " << typeid(this).name() << " does not implement " << + "method setLowerBound" << std::endl; } // setLowerBound @@ -112,9 +113,10 @@ void Variable::setLowerBound(double lowerBound) { * is considered a fatal error by default, and the program is terminated. * Those classes requiring this method must redefine it. */ -void Variable::setUpperBound(double upperBound) { - cout << "Class " << typeid(this).name() << " does not implement " << - "method setUpperBound" << endl; +void Variable::setUpperBound(double upperBound) +{ + std::cout << "Class " << typeid(this).name() << " does not implement " << + "method setUpperBound" << std::endl; } // setUpperBound @@ -123,6 +125,7 @@ void Variable::setUpperBound(double upperBound) { * @return The type of the variable */ -string Variable::getVariableType() { - return typeid(this).name() ; +std::string Variable::getVariableType() +{ + return typeid(this).name() ; } // getVariableType diff --git a/src/core/Variable.h b/src/core/Variable.h index 7da680a..9b60d16 100644 --- a/src/core/Variable.h +++ b/src/core/Variable.h @@ -30,24 +30,25 @@ using namespace std ; /** - * This is an abstract class for storing the variables composing a solution. + * This is an abstract class for storing the variables composing a solution. * Some examples of variables can be Real, Binary, etc. There is no guarantee * that those variables are implemented on the current version of this project */ -class Variable { +class Variable +{ public: - virtual ~Variable() = 0; - virtual Variable * deepCopy() = 0; - virtual double getValue() = 0; - virtual void setValue(double value) = 0; - virtual double getLowerBound() = 0; - virtual double getUpperBound() = 0; - void setLowerBound(double bound); - void setUpperBound(double bound); - //void setVariableType(VariableType_ variableType); - string getVariableType(); - virtual string toString() = 0; + virtual ~Variable() = 0; + virtual Variable * deepCopy() = 0; + virtual double getValue() = 0; + virtual void setValue(double value) = 0; + virtual double getLowerBound() = 0; + virtual double getUpperBound() = 0; + void setLowerBound(double bound); + void setUpperBound(double bound); + //void setVariableType(VariableType_ variableType); + string getVariableType(); + virtual string toString() = 0; }; // Variable diff --git a/src/encodings/CMakeLists.txt b/src/encodings/CMakeLists.txt new file mode 100644 index 0000000..d7041cd --- /dev/null +++ b/src/encodings/CMakeLists.txt @@ -0,0 +1,2 @@ +add_subdirectory(solutionType) +add_subdirectory(variable) \ No newline at end of file diff --git a/src/encodings/solutionType/ArrayRealSolutionType.cpp b/src/encodings/solutionType/ArrayRealSolutionType.cpp index c49b7bf..a14bda3 100644 --- a/src/encodings/solutionType/ArrayRealSolutionType.cpp +++ b/src/encodings/solutionType/ArrayRealSolutionType.cpp @@ -28,24 +28,26 @@ * @param problem */ ArrayRealSolutionType::ArrayRealSolutionType(Problem * problem) -: SolutionType(problem) { } + : SolutionType(problem) { } /** * Creates the variables of the solution */ -Variable ** ArrayRealSolutionType::createVariables() { - int i; - - Variable **variables = new Variable*[1]; //malloc(sizeof(Real) * problem->getNumberOfVariables()); - if (problem_->getSolutionType() == NULL) { - cout << "Error grave: Impossible to reserve memory for variable type" << endl; - exit(-1); - } - - variables[0] = new ArrayReal(problem_->getNumberOfVariables(),problem_); - - return variables; +Variable ** ArrayRealSolutionType::createVariables() +{ + int i; + + Variable **variables = snew Variable*[1]; //malloc(sizeof(Real) * problem->getNumberOfVariables()); + if (problem_->getSolutionType() == nullptr) + { + std::cout << "Error grave: Impossible to reserve memory for variable type" << std::endl; + exit(-1); + } + + variables[0] = snew ArrayReal(problem_->getNumberOfVariables(),problem_); + + return variables; } // createVariables @@ -54,8 +56,9 @@ Variable ** ArrayRealSolutionType::createVariables() { * @param decisionVariables * @return An array of variables */ -Variable ** ArrayRealSolutionType::copyVariables(Variable ** vars) { - Variable **variables = new Variable*[1]; - variables[0] = vars[0]->deepCopy(); - return variables ; +Variable ** ArrayRealSolutionType::copyVariables(Variable ** vars) +{ + Variable **variables = snew Variable*[1]; + variables[0] = vars[0]->deepCopy(); + return variables ; } // copyVariables diff --git a/src/encodings/solutionType/ArrayRealSolutionType.h b/src/encodings/solutionType/ArrayRealSolutionType.h index 1d2c1a0..5e2f6ab 100644 --- a/src/encodings/solutionType/ArrayRealSolutionType.h +++ b/src/encodings/solutionType/ArrayRealSolutionType.h @@ -28,12 +28,13 @@ * Class representing the solution type of solutions composed of an ArrayReal * variable */ -class ArrayRealSolutionType : public SolutionType { +class ArrayRealSolutionType : public SolutionType +{ public: - ArrayRealSolutionType(Problem *problem); - Variable **createVariables(); - Variable **copyVariables(Variable ** vars); + ArrayRealSolutionType(Problem *problem); + Variable **createVariables(); + Variable **copyVariables(Variable ** vars); }; diff --git a/src/encodings/solutionType/BinaryRealSolutionType.cpp b/src/encodings/solutionType/BinaryRealSolutionType.cpp index ac07d72..5c79f9b 100644 --- a/src/encodings/solutionType/BinaryRealSolutionType.cpp +++ b/src/encodings/solutionType/BinaryRealSolutionType.cpp @@ -28,29 +28,32 @@ * @param problem */ BinaryRealSolutionType::BinaryRealSolutionType(Problem *problem) -: SolutionType(problem) { } + : SolutionType(problem) { } /** * Creates the variables of the solution * @param decisionVariables */ -Variable ** BinaryRealSolutionType::createVariables() { - - Variable **variables = new Variable*[problem_->getNumberOfVariables()]; //malloc(sizeof(Real) * problem->getNumberOfVariables()); - - for (int var = 0; var < problem_->getNumberOfVariables(); var++) { - if (problem_->getPrecision() == NULL) { - int * precision = new int[problem_->getNumberOfVariables()] ; - for (int i = 0; i < problem_->getNumberOfVariables(); i++) - precision[i] = BinaryReal::DEFAULT_PRECISION ; - problem_->setPrecision(precision) ; - } // if - variables[var] = new BinaryReal(problem_->getPrecision(var), - problem_->getLowerLimit(var), - problem_->getUpperLimit(var)); - } // for - - return variables; +Variable ** BinaryRealSolutionType::createVariables() +{ + + Variable **variables = snew Variable*[problem_->getNumberOfVariables()]; //malloc(sizeof(Real) * problem->getNumberOfVariables()); + + for (int var = 0; var < problem_->getNumberOfVariables(); var++) + { + if (problem_->getPrecision() == nullptr) + { + int * precision = snew int[problem_->getNumberOfVariables()] ; + for (int i = 0; i < problem_->getNumberOfVariables(); i++) + precision[i] = BinaryReal::DEFAULT_PRECISION ; + problem_->setPrecision(precision) ; + } // if + variables[var] = snew BinaryReal(problem_->getPrecision(var), + problem_->getLowerLimit(var), + problem_->getUpperLimit(var)); + } // for + + return variables; } // createVariables diff --git a/src/encodings/solutionType/BinaryRealSolutionType.h b/src/encodings/solutionType/BinaryRealSolutionType.h index 6e063e9..047815e 100644 --- a/src/encodings/solutionType/BinaryRealSolutionType.h +++ b/src/encodings/solutionType/BinaryRealSolutionType.h @@ -27,11 +27,12 @@ /** * This class is aimed at defining a Type encoding a Real solution **/ -class BinaryRealSolutionType : public SolutionType { +class BinaryRealSolutionType : public SolutionType +{ public: - BinaryRealSolutionType(Problem * problem); - Variable ** createVariables(); + BinaryRealSolutionType(Problem * problem); + Variable ** createVariables(); }; diff --git a/src/encodings/solutionType/BinarySolutionType.cpp b/src/encodings/solutionType/BinarySolutionType.cpp index 56c32bd..bb00881 100644 --- a/src/encodings/solutionType/BinarySolutionType.cpp +++ b/src/encodings/solutionType/BinarySolutionType.cpp @@ -28,44 +28,45 @@ * @param problem */ BinarySolutionType::BinarySolutionType(Problem *problem) -: SolutionType(problem) { } + : SolutionType(problem) { } /** * Creates the variables of the solution * @param decisionVariables */ -Variable **BinarySolutionType::createVariables() { - //BinaryReal * binaryReal; +Variable **BinarySolutionType::createVariables() +{ + //BinaryReal * binaryReal; - Variable **variables = new Variable*[problem_->getNumberOfVariables()]; //malloc(sizeof(Real) * problem->getNumberOfVariables()); -// if (problem_->variableType_ == NULL) { -// cout << "Error grave: Impossible to reserve memory for variable type" << endl; + Variable **variables = snew Variable*[problem_->getNumberOfVariables()]; //malloc(sizeof(Real) * problem->getNumberOfVariables()); +// if (problem_->variableType_ == nullptr) { +// std::cout << "Error grave: Impossible to reserve memory for variable type" << std::endl; // exit(-1); // } - - for (int var = 0; var < problem_->getNumberOfVariables(); var++) - variables[var] = new Binary(problem_->getLength(var)); - /* - for (int var = 0; var < problem_->getNumberOfVariables(); var++) { - if (problem_->getPrecision() == NULL) { - int * precision = new int[problem_->getNumberOfVariables()] ; - for (int i = 0; i < problem_->getNumberOfVariables(); i++) - precision[i] = BinaryReal::DEFAULT_PRECISION ; - problem_->setPrecision(precision) ; - } // if - variables[var] = new BinaryReal(problem_->getPrecision(var), - problem_->getLowerLimit(var), - problem_->getUpperLimit(var)); - } - */ -/* - Variable[] variables = new Variable[problem_.getNumberOfVariables()]; - for (int var = 0; var < problem_.getNumberOfVariables(); var++) - variables[var] = new Binary(problem_.getLength(var)); + for (int var = 0; var < problem_->getNumberOfVariables(); var++) + variables[var] = snew Binary(problem_->getLength(var)); + /* + for (int var = 0; var < problem_->getNumberOfVariables(); var++) { + if (problem_->getPrecision() == nullptr) { + int * precision = snew int[problem_->getNumberOfVariables()] ; + for (int i = 0; i < problem_->getNumberOfVariables(); i++) + precision[i] = BinaryReal::DEFAULT_PRECISION ; + problem_->setPrecision(precision) ; + } // if + variables[var] = new BinaryReal(problem_->getPrecision(var), + problem_->getLowerLimit(var), + problem_->getUpperLimit(var)); + } + */ + /* + Variable[] variables = new Variable[problem_.getNumberOfVariables()]; - return variables ; -*/ - return variables; + for (int var = 0; var < problem_.getNumberOfVariables(); var++) + variables[var] = new Binary(problem_.getLength(var)); + + return variables ; + */ + return variables; } // createVariables diff --git a/src/encodings/solutionType/BinarySolutionType.h b/src/encodings/solutionType/BinarySolutionType.h index 5cc68bd..6f66bb1 100644 --- a/src/encodings/solutionType/BinarySolutionType.h +++ b/src/encodings/solutionType/BinarySolutionType.h @@ -27,12 +27,13 @@ /** * This class is aimed at defining a Type encoding a Real solution **/ -class BinarySolutionType : public SolutionType { +class BinarySolutionType : public SolutionType +{ public: - BinarySolutionType(Problem *problem); - Variable **createVariables(); - + BinarySolutionType(Problem *problem); + Variable **createVariables(); + }; #endif diff --git a/src/encodings/solutionType/CMakeLists.txt b/src/encodings/solutionType/CMakeLists.txt new file mode 100644 index 0000000..294ec59 --- /dev/null +++ b/src/encodings/solutionType/CMakeLists.txt @@ -0,0 +1,3 @@ +file(GLOB SOURCES "*.cpp" "*.h") +ListToString(SOURCES ";" ${SOURCES}) +LIST_APPEND("${SOURCES}") \ No newline at end of file diff --git a/src/encodings/solutionType/RealSolutionType.cpp b/src/encodings/solutionType/RealSolutionType.cpp index d0e3590..d4d3178 100644 --- a/src/encodings/solutionType/RealSolutionType.cpp +++ b/src/encodings/solutionType/RealSolutionType.cpp @@ -29,25 +29,28 @@ * @param problem */ RealSolutionType::RealSolutionType(Problem *problem) -: SolutionType(problem) { } + : SolutionType(problem) { } /** * Creates the variables of the solution * @param decisionVariables */ -Variable **RealSolutionType::createVariables() { - int i; - - Variable **variables = new Variable*[problem_->getNumberOfVariables()]; //malloc(sizeof(Real) * problem->getNumberOfVariables()); - if (variables == NULL) { - cout << "Error grave: Impossible to reserve memory for variable type" << endl; - exit(-1); - } - - for (i = 0; i < problem_->getNumberOfVariables(); i++) { - variables[i] = new Real(problem_->getLowerLimit(i),problem_->getUpperLimit(i)); - } - - return variables; +Variable **RealSolutionType::createVariables() +{ + int i; + + Variable **variables = new Variable*[problem_->getNumberOfVariables()]; //malloc(sizeof(Real) * problem->getNumberOfVariables()); + if (variables == nullptr) + { + std::cout << "Error grave: Impossible to reserve memory for variable type" << std::endl; + exit(-1); + } + + for (i = 0; i < problem_->getNumberOfVariables(); i++) + { + variables[i] = new Real(problem_->getLowerLimit(i),problem_->getUpperLimit(i)); + } + + return variables; } // createVariables diff --git a/src/encodings/solutionType/RealSolutionType.h b/src/encodings/solutionType/RealSolutionType.h index ecc9a22..1a0023e 100644 --- a/src/encodings/solutionType/RealSolutionType.h +++ b/src/encodings/solutionType/RealSolutionType.h @@ -29,11 +29,12 @@ /** * This class is aimed at defining a Type encoding a Real solution **/ -class RealSolutionType : public SolutionType { +class RealSolutionType : public SolutionType +{ public: - RealSolutionType(Problem *problem); - Variable **createVariables(); + RealSolutionType(Problem *problem); + Variable **createVariables(); }; diff --git a/src/encodings/variable/ArrayReal.cpp b/src/encodings/variable/ArrayReal.cpp index b0a0786..84b4464 100644 --- a/src/encodings/variable/ArrayReal.cpp +++ b/src/encodings/variable/ArrayReal.cpp @@ -2,6 +2,7 @@ // // Author: // Esteban López-Camacho +// Sérgio Vieira // // Copyright (c) 2011 Antonio J. Nebro, Juan J. Durillo // @@ -25,10 +26,11 @@ /** * Constructor */ -ArrayReal::ArrayReal() { - problem_ = NULL; - size_ = 0; - array_ = NULL; +ArrayReal::ArrayReal() +{ + problem_ = nullptr; + size_ = 0; + //array_ = nullptr; } // Constructor @@ -36,16 +38,19 @@ ArrayReal::ArrayReal() { * Constructor * @param size Size of the array */ -ArrayReal::ArrayReal(int size, Problem * problem) { - problem_ = problem; - size_ = size; - array_ = new double[size_]; - - for (int i = 0; i < size_ ; i++) { - array_[i] = PseudoRandom::randDouble()*(problem_->getUpperLimit(i)- - problem_->getLowerLimit(i))+ - problem_->getLowerLimit(i); - } // for +ArrayReal::ArrayReal(int size, Problem * problem) +{ + problem_ = problem; + size_ = size; + //array_ = snew double[size_]; + array_.assign(size_, 0.0); + + for (int i = 0; i < size_ ; i++) + { + array_[i] = PseudoRandom::randDouble()*(problem_->getUpperLimit(i)- + problem_->getLowerLimit(i))+ + problem_->getLowerLimit(i); + } // for } // Constructor @@ -53,22 +58,26 @@ ArrayReal::ArrayReal(int size, Problem * problem) { * Copy Constructor * @param arrayReal The arrayDouble to copy */ -ArrayReal::ArrayReal(ArrayReal * arrayReal) { - problem_ = arrayReal->problem_ ; - size_ = arrayReal->size_; - array_ = new double[size_]; - - for (int i = 0; i < size_; i++) { - array_[i] = arrayReal->array_[i]; - } // for +ArrayReal::ArrayReal(ArrayReal * arrayReal) +{ + problem_ = arrayReal->problem_ ; + size_ = arrayReal->size_; + //array_ = snew double[size_]; + array_.assign(size_, 0.0); + + for (int i = 0; i < size_; i++) + { + array_[i] = arrayReal->array_[i]; + } // for } // Copy Constructor /** * Destructor */ -ArrayReal::~ArrayReal() { - delete [] array_; +ArrayReal::~ArrayReal() +{ + //delete [] array_; } // ~ArrayReal @@ -76,8 +85,9 @@ ArrayReal::~ArrayReal() { * Creates an exact copy of a BinaryReal object. * @return The copy of the object */ -Variable * ArrayReal::deepCopy() { - return new ArrayReal(this); +Variable * ArrayReal::deepCopy() +{ + return snew ArrayReal(this); } // deepCopy @@ -85,8 +95,9 @@ Variable * ArrayReal::deepCopy() { * Returns the length of the arrayReal. * @return The length */ -int ArrayReal::getLength(){ - return size_; +int ArrayReal::getLength() +{ + return size_; } // getLength @@ -95,18 +106,21 @@ int ArrayReal::getLength(){ * @param index Index of value to be returned * @return the value in position index */ -double ArrayReal::getValue(int index) { - if ((index >= 0) && (index < size_)) - return array_[index] ; - else { - cerr << "ArrayReal.getValue: index value (" << index << ") invalid" << endl; - exit(-1); - } // if +double ArrayReal::getValue(int index) +{ + if ((index >= 0) && (index < size_)) + return array_[index] ; + else + { + cerr << "ArrayReal.getValue: index value (" << index << ") invalid" << std::endl; + exit(-1); + } // if } // getValue -double ArrayReal::getValue() { - cerr << "ERROR: ArrayReal::getValue() without index" << endl; - exit(-1); +double ArrayReal::getValue() +{ + cerr << "ERROR: ArrayReal::getValue() without index" << std::endl; + exit(-1); } // getValue @@ -115,16 +129,19 @@ double ArrayReal::getValue() { * @param index Index of value to be returned * @param value The value to be set in position index */ -void ArrayReal::setValue(int index, double value) { - if ((index >= 0) && (index < size_)) - array_[index] = value; - else { - cout << "ArrayReal.getValue: index value (" << index << ") invalid" << endl; - } // if +void ArrayReal::setValue(int index, double value) +{ + if ((index >= 0) && (index < size_)) + array_[index] = value; + else + { + std::cout << "ArrayReal.getValue: index value (" << index << ") invalid" << std::endl; + } // if } // setValue -void ArrayReal::setValue(double value) { - cout << "ERROR: ArrayReal::setValue(value) without index" << endl; +void ArrayReal::setValue(double value) +{ + std::cout << "ERROR: ArrayReal::setValue(value) without index" << std::endl; } // setValue @@ -133,18 +150,21 @@ void ArrayReal::setValue(double value) { * @param index The index of the value * @return the lower bound */ -double ArrayReal::getLowerBound(int index) { - if ((index >= 0) && (index < size_)) - return problem_->getLowerLimit(index) ; - else { - cerr << "ArrayReal.getValue: index value (" << index << ") invalid" << endl; - exit(-1); - } // if +double ArrayReal::getLowerBound(int index) +{ + if ((index >= 0) && (index < size_)) + return problem_->getLowerLimit(index) ; + else + { + cerr << "ArrayReal.getValue: index value (" << index << ") invalid" << std::endl; + exit(-1); + } // if } // getLowerBound -double ArrayReal::getLowerBound() { - cerr << "ERROR: ArrayReal::getLowerBound() without index" << endl; - exit(-1); +double ArrayReal::getLowerBound() +{ + cerr << "ERROR: ArrayReal::getLowerBound() without index" << std::endl; + exit(-1); } // getLowerBound @@ -153,30 +173,35 @@ double ArrayReal::getLowerBound() { * @param index The index of the value * @return the upper bound */ -double ArrayReal::getUpperBound(int index) { - if ((index >= 0) && (index < size_)) - return problem_->getUpperLimit(index); - else { - cerr << "ArrayReal.getValue: index value (" << index << ") invalid" << endl; - exit(-1); - } // if +double ArrayReal::getUpperBound(int index) +{ + if ((index >= 0) && (index < size_)) + return problem_->getUpperLimit(index); + else + { + cerr << "ArrayReal.getValue: index value (" << index << ") invalid" << std::endl; + exit(-1); + } // if } // getLowerBound -double ArrayReal::getUpperBound() { - cerr << "ERROR: ArrayReal::getUpperBound() without index" << endl; - exit(-1); +double ArrayReal::getUpperBound() +{ + cerr << "ERROR: ArrayReal::getUpperBound() without index" << std::endl; + exit(-1); } // getUpperBound /** - * Returns a string representing the object + * Returns a std::string representing the object * @return The string */ -string ArrayReal::toString(){ - std::ostringstream ss; - for (int i = 0; i < (size_ - 1); i ++) { - ss << array_[i] << " "; - } - ss << array_[size_ -1]; - return ss.str(); +std::string ArrayReal::toString() +{ + std::ostringstream ss; + for (int i = 0; i < (size_ - 1); i ++) + { + ss << array_[i] << " "; + } + ss << array_[size_ -1]; + return ss.str(); } // toString diff --git a/src/encodings/variable/ArrayReal.h b/src/encodings/variable/ArrayReal.h index 83e11ef..d3f829f 100644 --- a/src/encodings/variable/ArrayReal.h +++ b/src/encodings/variable/ArrayReal.h @@ -2,6 +2,7 @@ // // Author: // Esteban López-Camacho +// Sérgio Vieira // // Copyright (c) 2011 Antonio J. Nebro, Juan J. Durillo // @@ -30,31 +31,31 @@ * Class implementing a decision variable representing an array of real values. * The real values of the array have their own bounds. */ -class ArrayReal : public Variable { - -public: - - double * array_; - Problem * problem_; - int size_; - - ArrayReal(); - ArrayReal(int size, Problem * problem); - ArrayReal(ArrayReal * arrayReal); - ~ArrayReal(); - - Variable * deepCopy(); - int getLength(); - double getValue(int index); - void setValue(int index, double value); - double getLowerBound(int index); - double getUpperBound(int index); - string toString(); - - void setValue(double value); - double getValue(); - double getLowerBound(); - double getUpperBound(); +class ArrayReal : public Variable +{ +protected: + JMetal::VectorOfDouble array_; +public: + Problem * problem_ = nullptr; + int size_; + + ArrayReal(); + ArrayReal(int size, Problem * problem); + ArrayReal(ArrayReal * arrayReal); + ~ArrayReal(); + + Variable * deepCopy(); + int getLength(); + double getValue(int index); + void setValue(int index, double value); + double getLowerBound(int index); + double getUpperBound(int index); + std::string toString(); + + void setValue(double value); + double getValue(); + double getLowerBound(); + double getUpperBound(); }; #endif diff --git a/src/encodings/variable/Binary.cpp b/src/encodings/variable/Binary.cpp index 899aeaa..8929987 100644 --- a/src/encodings/variable/Binary.cpp +++ b/src/encodings/variable/Binary.cpp @@ -2,6 +2,7 @@ // // Author: // Esteban López-Camacho +// Sérgio Vieira // // Copyright (c) 2011 Antonio J. Nebro, Juan J. Durillo // @@ -25,9 +26,10 @@ /** * Default constructor. */ -Binary::Binary() { - bits_ = NULL ; - numberOfBits_ = -1 ; +Binary::Binary() +{ + bits_ = nullptr ; + numberOfBits_ = -1 ; } //Binary @@ -35,18 +37,23 @@ Binary::Binary() { * Constructor * @param numberOfBits Length of the bit string */ -Binary::Binary(int numberOfBits){ - numberOfBits_ = numberOfBits; - - bits_ = new vector(numberOfBits_, false) ; - - for (int i = 0; i < numberOfBits_; i++){ - if (PseudoRandom::randDouble() < 0.5) { - (*bits_)[i] = true ; - } else { - (*bits_)[i] = false ; +Binary::Binary(int numberOfBits) +{ + numberOfBits_ = numberOfBits; + + bits_ = snew VectorOfBoolean(numberOfBits_, false) ; + + for (int i = 0; i < numberOfBits_; i++) + { + if (PseudoRandom::randDouble() < 0.5) + { + (*bits_)[i] = true ; + } + else + { + (*bits_)[i] = false ; + } } - } } //Binary @@ -54,20 +61,23 @@ Binary::Binary(int numberOfBits){ * Copy constructor. * @param variable The Binary variable to copy. */ -Binary::Binary(Binary * variable){ - numberOfBits_ = variable->getNumberOfBits(); - bits_ = new vector(numberOfBits_, false) ; - for (int i = 0; i < numberOfBits_; i++) { - (*bits_)[i] = (*variable->bits_)[i] ; - } +Binary::Binary(Binary * variable) +{ + numberOfBits_ = variable->getNumberOfBits(); + bits_ = snew VectorOfBoolean(numberOfBits_, false) ; + for (int i = 0; i < numberOfBits_; i++) + { + (*bits_)[i] = (*variable->bits_)[i] ; + } } //Binary /** * Destructor */ -Binary::~Binary() { - delete bits_; +Binary::~Binary() +{ + delete bits_; } //~Binary @@ -78,8 +88,9 @@ Binary::~Binary() { * value encoded in the binary string. As generic variables do not encode any * value, this method do noting */ -void Binary::decode() { - //do nothing +void Binary::decode() +{ + //do nothing } //decode @@ -87,8 +98,9 @@ void Binary::decode() { * Creates an exact copy of a Binary object * @return An exact copy of the object. **/ -Variable * Binary::deepCopy() { - return new Binary(this); +Variable * Binary::deepCopy() +{ + return snew Binary(this); } //deepCopy @@ -96,8 +108,9 @@ Variable * Binary::deepCopy() { * Returns the length of the binary string. * @return The length */ -int Binary::getNumberOfBits(){ - return numberOfBits_; +int Binary::getNumberOfBits() +{ + return numberOfBits_; } //getNumberOfBits @@ -106,8 +119,9 @@ int Binary::getNumberOfBits(){ * @param bit The bit to retrieve * @return The ith bit */ -bool Binary::getIth(int bit){ - return (*bits_)[bit]; +bool Binary::getIth(int bit) +{ + return (*bits_)[bit]; } //getIth /** @@ -115,79 +129,91 @@ bool Binary::getIth(int bit){ * @param bit The bit to flip */ -void Binary::flip(int bit){ - (*bits_)[bit].flip(); +void Binary::flip(int bit) +{ + (*bits_)[bit].flip(); } //blip /** * Sets the value of the ith bit. * @param bit The bit to set */ -void Binary::setIth(int bit, bool value){ - (*bits_)[bit] = value ; +void Binary::setIth(int bit, bool value) +{ + (*bits_)[bit] = value ; } //getNumberOfBits /** * Obtain the hamming distance between two binary strings -* @param other The binary string to compare +* @param other The binary std::string to compare * @return The hamming distance */ -int Binary::hammingDistance(Binary * other) { - int distance = 0; - int i = 0; - while (i < bits_->size()) { - if ((*bits_)[i] != (*other->bits_)[i]) { - distance++; +int Binary::hammingDistance(Binary * other) +{ + int distance = 0; + int i = 0; + while (i < bits_->size()) + { + if ((*bits_)[i] != (*other->bits_)[i]) + { + distance++; + } + i++; } - i++; - } - return distance; + return distance; } // hammingDistance /** - * Returns a string representing the object. + * Returns a std::string representing the object. * @return the string. */ -string Binary::toString() { - vector::iterator it; - string str = "" ; - for(it = bits_->begin(); it != bits_->end(); it++) { - if (*it == true) - str += "1" ; - else - str += "0" ; - } - return str ; +std::string Binary::toString() +{ + VectorOfBoolean::iterator it; + std::string str = "" ; + for(it = bits_->begin(); it != bits_->end(); it++) + { + if (*it == true) + str += "1" ; + else + str += "0" ; + } + return str ; } // toString /* * Returns the number of 1's in the binary variable */ -int Binary::cardinality() { - int counter = 0 ; - vector::iterator it; - for(it = bits_->begin(); it != bits_->end(); it++) - if (*it == true) - counter ++ ; - return counter ; +int Binary::cardinality() +{ + int counter = 0 ; + VectorOfBoolean::iterator it; + for(it = bits_->begin(); it != bits_->end(); it++) + if (*it == true) + counter ++ ; + return counter ; } -double Binary::getValue() { - return 0.0; +double Binary::getValue() +{ + return 0.0; } -void Binary::setValue(double value) { - //value_ = value; +void Binary::setValue(double value) +{ + //value_ = value; } -double Binary::getLowerBound() { - // return 0.0; - exit(-1); +double Binary::getLowerBound() +{ + // return 0.0; + exit(-1); } -double Binary::getUpperBound() { +double Binary::getUpperBound() +{ // return 0.0; - exit(-1); + exit(-1); } diff --git a/src/encodings/variable/Binary.h b/src/encodings/variable/Binary.h index 9c34140..ad21695 100644 --- a/src/encodings/variable/Binary.h +++ b/src/encodings/variable/Binary.h @@ -2,6 +2,7 @@ // // Author: // Esteban López-Camacho +// Sérgio Vieira // // Copyright (c) 2011 Antonio J. Nebro, Juan J. Durillo // @@ -22,44 +23,47 @@ #ifndef Binary_h #define Binary_h +#include "JMetalHeader.h" #include #include -#include #include #include +using namespace JMetal; + /** - * This class implements a generic binary string variable.It can be used as - * a base class other binary string based classes (e.g., binary coded integer + * This class implements a generic binary std::string variable.It can be used as + * a base class other binary std::string based classes (e.g., binary coded integer * or real variables). */ -class Binary : public Variable { +class Binary : public Variable +{ public: - Binary(); - Binary(int numberOfBits); - Binary(Binary * variable); - ~Binary(); + Binary(); + Binary(int numberOfBits); + Binary(Binary * variable); + ~Binary(); - void decode(); - Variable * deepCopy(); - int getNumberOfBits(); - bool getIth(int bit); - void setIth(int bit, bool value); - void flip(int bit) ; - int hammingDistance(Binary * other); - string toString(); - int cardinality() ; + void decode(); + Variable * deepCopy(); + int getNumberOfBits(); + bool getIth(int bit); + void setIth(int bit, bool value); + void flip(int bit) ; + int hammingDistance(Binary * other); + std::string toString(); + int cardinality() ; - double getValue(); - void setValue(double value); - double getLowerBound(); - double getUpperBound(); + double getValue(); + void setValue(double value); + double getLowerBound(); + double getUpperBound(); protected: - vector * bits_; - int numberOfBits_; + VectorOfBoolean * bits_ = nullptr; + int numberOfBits_; }; #endif diff --git a/src/encodings/variable/BinaryReal.cpp b/src/encodings/variable/BinaryReal.cpp index 1e9cc58..88d34b5 100644 --- a/src/encodings/variable/BinaryReal.cpp +++ b/src/encodings/variable/BinaryReal.cpp @@ -2,6 +2,7 @@ // // Author: // Esteban López-Camacho +// Sérgio Vieira // // Copyright (c) 2011 Antonio J. Nebro, Juan J. Durillo // @@ -41,10 +42,11 @@ BinaryReal::BinaryReal() : Binary() { } * @param upperBound The upper limit for the variable. */ BinaryReal::BinaryReal(int numberOfBits, double lowerBound, double upperBound) -: Binary(numberOfBits) { - lowerBound_ = lowerBound; - upperBound_ = upperBound; - this->decode(); + : Binary(numberOfBits) +{ + lowerBound_ = lowerBound; + upperBound_ = upperBound; + this->decode(); } //BinaryReal @@ -52,10 +54,11 @@ BinaryReal::BinaryReal(int numberOfBits, double lowerBound, double upperBound) * Copy constructor * @param variable The variable to copy */ -BinaryReal::BinaryReal(BinaryReal * variable) : Binary (variable) { - lowerBound_ = variable->lowerBound_; - upperBound_ = variable->upperBound_; - value_ = variable->value_; +BinaryReal::BinaryReal(BinaryReal * variable) : Binary (variable) +{ + lowerBound_ = variable->lowerBound_; + upperBound_ = variable->upperBound_; + value_ = variable->value_; } //BinaryReal @@ -66,21 +69,24 @@ BinaryReal::~BinaryReal() { /* do nothing */ } /** - * Decodes the real value encoded in the binary string represented + * Decodes the real value encoded in the binary std::string represented * by the BinaryReal object. The decoded value is stores in the * value_ field and can be accessed by the method * getValue. */ -void BinaryReal::decode(){ - double value = 0.0; - for (int i = 0; i < numberOfBits_; i++) { - if ((*bits_)[i] == true) { - value += pow(2.0,i); +void BinaryReal::decode() +{ + double value = 0.0; + for (int i = 0; i < numberOfBits_; i++) + { + if ((*bits_)[i] == true) + { + value += pow(2.0,i); + } } - } - value_ = value * (upperBound_ - lowerBound_) / - (pow(2.0,numberOfBits_)-1.0); - value_ += lowerBound_; + value_ = value * (upperBound_ - lowerBound_) / + (pow(2.0,numberOfBits_)-1.0); + value_ += lowerBound_; } //decode @@ -88,13 +94,15 @@ void BinaryReal::decode(){ * Returns the double value of the variable. * @return the double value. */ -double BinaryReal::getValue() { - return value_; +double BinaryReal::getValue() +{ + return value_; } //getValue -void BinaryReal::setValue(double value) { - value_ = value; +void BinaryReal::setValue(double value) +{ + value_ = value; } @@ -102,8 +110,9 @@ void BinaryReal::setValue(double value) { * Creates an exact copy of a BinaryReal object. * @return The copy of the object */ -Variable * BinaryReal::deepCopy() { - return new BinaryReal(this); +Variable * BinaryReal::deepCopy() +{ + return snew BinaryReal(this); } //deepCopy @@ -111,8 +120,9 @@ Variable * BinaryReal::deepCopy() { * Returns the lower bound of the variable. * @return the lower bound. */ -double BinaryReal::getLowerBound() { - return lowerBound_; +double BinaryReal::getLowerBound() +{ + return lowerBound_; } // getLowerBound @@ -120,8 +130,9 @@ double BinaryReal::getLowerBound() { * Returns the upper bound of the variable. * @return the upper bound. */ -double BinaryReal::getUpperBound() { - return upperBound_; +double BinaryReal::getUpperBound() +{ + return upperBound_; } // getUpperBound @@ -129,8 +140,9 @@ double BinaryReal::getUpperBound() { * Sets the lower bound of the variable. * @param lowerBound the lower bound. */ -void BinaryReal::setLowerBound(double lowerBound) { - lowerBound_ = lowerBound; +void BinaryReal::setLowerBound(double lowerBound) +{ + lowerBound_ = lowerBound; } // setLowerBound @@ -138,17 +150,19 @@ void BinaryReal::setLowerBound(double lowerBound) { * Sets the upper bound of the variable. * @param upperBound the upper bound. */ -void BinaryReal::setUpperBound(double upperBound) { - upperBound_ = upperBound; +void BinaryReal::setUpperBound(double upperBound) +{ + upperBound_ = upperBound; } // setUpperBound /** - * Returns a string representing the object. + * Returns a std::string representing the object. * @return the string. */ -string BinaryReal::toString() { - std::ostringstream ss; - ss << value_; - return ss.str(); +std::string BinaryReal::toString() +{ + std::ostringstream ss; + ss << value_; + return ss.str(); } // toString diff --git a/src/encodings/variable/BinaryReal.h b/src/encodings/variable/BinaryReal.h index 3967975..5c3bb6d 100644 --- a/src/encodings/variable/BinaryReal.h +++ b/src/encodings/variable/BinaryReal.h @@ -2,6 +2,7 @@ // // Author: // Esteban López-Camacho +// Sérgio Vieira // // Copyright (c) 2011 Antonio J. Nebro, Juan J. Durillo // @@ -31,32 +32,33 @@ * This class extends the Binary class to represent a Real variable encoded by * a binary string */ -class BinaryReal : public Binary { +class BinaryReal : public Binary +{ public: - static const int DEFAULT_PRECISION; + static const int DEFAULT_PRECISION; - BinaryReal(); - BinaryReal(int numberOfBits, double lowerBound, double upperBound); - BinaryReal(BinaryReal * variable); - ~BinaryReal(); + BinaryReal(); + BinaryReal(int numberOfBits, double lowerBound, double upperBound); + BinaryReal(BinaryReal * variable); + ~BinaryReal(); - void decode(); - double getValue(); - void setValue(double value); - Variable * deepCopy(); - double getLowerBound(); - double getUpperBound(); - void setLowerBound(double bound); - void setUpperBound(double bound); - string toString(); + void decode(); + double getValue(); + void setValue(double value); + Variable * deepCopy(); + double getLowerBound(); + double getUpperBound(); + void setLowerBound(double bound); + void setUpperBound(double bound); + std::string toString(); private: double value_; double lowerBound_ ; double upperBound_ ; - + }; // BinaryReal #endif diff --git a/src/encodings/variable/CMakeLists.txt b/src/encodings/variable/CMakeLists.txt new file mode 100644 index 0000000..294ec59 --- /dev/null +++ b/src/encodings/variable/CMakeLists.txt @@ -0,0 +1,3 @@ +file(GLOB SOURCES "*.cpp" "*.h") +ListToString(SOURCES ";" ${SOURCES}) +LIST_APPEND("${SOURCES}") \ No newline at end of file diff --git a/src/encodings/variable/Real.cpp b/src/encodings/variable/Real.cpp index 1f60de7..bf4d78c 100644 --- a/src/encodings/variable/Real.cpp +++ b/src/encodings/variable/Real.cpp @@ -23,35 +23,38 @@ #include -/** - * Empty constructor. +/** + * Empty constructor. * It will only initialize all the variables. **/ -Real::Real() { - value_ = 0.0; +Real::Real() +{ + value_ = 0.0; } // Real /** * Lower and Upper bounds based constructor. - * It will initialize the upper and lower bounds of the + * It will initialize the upper and lower bounds of the * variable and it will initialize its value to a random * value between those upper and lower bound values. **/ -Real::Real(double lowerBound, double upperBound) { - value_ = PseudoRandom::randDouble(lowerBound, upperBound); - lowerBound_ = lowerBound; - upperBound_ = upperBound; +Real::Real(double lowerBound, double upperBound) +{ + value_ = PseudoRandom::randDouble(lowerBound, upperBound); + lowerBound_ = lowerBound; + upperBound_ = upperBound; } // Real /** * Constructor */ -Real::Real(Variable * variable) { - lowerBound_ = variable->getLowerBound(); - upperBound_ = variable->getUpperBound(); - value_ = variable->getValue(); +Real::Real(Variable * variable) +{ + lowerBound_ = variable->getLowerBound(); + upperBound_ = variable->getUpperBound(); + value_ = variable->getValue(); } // Real @@ -65,8 +68,9 @@ Real::~Real() { /* do nothing */ } * Gets the value of the Real variable. * @return the value. */ -double Real::getValue() { - return value_; +double Real::getValue() +{ + return value_; } // getValue @@ -74,8 +78,9 @@ double Real::getValue() { * Sets the value of the variable. * @param value The value. */ -void Real::setValue(double value) { - value_ = value; +void Real::setValue(double value) +{ + value_ = value; } // setValue @@ -83,8 +88,9 @@ void Real::setValue(double value) { * Returns a exact copy of the Real variable * @return the copy */ -Variable *Real::deepCopy() { - return new Real(this); +Variable *Real::deepCopy() +{ + return new Real(this); } // deepCopy @@ -92,8 +98,9 @@ Variable *Real::deepCopy() { * Gets the lower bound of the variable. * @return the lower bound. */ -double Real::getLowerBound() { - return lowerBound_; +double Real::getLowerBound() +{ + return lowerBound_; } // getLowerBound @@ -101,8 +108,9 @@ double Real::getLowerBound() { * Gets the upper bound of the variable. * @return the upper bound. */ -double Real::getUpperBound() { - return upperBound_; +double Real::getUpperBound() +{ + return upperBound_; } // getUpperBound @@ -110,8 +118,9 @@ double Real::getUpperBound() { * Sets the lower bound of the variable. * @param lowerBound The lower bound. */ -void Real::setLowerBound(double bound) { - lowerBound_ = bound; +void Real::setLowerBound(double bound) +{ + lowerBound_ = bound; } // setLowerBound @@ -119,19 +128,21 @@ void Real::setLowerBound(double bound) { * Sets the upper bound of the variable. * @param upperBound The upper bound. */ -void Real::setUpperBound(double bound) { - upperBound_ = bound; +void Real::setUpperBound(double bound) +{ + upperBound_ = bound; } // setUpperBound /** - * Returns a string representing the object + * Returns a std::string representing the object * @return The string */ -string Real::toString(){ - std::ostringstream stringStream; - stringStream << value_ ; - string aux = stringStream.str() + " "; +std::string Real::toString() +{ + std::ostringstream stringStream; + stringStream << value_ ; + std::string aux = stringStream.str() + " "; - return aux ; + return aux ; } // toString diff --git a/src/encodings/variable/Real.h b/src/encodings/variable/Real.h index a67a076..c1e9ac2 100644 --- a/src/encodings/variable/Real.h +++ b/src/encodings/variable/Real.h @@ -29,28 +29,29 @@ /** * This class implements a Real value decision variable */ -class Real : public Variable { +class Real : public Variable +{ public: - Real(); - Real(double lowerBound, double upperBound); - Real(Variable * variable); - ~Real(); + Real(); + Real(double lowerBound, double upperBound); + Real(Variable * variable); + ~Real(); - double getValue(); - void setValue(double value); - Variable * deepCopy(); - double getLowerBound(); - double getUpperBound(); - void setLowerBound(double bound); - void setUpperBound(double bound); - string toString() ; + double getValue(); + void setValue(double value); + Variable * deepCopy(); + double getLowerBound(); + double getUpperBound(); + void setLowerBound(double bound); + void setUpperBound(double bound); + string toString() ; private: - double value_; - double lowerBound_ ; - double upperBound_ ; + double value_; + double lowerBound_ ; + double upperBound_ ; }; #endif diff --git a/src/experiments/CMakeLists.txt b/src/experiments/CMakeLists.txt new file mode 100644 index 0000000..762c9c8 --- /dev/null +++ b/src/experiments/CMakeLists.txt @@ -0,0 +1,6 @@ +file(GLOB SOURCES "*.cpp" "*.h") +ListToString(SOURCES ";" ${SOURCES}) +LIST_APPEND("${SOURCES}") +add_subdirectory(main) +add_subdirectory(settings) +add_subdirectory(util) diff --git a/src/experiments/Experiment.cpp b/src/experiments/Experiment.cpp index 3e07597..85d5eea 100644 --- a/src/experiments/Experiment.cpp +++ b/src/experiments/Experiment.cpp @@ -2,6 +2,7 @@ // // Author: // Esteban López-Camacho +// Sérgio Vieira // // Copyright (c) 2011 Antonio J. Nebro, Juan J. Durillo // @@ -30,70 +31,85 @@ Experiment::Experiment() {} -void Experiment::checkExperimentDirectory() { - int res = FileUtils::existsPath(experimentBaseDirectory_.c_str()); - switch (res) { - case 0: - cout << "Experiment directory does NOT exist. Creating" << endl; - if (FileUtils::createDirectory(experimentBaseDirectory_) == -1) { - cout << "Error creating directory" << endl; - exit(-1); +void Experiment::checkExperimentDirectory() +{ + int res = FileUtils::existsPath(experimentBaseDirectory_.c_str()); + switch (res) + { + case 0: + std::cout << "Experiment directory does NOT exist. Creating" << std::endl; + if (FileUtils::createDirectory(experimentBaseDirectory_) == -1) + { + std::cout << "Error creating directory" << std::endl; + exit(-1); + } + break; + case 1: + std::cout << "Experiment directory exists." << std::endl; + std::cout << "Experiment directory is a directory" << std::endl; + break; + case 2: + std::cout << "Experiment directory exists." << std::endl; + std::cout << "Experiment directory is not a directory. Deleting file and creating directory" << std::endl; + if( remove(experimentBaseDirectory_.c_str()) != 0 ) + { + std::cout << "Error deleting file." << std::endl; + exit(-1); + } + else + { + std::cout << "File successfully deleted." << std::endl; + } + if (FileUtils::createDirectory(experimentBaseDirectory_) == -1) + { + std::cout << "Error creating directory" << std::endl; + exit(-1); + } + break; + case -1: + std::cout << "Error checking experiment directory" << std::endl; + exit(-1); } - break; - case 1: - cout << "Experiment directory exists." << endl; - cout << "Experiment directory is a directory" << endl; - break; - case 2: - cout << "Experiment directory exists." << endl; - cout << "Experiment directory is not a directory. Deleting file and creating directory" << endl; - if( remove(experimentBaseDirectory_.c_str()) != 0 ) { - cout << "Error deleting file." << endl; - exit(-1); - } else { - cout << "File successfully deleted." << endl; - } - if (FileUtils::createDirectory(experimentBaseDirectory_) == -1) { - cout << "Error creating directory" << endl; - exit(-1); - } - break; - case -1: - cout << "Error checking experiment directory" << endl; - exit(-1); - } } // checkExperimentDirectory -void Experiment::resetFile(string file) { - int res = FileUtils::existsPath(file.c_str()); - switch (res) { - case 0: - cout << "File (" << file << ") does NOT exist." << endl; - break; - case 1: - cout << "File (" << file << ") exists." << endl; - cout << "File (" << file << ") is a directory. Deleting directory." << endl; - if( remove(file.c_str()) != 0 ) { - cout << "Error deleting directory." << endl; - exit(-1); - } else { - cout << "Directory successfully deleted." << endl; - } - break; - case 2: - cout << "File (" << file << ") exists." << endl; - cout << "File (" << file << ") is a file. Deleting file." << endl; - if( remove(file.c_str()) != 0 ) { - cout << "Error deleting file." << endl; - exit(-1); - } else { - cout << "File successfully deleted." << endl; +void Experiment::resetFile(std::string file) +{ + int res = FileUtils::existsPath(file.c_str()); + switch (res) + { + case 0: + std::cout << "File (" << file << ") does NOT exist." << std::endl; + break; + case 1: + std::cout << "File (" << file << ") exists." << std::endl; + std::cout << "File (" << file << ") is a directory. Deleting directory." << std::endl; + if( remove(file.c_str()) != 0 ) + { + std::cout << "Error deleting directory." << std::endl; + exit(-1); + } + else + { + std::cout << "Directory successfully deleted." << std::endl; + } + break; + case 2: + std::cout << "File (" << file << ") exists." << std::endl; + std::cout << "File (" << file << ") is a file. Deleting file." << std::endl; + if( remove(file.c_str()) != 0 ) + { + std::cout << "Error deleting file." << std::endl; + exit(-1); + } + else + { + std::cout << "File successfully deleted." << std::endl; + } + break; + case -1: + std::cout << "Error checking file (" << file << ")" << std::endl; + exit(-1); } - break; - case -1: - cout << "Error checking file (" << file << ")" << endl; - exit(-1); - } } // resetFile diff --git a/src/experiments/Experiment.h b/src/experiments/Experiment.h index b4232eb..5e3e0ce 100644 --- a/src/experiments/Experiment.h +++ b/src/experiments/Experiment.h @@ -2,6 +2,7 @@ // // Author: // Esteban López-Camacho +// Sérgio Vieira // // Copyright (c) 2011 Antonio J. Nebro, Juan J. Durillo // @@ -21,35 +22,30 @@ #ifndef __EXPERIMENT__ #define __EXPERIMENT__ -#include -#include +#include "JMetalHeader.h" #include #include #include -using namespace std; +using namespace JMetal; /** * Abstract class representing jMetal experiments */ -class Experiment { - +class Experiment +{ public: - - string experimentName_; - vector algorithmNameList_; // List of the names of the algorithms to - // be executed - vector problemList_; // List of problems to be solved - string experimentBaseDirectory_; // Directory to store the results - int independentRuns_; // Number of independent runs per algorithm - bool isSingleObjective_; // If this experiment is a singleObjective one or not - - Experiment(); - - void checkExperimentDirectory(); - void resetFile(string file); - + std::string experimentName_; + VectorOfString algorithmNameList_; // List of the names of the algorithms to + // be executed + VectorOfString problemList_; // List of problems to be solved + std::string experimentBaseDirectory_; // Directory to store the results + int independentRuns_; // Number of independent runs per algorithm + bool isSingleObjective_; // If this experiment is a singleObjective one or not + Experiment(); + void checkExperimentDirectory(); + void resetFile(std::string file); }; #endif /* __EXPERIMENT__ */ diff --git a/src/experiments/ExperimentExecution.cpp b/src/experiments/ExperimentExecution.cpp index f33fd4e..a6684b0 100644 --- a/src/experiments/ExperimentExecution.cpp +++ b/src/experiments/ExperimentExecution.cpp @@ -2,6 +2,7 @@ // // Author: // Esteban López-Camacho +// Sérgio Vieira // // Copyright (c) 2011 Antonio J. Nebro, Juan J. Durillo // @@ -22,10 +23,12 @@ #include -void* executeRun(void* ctx) { - RunExperiment* cptr = (RunExperiment*)ctx; - cptr->run(); - //pthread_exit(0); +void* executeRun(void* ctx) +{ + RunExperiment* cptr = (RunExperiment*)ctx; + cptr->run(); + //pthread_exit(0); + return nullptr; } // executeRun @@ -34,21 +37,22 @@ void* executeRun(void* ctx) { * * Contains default settings */ -ExperimentExecution::ExperimentExecution() { +ExperimentExecution::ExperimentExecution() +{ - experimentName_ = "noName"; + experimentName_ = "noName"; - experimentBaseDirectory_ = ""; + experimentBaseDirectory_ = ""; - outputParetoFrontFile_ = "FUN"; - outputParetoSetFile_ = "VAR"; + outputParetoFrontFile_ = "FUN"; + outputParetoSetFile_ = "VAR"; - independentRuns_ = 0; + independentRuns_ = 0; - experimentIndividualListIndex_ = 0; - experimentIndividualListSize_ = -1; + experimentIndividualListIndex_ = 0; + experimentIndividualListSize_ = -1; - isSingleObjective_ = false; + isSingleObjective_ = false; } // ExperimentExecution @@ -56,86 +60,92 @@ ExperimentExecution::ExperimentExecution() { /** * Runs the experiment */ -void ExperimentExecution::runExperiment(int numberOfThreads) { - - checkExperimentDirectory(); - - map_["name"] = &experimentName_; - map_["experimentDirectory"] = &experimentBaseDirectory_; - map_["algorithmNameList"] = &algorithmNameList_; - map_["problemList"] = &problemList_; - map_["independentRuns"] = &independentRuns_; - map_["outputParetoFrontFile"] = &outputParetoFrontFile_; - map_["outputParetoSetFile"] = &outputParetoSetFile_; - - cout << "Initializing task list..." << endl; - //cout << "algorithmNameList_.size() = " << algorithmNameList_.size() << endl; - - experimentIndividualListSize_ = - problemList_.size() * algorithmNameList_.size() * independentRuns_; - for (int i=0; i threads; - RunExperiment ** experiments_ = new RunExperiment*[numberOfThreads]; - for (int i = 0; i < numberOfThreads; i++) { - experiments_[i] = new RunExperiment(this, map_, i, numberOfThreads, - problemList_.size(), i, &mtx); -// result = pthread_create(&p[i], NULL, executeRun, experiments_[i]); +// std::cout << "------- MUTEX OK ------" << std::endl ; + + //pthread_t * p = new pthread_t[numberOfThreads]; + //thread * p = new thread[numberOfThreads]; + std::vector threads; + RunExperiment ** experiments_ = snew RunExperiment*[numberOfThreads]; + for (int i = 0; i < numberOfThreads; i++) + { + experiments_[i] = snew RunExperiment(this, map_, i, numberOfThreads, + problemList_.size(), i, &mtx); +// result = pthread_create(&p[i], nullptr, executeRun, experiments_[i]); // if (result != 0) { // perror("ERROR WHILE CREATING THREADS"); // exit(-1) ; // } - threads.push_back(thread(executeRun, experiments_[i])); - } + threads.push_back(thread(executeRun, experiments_[i])); + } // for (int i = 0; i < numberOfThreads; i++) { -// result = pthread_join(p[i], NULL) ; -// cout << "Joined thread number " << (i+1) << "." <join(); // } - for (auto& th : threads) th.join(); + for (auto& th : threads) th.join(); - cout << "All the threads have finished." << endl; + std::cout << "All the threads have finished." << std::endl; - for (int i=0; i < experimentIndividualList_.size(); i++) { - delete experimentIndividualList_[i]; - } + for (int i=0; i < experimentIndividualList_.size(); i++) + { + delete experimentIndividualList_[i]; + } - delete [] algorithmSettingsList_; + delete [] algorithmSettingsList_; // delete [] p; - for (int i=0; i < numberOfThreads; i++) - delete experiments_[i]; - delete [] experiments_; + for (int i=0; i < numberOfThreads; i++) + delete experiments_[i]; + delete [] experiments_; } // runExperiment @@ -143,6 +153,7 @@ void ExperimentExecution::runExperiment(int numberOfThreads) { /** * Runs the experiment */ -void ExperimentExecution::runExperiment() { - runExperiment(1); +void ExperimentExecution::runExperiment() +{ + runExperiment(1); } // runExperiment diff --git a/src/experiments/ExperimentExecution.h b/src/experiments/ExperimentExecution.h index a209389..6071a3f 100644 --- a/src/experiments/ExperimentExecution.h +++ b/src/experiments/ExperimentExecution.h @@ -2,6 +2,7 @@ // // Author: // Esteban López-Camacho +// Sérgio Vieira // // Copyright (c) 2011 Antonio J. Nebro, Juan J. Durillo // @@ -33,37 +34,38 @@ #include #include -using namespace std; -class ExperimentExecution : public Experiment { + +class ExperimentExecution : public Experiment +{ private: - map map_; // Map used to send experiment parameters to threads + MapOfStringFunct map_; // Map used to send experiment parameters to threads public: - string outputParetoFrontFile_; // Name of the file containing the output - // Pareto front - string outputParetoSetFile_; // Name of the file containing the output Pareto - // set + std::string outputParetoFrontFile_; // Name of the file containing the output + // Pareto front + std::string outputParetoSetFile_; // Name of the file containing the output Pareto + // set - vector experimentIndividualList_; - Settings ** algorithmSettingsList_; - int experimentIndividualListIndex_; - int experimentIndividualListSize_; + std::vector experimentIndividualList_; + Settings ** algorithmSettingsList_; + int experimentIndividualListIndex_; + int experimentIndividualListSize_; - ExperimentExecution(); + ExperimentExecution(); - void runExperiment(int numberOfThreads); - void runExperiment(); + void runExperiment(int numberOfThreads); + void runExperiment(); - // TODO: Check different algorithmSettings configurations - // virtual void algorithmSettings(string problemName, int problemId, - // Algorithm ** algorithm) = 0; - // virtual Algorithm * algorithmSettings(string problemName) = 0; - virtual Algorithm * algorithmSettings(string problemName, int algorithmId, - int experimentIndividiualId) = 0; + // TODO: Check different algorithmSettings configurations + // virtual void algorithmSettings(std::string problemName, int problemId, + // Algorithm ** algorithm) = 0; + // virtual Algorithm * algorithmSettings(std::string problemName) = 0; + virtual Algorithm * algorithmSettings(std::string problemName, int algorithmId, + int experimentIndividiualId) = 0; }; // ExperimentExecution diff --git a/src/experiments/ExperimentIndividual.cpp b/src/experiments/ExperimentIndividual.cpp index 68239de..dac87bd 100644 --- a/src/experiments/ExperimentIndividual.cpp +++ b/src/experiments/ExperimentIndividual.cpp @@ -2,6 +2,7 @@ // // Author: // Esteban López-Camacho +// Sérgio Vieira // // Copyright (c) 2011 Antonio J. Nebro, Juan J. Durillo // @@ -23,29 +24,33 @@ /** * Constructor */ -ExperimentIndividual::ExperimentIndividual(int algorithmIndex, int problemIndex, int numRun) { - algorithmIndex_ = algorithmIndex; - problemIndex_ = problemIndex; - numRun_ = numRun; +ExperimentIndividual::ExperimentIndividual(int algorithmIndex, int problemIndex, int numRun) +{ + algorithmIndex_ = algorithmIndex; + problemIndex_ = problemIndex; + numRun_ = numRun; } /** * Return the algorithm index atribute */ -int ExperimentIndividual::getAlgorithmIndex() { - return algorithmIndex_; +int ExperimentIndividual::getAlgorithmIndex() +{ + return algorithmIndex_; } /** * Return the problem index atribute */ -int ExperimentIndividual::getProblemIndex() { - return problemIndex_; +int ExperimentIndividual::getProblemIndex() +{ + return problemIndex_; } /** * Return the algorithm index atribute */ -int ExperimentIndividual::getNumRun() { - return numRun_; +int ExperimentIndividual::getNumRun() +{ + return numRun_; } diff --git a/src/experiments/ExperimentIndividual.h b/src/experiments/ExperimentIndividual.h index 5f1b9e0..0304437 100644 --- a/src/experiments/ExperimentIndividual.h +++ b/src/experiments/ExperimentIndividual.h @@ -2,6 +2,7 @@ // // Author: // Esteban López-Camacho +// Sérgio Vieira // // Copyright (c) 2011 Antonio J. Nebro, Juan J. Durillo // @@ -21,18 +22,19 @@ #ifndef __EXPERIMENT_INDIVIDUAL__ #define __EXPERIMENT_INDIVIDUAL__ -class ExperimentIndividual { +class ExperimentIndividual +{ private: - int algorithmIndex_; - int problemIndex_; - int numRun_; + int algorithmIndex_; + int problemIndex_; + int numRun_; public: - ExperimentIndividual(int algorithmIndex, int problemIndex, int numRun); - int getAlgorithmIndex(); - int getProblemIndex(); - int getNumRun(); + ExperimentIndividual(int algorithmIndex, int problemIndex, int numRun); + int getAlgorithmIndex(); + int getProblemIndex(); + int getNumRun(); }; // ExperimentIndividual diff --git a/src/experiments/ExperimentReport.cpp b/src/experiments/ExperimentReport.cpp index 2e98688..89a14d7 100644 --- a/src/experiments/ExperimentReport.cpp +++ b/src/experiments/ExperimentReport.cpp @@ -2,6 +2,7 @@ // // Author: // Esteban López-Camacho +// Sérgio Vieira // // Copyright (c) 2011 Antonio J. Nebro, Juan J. Durillo // @@ -27,357 +28,395 @@ * * Contains default settings */ -ExperimentReport::ExperimentReport() { +ExperimentReport::ExperimentReport() +{ - experimentName_ = "noName"; + experimentName_ = "noName"; - experimentBaseDirectory_ = ""; - paretoFrontDirectory_ = ""; - latexDirectory_ = "latex"; + experimentBaseDirectory_ = ""; + paretoFrontDirectory_ = ""; + latexDirectory_ = "latex"; - independentRuns_ = 0; + independentRuns_ = 0; - indicatorMinimize_["HV"] = false; - indicatorMinimize_["EPSILON"] = true; - indicatorMinimize_["SPREAD"] = true; - indicatorMinimize_["GD"] = true; - indicatorMinimize_["IGD"] = true; - indicatorMinimize_["FIT"] = true; + indicatorMinimize_["HV"] = false; + indicatorMinimize_["EPSILON"] = true; + indicatorMinimize_["SPREAD"] = true; + indicatorMinimize_["GD"] = true; + indicatorMinimize_["IGD"] = true; + indicatorMinimize_["FIT"] = true; - isSingleObjective_ = false; + isSingleObjective_ = false; } // ExperimentReport -void ExperimentReport::generateQualityIndicators() { +void ExperimentReport::generateQualityIndicators() +{ - if ((!isSingleObjective_) && (paretoFrontDirectory_.empty())) { - generateReferenceFronts(); - } - - // TODO: Check if it is possible to use QualityIndicator class instead each independent class. - // Problem: knowing number of objectives of each problem - - if (indicatorList_.size() > 0) { - - cout << "PF file: " << paretoFrontDirectory_ << endl; - - for (int algorithmIndex=0; algorithmIndex > solutionFront = - indicators->utils_->readFront(solutionFrontFile); - qualityIndicatorFile = qualityIndicatorFile + "/FIT"; - indicators->fitness(solutionFront, qualityIndicatorFile); - delete indicators; - - } else { - - for (int numRun=0; numRun > solutionFront = - indicators->utils_->readFront(solutionFrontFile); - vector< vector > trueFront = - indicators->utils_->readFront(paretoFrontPath); - value = indicators->hypervolume(solutionFront, trueFront, trueFront[0].size()); - delete indicators; - qualityIndicatorFile = qualityIndicatorFile + "/HV"; - } - if (indicatorList_[indicatorIndex].compare("SPREAD")==0) { - Spread * indicators = new Spread(); - vector< vector > solutionFront = - indicators->utils_->readFront(solutionFrontFile); - vector< vector > trueFront = - indicators->utils_->readFront(paretoFrontPath); - value = indicators->spread(solutionFront, trueFront, trueFront[0].size()); - delete indicators; - qualityIndicatorFile = qualityIndicatorFile + "/SPREAD"; - } - if (indicatorList_[indicatorIndex].compare("IGD")==0) { - InvertedGenerationalDistance * indicators = new InvertedGenerationalDistance(); - vector< vector > solutionFront = - indicators->utils_->readFront(solutionFrontFile); - vector< vector > trueFront = - indicators->utils_->readFront(paretoFrontPath); - value = indicators->invertedGenerationalDistance(solutionFront, trueFront, trueFront[0].size()); - delete indicators; - qualityIndicatorFile = qualityIndicatorFile + "/IGD"; - } - if (indicatorList_[indicatorIndex].compare("EPSILON")==0) { - Epsilon * indicators = new Epsilon(); - vector< vector > solutionFront = - indicators->utils_->readFront(solutionFrontFile); - vector< vector > trueFront = - indicators->utils_->readFront(paretoFrontPath); - value = indicators->epsilon(solutionFront, trueFront, trueFront[0].size()); - delete indicators; - qualityIndicatorFile = qualityIndicatorFile + "/EPSILON"; - } - - cout << "ExperimentReport: Quality indicator file: " << qualityIndicatorFile << endl; - - if (qualityIndicatorFile.compare(problemDirectory)!=0) { - std::fstream out(qualityIndicatorFile.c_str(), - std::ios::out | std::ios::app); - out << value << endl; - out.close(); - } // if + if ((!isSingleObjective_) && (paretoFrontDirectory_.empty())) + { + generateReferenceFronts(); + } + // TODO: Check if it is possible to use QualityIndicator class instead each independent class. + // Problem: knowing number of objectives of each problem + + if (indicatorList_.size() > 0) + { + + std::cout << "PF file: " << paretoFrontDirectory_ << std::endl; + + for (int algorithmIndex=0; algorithmIndexutils_->readFront(solutionFrontFile); + qualityIndicatorFile = qualityIndicatorFile + "/FIT"; + indicators->fitness(solutionFront, qualityIndicatorFile); + delete indicators; + + } + else + { + + for (int numRun=0; numRunutils_->readFront(solutionFrontFile); + MatrixOfDouble trueFront = + indicators->utils_->readFront(paretoFrontPath); + value = indicators->hypervolume(solutionFront, trueFront, trueFront[0].size()); + delete indicators; + qualityIndicatorFile = qualityIndicatorFile + "/HV"; + } + if (indicatorList_[indicatorIndex].compare("SPREAD")==0) + { + Spread * indicators = snew Spread(); + MatrixOfDouble solutionFront = + indicators->utils_->readFront(solutionFrontFile); + MatrixOfDouble trueFront = + indicators->utils_->readFront(paretoFrontPath); + value = indicators->spread(solutionFront, trueFront, trueFront[0].size()); + delete indicators; + qualityIndicatorFile = qualityIndicatorFile + "/SPREAD"; + } + if (indicatorList_[indicatorIndex].compare("IGD")==0) + { + InvertedGenerationalDistance * indicators = snew InvertedGenerationalDistance(); + MatrixOfDouble solutionFront = + indicators->utils_->readFront(solutionFrontFile); + MatrixOfDouble trueFront = + indicators->utils_->readFront(paretoFrontPath); + value = indicators->invertedGenerationalDistance(solutionFront, trueFront, trueFront[0].size()); + delete indicators; + qualityIndicatorFile = qualityIndicatorFile + "/IGD"; + } + if (indicatorList_[indicatorIndex].compare("EPSILON")==0) + { + Epsilon * indicators = snew Epsilon(); + MatrixOfDouble solutionFront = + indicators->utils_->readFront(solutionFrontFile); + MatrixOfDouble trueFront = + indicators->utils_->readFront(paretoFrontPath); + value = indicators->epsilon(solutionFront, trueFront, trueFront[0].size()); + delete indicators; + qualityIndicatorFile = qualityIndicatorFile + "/EPSILON"; + } + + std::cout << "ExperimentReport: Quality indicator file: " << qualityIndicatorFile << std::endl; + + if (qualityIndicatorFile.compare(problemDirectory)!=0) + { + std::fstream out(qualityIndicatorFile.c_str(), + std::ios::out | std::ios::app); + out << value << std::endl; + out.close(); + } // if + + } // for + + } // if + } // for } // for - - } // if } // for - } // for - } // for - } // if + } // if } // generateQualityIndicators -void ExperimentReport::generateReferenceFronts() { +void ExperimentReport::generateReferenceFronts() +{ - string referenceFrontDirectory = experimentBaseDirectory_ + "/referenceFronts"; + std::string referenceFrontDirectory = experimentBaseDirectory_ + "/referenceFronts"; - if (FileUtils::existsPath(referenceFrontDirectory.c_str()) != 1) { - FileUtils::createDirectory(referenceFrontDirectory); - cout << "Creating " << referenceFrontDirectory << endl; - } + if (FileUtils::existsPath(referenceFrontDirectory.c_str()) != 1) + { + FileUtils::createDirectory(referenceFrontDirectory); + std::cout << "Creating " << referenceFrontDirectory << std::endl; + } - for (int problemIndex=0; problemIndexreadNonDominatedSolutionSet(solutionFrontFile, solutionSet); + metricsUtils->readNonDominatedSolutionSet(solutionFrontFile, solutionSet); - } // for - } // for + } // for + } // for - solutionSet->printObjectivesToFile(paretoFrontPath); + solutionSet->printObjectivesToFile(paretoFrontPath); - delete solutionSet; - delete metricsUtils; + delete solutionSet; + delete metricsUtils; - } // for + } // for } // generateQualityIndicators -void ExperimentReport::generateLatexTables() { - latexDirectory_ = experimentBaseDirectory_ + "/" + latexDirectory_; - cout << "latex directory: " << latexDirectory_ << endl; - - vector *** data = new vector**[indicatorList_.size()]; - for (int indicator = 0; indicator < indicatorList_.size(); indicator++) { - // A data vector per problem - data[indicator] = new vector*[problemList_.size()]; - - for (int problem = 0; problem < problemList_.size(); problem++) { - data[indicator][problem] = new vector[algorithmNameList_.size()]; - - for (int algorithm = 0; algorithm < algorithmNameList_.size(); algorithm++) { - - string directory = experimentBaseDirectory_; - directory += "/data/"; - directory += "/" + algorithmNameList_[algorithm]; - directory += "/" + problemList_[problem]; - directory += "/" + indicatorList_[indicator]; - - // Read values from data files - std::ifstream in(directory.c_str()); - if( !in ) { - cout << "Error trying to read quality indicator file: " << directory << endl; - exit(-1); - } // if - string aux; - while( getline(in, aux ) ) { - data[indicator][problem][algorithm].push_back(atof(aux.c_str())); - } // while - } // for +void ExperimentReport::generateLatexTables() +{ + latexDirectory_ = experimentBaseDirectory_ + "/" + latexDirectory_; + std::cout << "latex directory: " << latexDirectory_ << std::endl; + + VectorOfDouble *** data = snew VectorOfDouble**[indicatorList_.size()]; + for (int indicator = 0; indicator < indicatorList_.size(); indicator++) + { + // A data vector per problem + data[indicator] = snew VectorOfDouble*[problemList_.size()]; + + for (int problem = 0; problem < problemList_.size(); problem++) + { + data[indicator][problem] = snew VectorOfDouble[algorithmNameList_.size()]; + + for (int algorithm = 0; algorithm < algorithmNameList_.size(); algorithm++) + { + + std::string directory = experimentBaseDirectory_; + directory += "/data/"; + directory += "/" + algorithmNameList_[algorithm]; + directory += "/" + problemList_[problem]; + directory += "/" + indicatorList_[indicator]; + + // Read values from data files + std::ifstream in(directory.c_str()); + if( !in ) + { + std::cout << "Error trying to read quality indicator file: " << directory << std::endl; + exit(-1); + } // if + std::string aux; + while( getline(in, aux ) ) + { + data[indicator][problem][algorithm].push_back(atof(aux.c_str())); + } // while + } // for + } // for } // for - } // for - - double *** mean; - double *** median; - double *** stdDeviation; - double *** iqr; - double *** max; - double *** min; - int *** numberOfValues; - - map statValues; - - statValues["mean"] = 0.0; - statValues["median"] = 0.0; - statValues["stdDeviation"] = 0.0; - statValues["iqr"] = 0.0; - statValues["max"] = 0.0; - statValues["min"] = 0.0; - - mean = new double**[indicatorList_.size()]; - median = new double**[indicatorList_.size()]; - stdDeviation = new double**[indicatorList_.size()]; - iqr = new double**[indicatorList_.size()]; - min = new double**[indicatorList_.size()]; - max = new double**[indicatorList_.size()]; - numberOfValues = new int**[indicatorList_.size()]; - - for (int indicator = 0; indicator < indicatorList_.size(); indicator++) { - // A data vector per problem - mean[indicator] = new double*[problemList_.size()]; - median[indicator] = new double*[problemList_.size()]; - stdDeviation[indicator] = new double*[problemList_.size()]; - iqr[indicator] = new double*[problemList_.size()]; - min[indicator] = new double*[problemList_.size()]; - max[indicator] = new double*[problemList_.size()]; - numberOfValues[indicator] = new int*[problemList_.size()]; - - for (int problem = 0; problem < problemList_.size(); problem++) { - mean[indicator][problem] = new double[algorithmNameList_.size()]; - median[indicator][problem] = new double[algorithmNameList_.size()]; - stdDeviation[indicator][problem] = new double[algorithmNameList_.size()]; - iqr[indicator][problem] = new double[algorithmNameList_.size()]; - min[indicator][problem] = new double[algorithmNameList_.size()]; - max[indicator][problem] = new double[algorithmNameList_.size()]; - numberOfValues[indicator][problem] = new int[algorithmNameList_.size()]; - - for (int algorithm = 0; algorithm < algorithmNameList_.size(); algorithm++) { - sort(data[indicator][problem][algorithm].begin(), - data[indicator][problem][algorithm].end()); - - string directory = experimentBaseDirectory_; - directory += "/" + algorithmNameList_[algorithm]; - directory += "/" + problemList_[problem]; - directory += "/" + indicatorList_[indicator]; - - //cout << "----" << directory << "-----" << endl; - //calculateStatistics(data[indicator][problem][algorithm], meanV, medianV, minV, maxV, stdDeviationV, iqrV); - calculateStatistics(data[indicator][problem][algorithm], &statValues); - - /* - cout << "Mean: " << statValues["mean"] << endl; - cout << "Median : " << statValues["median"] << endl; - cout << "Std : " << statValues["stdDeviation"] << endl; - cout << "IQR : " << statValues["iqr"] << endl; - cout << "Min : " << statValues["min"] << endl; - cout << "Max : " << statValues["max"] << endl; - cout << "N_values: " << data[indicator][problem][algorithm].size() << endl; - */ - - mean[indicator][problem][algorithm] = statValues["mean"]; - median[indicator][problem][algorithm] = statValues["median"]; - stdDeviation[indicator][problem][algorithm] = statValues["stdDeviation"]; - iqr[indicator][problem][algorithm] = statValues["iqr"]; - min[indicator][problem][algorithm] = statValues["min"]; - max[indicator][problem][algorithm] = statValues["max"]; - numberOfValues[indicator][problem][algorithm] = data[indicator][problem][algorithm].size(); - } + + double *** mean; + double *** median; + double *** stdDeviation; + double *** iqr; + double *** max; + double *** min; + int *** numberOfValues; + + MapOfStringDouble statValues; + + statValues["mean"] = 0.0; + statValues["median"] = 0.0; + statValues["stdDeviation"] = 0.0; + statValues["iqr"] = 0.0; + statValues["max"] = 0.0; + statValues["min"] = 0.0; + + mean = snew double**[indicatorList_.size()]; + median = snew double**[indicatorList_.size()]; + stdDeviation = snew double**[indicatorList_.size()]; + iqr = snew double**[indicatorList_.size()]; + min = snew double**[indicatorList_.size()]; + max = snew double**[indicatorList_.size()]; + numberOfValues = snew int**[indicatorList_.size()]; + + for (int indicator = 0; indicator < indicatorList_.size(); indicator++) + { + // A data vector per problem + mean[indicator] = snew double*[problemList_.size()]; + median[indicator] = snew double*[problemList_.size()]; + stdDeviation[indicator] = snew double*[problemList_.size()]; + iqr[indicator] = snew double*[problemList_.size()]; + min[indicator] = snew double*[problemList_.size()]; + max[indicator] = snew double*[problemList_.size()]; + numberOfValues[indicator] = snew int*[problemList_.size()]; + + for (int problem = 0; problem < problemList_.size(); problem++) + { + mean[indicator][problem] = snew double[algorithmNameList_.size()]; + median[indicator][problem] = snew double[algorithmNameList_.size()]; + stdDeviation[indicator][problem] = snew double[algorithmNameList_.size()]; + iqr[indicator][problem] = snew double[algorithmNameList_.size()]; + min[indicator][problem] = snew double[algorithmNameList_.size()]; + max[indicator][problem] = snew double[algorithmNameList_.size()]; + numberOfValues[indicator][problem] = snew int[algorithmNameList_.size()]; + + for (int algorithm = 0; algorithm < algorithmNameList_.size(); algorithm++) + { + sort(data[indicator][problem][algorithm].begin(), + data[indicator][problem][algorithm].end()); + + std::string directory = experimentBaseDirectory_; + directory += "/" + algorithmNameList_[algorithm]; + directory += "/" + problemList_[problem]; + directory += "/" + indicatorList_[indicator]; + + //std::cout << "----" << directory << "-----" << std::endl; + //calculateStatistics(data[indicator][problem][algorithm], meanV, medianV, minV, maxV, stdDeviationV, iqrV); + calculateStatistics(data[indicator][problem][algorithm], &statValues); + + /* + std::cout << "Mean: " << statValues["mean"] << std::endl; + std::cout << "Median : " << statValues["median"] << std::endl; + std::cout << "Std : " << statValues["stdDeviation"] << std::endl; + std::cout << "IQR : " << statValues["iqr"] << std::endl; + std::cout << "Min : " << statValues["min"] << std::endl; + std::cout << "Max : " << statValues["max"] << std::endl; + std::cout << "N_values: " << data[indicator][problem][algorithm].size() << std::endl; + */ + + mean[indicator][problem][algorithm] = statValues["mean"]; + median[indicator][problem][algorithm] = statValues["median"]; + stdDeviation[indicator][problem][algorithm] = statValues["stdDeviation"]; + iqr[indicator][problem][algorithm] = statValues["iqr"]; + min[indicator][problem][algorithm] = statValues["min"]; + max[indicator][problem][algorithm] = statValues["max"]; + numberOfValues[indicator][problem][algorithm] = data[indicator][problem][algorithm].size(); + } + } } - } - if (FileUtils::existsPath(latexDirectory_.c_str()) != 1) { - if (FileUtils::createDirectory(latexDirectory_) == -1) { - cout << "Error creating directory: " << latexDirectory_ << endl; - exit(-1); + if (FileUtils::existsPath(latexDirectory_.c_str()) != 1) + { + if (FileUtils::createDirectory(latexDirectory_) == -1) + { + std::cout << "Error creating directory: " << latexDirectory_ << std::endl; + exit(-1); + } // if + std::cout << "Creating " << latexDirectory_ << " directory" << std::endl; } // if - cout << "Creating " << latexDirectory_ << " directory" << endl; - } // if - cout << "Experiment name: " << experimentName_ << endl; - string latexFile = latexDirectory_ + "/" + experimentName_ + ".tex"; - printHeaderLatexCommands(latexFile); - for (int i = 0; i < indicatorList_.size(); i++) { - printMeanStdDev(latexFile, i, mean, stdDeviation); - printMedianIQR(latexFile, i, median, iqr); - } // for - printEndLatexCommands(latexFile); - - // Free memory: - for (int indicator = 0; indicator < indicatorList_.size(); indicator++) { - for (int problem = 0; problem < problemList_.size(); problem++) { - delete [] data[indicator][problem]; - delete [] mean[indicator][problem]; - delete [] median[indicator][problem]; - delete [] stdDeviation[indicator][problem]; - delete [] iqr[indicator][problem]; - delete [] max[indicator][problem]; - delete [] min[indicator][problem]; - delete [] numberOfValues[indicator][problem]; + std::cout << "Experiment name: " << experimentName_ << std::endl; + std::string latexFile = latexDirectory_ + "/" + experimentName_ + ".tex"; + printHeaderLatexCommands(latexFile); + for (int i = 0; i < indicatorList_.size(); i++) + { + printMeanStdDev(latexFile, i, mean, stdDeviation); + printMedianIQR(latexFile, i, median, iqr); + } // for + printEndLatexCommands(latexFile); + + // Free memory: + for (int indicator = 0; indicator < indicatorList_.size(); indicator++) + { + for (int problem = 0; problem < problemList_.size(); problem++) + { + delete [] data[indicator][problem]; + delete [] mean[indicator][problem]; + delete [] median[indicator][problem]; + delete [] stdDeviation[indicator][problem]; + delete [] iqr[indicator][problem]; + delete [] max[indicator][problem]; + delete [] min[indicator][problem]; + delete [] numberOfValues[indicator][problem]; + } + delete [] data[indicator]; + delete [] mean[indicator]; + delete [] median[indicator]; + delete [] stdDeviation[indicator]; + delete [] iqr[indicator]; + delete [] max[indicator]; + delete [] min[indicator]; + delete [] numberOfValues[indicator]; } - delete [] data[indicator]; - delete [] mean[indicator]; - delete [] median[indicator]; - delete [] stdDeviation[indicator]; - delete [] iqr[indicator]; - delete [] max[indicator]; - delete [] min[indicator]; - delete [] numberOfValues[indicator]; - } - delete [] data; - delete [] mean; - delete [] median; - delete [] stdDeviation; - delete [] iqr; - delete [] max; - delete [] min; - delete [] numberOfValues; + delete [] data; + delete [] mean; + delete [] median; + delete [] stdDeviation; + delete [] iqr; + delete [] max; + delete [] min; + delete [] numberOfValues; } // generateLatexTables @@ -385,326 +424,381 @@ void ExperimentReport::generateLatexTables() { /** * Calculates statistical values from a vector of Double objects */ -void ExperimentReport::calculateStatistics(vector vector, map * values) { - if (vector.size() > 0) { - double sum, minimum, maximum, sqsum, min, max, median, mean, iqr, stdDeviation; - - sqsum = 0.0; - sum = 0.0; - min = 1E300; - max = -1E300; - median = 0; - - for (int i = 0; i < vector.size(); i++) { - double val = vector[i]; - sqsum += val * val; - sum += val; - if (val < min) { - min = val; - } - if (val > max) { - max = val; - } // if - } // for +void ExperimentReport::calculateStatistics(VectorOfDouble vector, MapOfStringDouble * values) +{ + if (vector.size() > 0) + { + double sum, minimum, maximum, sqsum, min, max, median, mean, iqr, stdDeviation; + + sqsum = 0.0; + sum = 0.0; + min = 1E300; + max = -1E300; + median = 0; + + for (int i = 0; i < vector.size(); i++) + { + double val = vector[i]; + sqsum += val * val; + sum += val; + if (val < min) + { + min = val; + } + if (val > max) + { + max = val; + } // if + } // for - // Mean - mean = sum / vector.size(); + // Mean + mean = sum / vector.size(); - // Standard deviation - if (sqsum / vector.size() - mean * mean < 0.0) { - stdDeviation = 0.0; - } else { - stdDeviation = sqrt(sqsum / vector.size() - mean * mean); - } // if + // Standard deviation + if (sqsum / vector.size() - mean * mean < 0.0) + { + stdDeviation = 0.0; + } + else + { + stdDeviation = sqrt(sqsum / vector.size() - mean * mean); + } // if - (*values)["mean"] = mean; - (*values)["median"] = Statistics::calculateMedian(vector, 0, vector.size() - 1); - (*values)["iqr"] = Statistics::calculateIQR(vector); - (*values)["stdDeviation"] = stdDeviation; - (*values)["min"] = min; - (*values)["max"] = max; - } // if - else { - (*values)["mean"] = std::numeric_limits::quiet_NaN(); - (*values)["median"] = std::numeric_limits::quiet_NaN(); - (*values)["iqr"] = std::numeric_limits::quiet_NaN(); - (*values)["stdDeviation"] = std::numeric_limits::quiet_NaN(); - (*values)["min"] = std::numeric_limits::quiet_NaN(); - (*values)["max"] = std::numeric_limits::quiet_NaN(); - } // else + (*values)["mean"] = mean; + (*values)["median"] = Statistics::calculateMedian(vector, 0, vector.size() - 1); + (*values)["iqr"] = Statistics::calculateIQR(vector); + (*values)["stdDeviation"] = stdDeviation; + (*values)["min"] = min; + (*values)["max"] = max; + } // if + else + { + (*values)["mean"] = std::numeric_limits::quiet_NaN(); + (*values)["median"] = std::numeric_limits::quiet_NaN(); + (*values)["iqr"] = std::numeric_limits::quiet_NaN(); + (*values)["stdDeviation"] = std::numeric_limits::quiet_NaN(); + (*values)["min"] = std::numeric_limits::quiet_NaN(); + (*values)["max"] = std::numeric_limits::quiet_NaN(); + } // else } // calculateStatistics -void ExperimentReport::printHeaderLatexCommands(string fileName) { - std::ofstream out(fileName.c_str()); - out << "\\documentclass{article}" << endl; - out << "\\title{" << experimentName_ << "}" << endl; - out << "\\usepackage{colortbl}" << endl; - out << "\\usepackage[table*]{xcolor}" << endl; - out << "\\xdefinecolor{gray95}{gray}{0.65}" << endl; - out << "\\xdefinecolor{gray25}{gray}{0.8}" << endl; - out << "\\author{}" << endl; - out << "\\begin{document}" << endl; - out << "\\maketitle" << endl; - out << "\\section{Tables}" << endl; - out.close(); +void ExperimentReport::printHeaderLatexCommands(std::string fileName) +{ + std::ofstream out(fileName.c_str()); + out << "\\documentclass{article}" << std::endl; + out << "\\title{" << experimentName_ << "}" << std::endl; + out << "\\usepackage{colortbl}" << std::endl; + out << "\\usepackage[table*]{xcolor}" << std::endl; + out << "\\xdefinecolor{gray95}{gray}{0.65}" << std::endl; + out << "\\xdefinecolor{gray25}{gray}{0.8}" << std::endl; + out << "\\author{}" << std::endl; + out << "\\begin{document}" << std::endl; + out << "\\maketitle" << std::endl; + out << "\\section{Tables}" << std::endl; + out.close(); } // printHeaderLatexCommands -void ExperimentReport::printEndLatexCommands(string fileName) { - std::fstream out(fileName.c_str(), std::ios::out | std::ios::app); - out << "\\end{document}" << endl; - out.close(); +void ExperimentReport::printEndLatexCommands(std::string fileName) +{ + std::fstream out(fileName.c_str(), std::ios::out | std::ios::app); + out << "\\end{document}" << std::endl; + out.close(); } //printEndLatexCommands -void ExperimentReport::printMeanStdDev(string fileName, int indicator, double *** mean, - double *** stdDev) { - std::fstream out(fileName.c_str(), std::ios::out | std::ios::app); - out << "\\" << endl; - out << "\\begin{table}" << endl; - out << "\\caption{" << indicatorList_[indicator] << ". Mean and standard deviation}" << endl; - out << "\\label{table:mean." << indicatorList_[indicator] << "}" << endl; - out << "\\centering" << endl; - out << "\\begin{scriptsize}" << endl; - out << "\\begin{tabular}{l"; - - // calculate the number of columns - for (int i = 0; i < algorithmNameList_.size(); i++) { - out << "l"; - } - out << "}" << endl; - - out << "\\hline"; - // write table head - for (int i = -1; i < (int) (algorithmNameList_.size()); i++) { - if (i == -1) { - out << " & "; - } else if (i == (algorithmNameList_.size() - 1)) { - out << " " << algorithmNameList_[i] << "\\\\" << endl; - } else { - out << "" << algorithmNameList_[i] << " & "; +void ExperimentReport::printMeanStdDev(std::string fileName, int indicator, double *** mean, + double *** stdDev) +{ + std::fstream out(fileName.c_str(), std::ios::out | std::ios::app); + out << "\\" << std::endl; + out << "\\begin{table}" << std::endl; + out << "\\caption{" << indicatorList_[indicator] << ". Mean and standard deviation}" << std::endl; + out << "\\label{table:mean." << indicatorList_[indicator] << "}" << std::endl; + out << "\\centering" << std::endl; + out << "\\begin{scriptsize}" << std::endl; + out << "\\begin{tabular}{l"; + + // calculate the number of columns + for (int i = 0; i < algorithmNameList_.size(); i++) + { + out << "l"; } - } - out << "\\hline" << endl; - - char m[20], s[20]; - // write lines - for (int i = 0; i < problemList_.size(); i++) { - // find the best value and second best value - double bestValue ; - double bestValueIQR ; - double secondBestValue ; - double secondBestValueIQR ; - int bestIndex = -1 ; - int secondBestIndex = -1 ; - if (indicatorMinimize_[indicatorList_[indicator]] == true) {// minimize by default - bestValue = std::numeric_limits::max(); - bestValueIQR = std::numeric_limits::max(); - secondBestValue = std::numeric_limits::max(); - secondBestValueIQR = std::numeric_limits::max(); - for (int j = 0; j < (algorithmNameList_.size()); j++) { - if ((mean[indicator][i][j] < bestValue) || - ((mean[indicator][i][j] == bestValue) && (stdDev[indicator][i][j] < bestValueIQR))) { - secondBestIndex = bestIndex ; - secondBestValue = bestValue ; - secondBestValueIQR = bestValueIQR ; - bestValue = mean[indicator][i][j]; - bestValueIQR = stdDev[indicator][i][j]; - bestIndex = j; + out << "}" << std::endl; + + out << "\\hline"; + // write table head + for (int i = -1; i < (int) (algorithmNameList_.size()); i++) + { + if (i == -1) + { + out << " & "; } - else if ((mean[indicator][i][j] < secondBestValue) || - ((mean[indicator][i][j] == secondBestValue) && (stdDev[indicator][i][j] < secondBestValueIQR))) { - secondBestIndex = j ; - secondBestValue = mean[indicator][i][j] ; - secondBestValueIQR = stdDev[indicator][i][j] ; - } // else if - } - } // if - else { // indicator to maximize e.g., the HV - bestValue = -std::numeric_limits::max(); - bestValueIQR = -std::numeric_limits::max(); - secondBestValue = -std::numeric_limits::max(); - secondBestValueIQR = -std::numeric_limits::max(); - for (int j = 0; j < (algorithmNameList_.size()); j++) { - if ((mean[indicator][i][j] > bestValue) || - ((mean[indicator][i][j] == bestValue) && (stdDev[indicator][i][j] < bestValueIQR))) { - secondBestIndex = bestIndex ; - secondBestValue = bestValue ; - secondBestValueIQR = bestValueIQR ; - bestValue = mean[indicator][i][j]; - bestValueIQR = stdDev[indicator][i][j]; - bestIndex = j; + else if (i == (algorithmNameList_.size() - 1)) + { + out << " " << algorithmNameList_[i] << "\\\\" << std::endl; + } + else + { + out << "" << algorithmNameList_[i] << " & "; } - else if ((mean[indicator][i][j] > secondBestValue) || - ((mean[indicator][i][j] == secondBestValue) && (stdDev[indicator][i][j] < secondBestValueIQR))) { - secondBestIndex = j ; - secondBestValue = mean[indicator][i][j] ; - secondBestValueIQR = stdDev[indicator][i][j] ; - } // else if - } // for - } // else - - out << problemList_[i] << " & "; - for (int j = 0; j < (algorithmNameList_.size() - 1); j++) { - if (j == bestIndex) { - out << "\\cellcolor{gray95}"; - } - if (j == secondBestIndex) { - out << "\\cellcolor{gray25}"; - } - - sprintf(m, "%10.2e", mean[indicator][i][j]); - sprintf(s, "%8.1e", stdDev[indicator][i][j]); - out << "$" << m << "_{" << s << "}$ & "; - } - if (bestIndex == (algorithmNameList_.size() - 1)) { - out << "\\cellcolor{gray95}"; } - sprintf(m, "%10.2e", mean[indicator][i][algorithmNameList_.size() - 1]); - sprintf(s, "%8.1e", stdDev[indicator][i][algorithmNameList_.size() - 1]); - out << "$" << m << "_{" << s << "}$ \\\\" << endl; - } // for - //out << "" + mean[0][problemList_.length-1][algorithmNameList_.length-1] + "\\\\"+ "\n" ) ; - - out << "\\hline" << endl; - out << "\\end{tabular}" << endl; - out << "\\end{scriptsize}" << endl; - out << "\\end{table}" << endl; - out.close(); + out << "\\hline" << std::endl; + + char m[20], s[20]; + // write lines + for (int i = 0; i < problemList_.size(); i++) + { + // find the best value and second best value + double bestValue ; + double bestValueIQR ; + double secondBestValue ; + double secondBestValueIQR ; + int bestIndex = -1 ; + int secondBestIndex = -1 ; + if (indicatorMinimize_[indicatorList_[indicator]] == true) // minimize by default + { + bestValue = std::numeric_limits::max(); + bestValueIQR = std::numeric_limits::max(); + secondBestValue = std::numeric_limits::max(); + secondBestValueIQR = std::numeric_limits::max(); + for (int j = 0; j < (algorithmNameList_.size()); j++) + { + if ((mean[indicator][i][j] < bestValue) || + ((mean[indicator][i][j] == bestValue) && (stdDev[indicator][i][j] < bestValueIQR))) + { + secondBestIndex = bestIndex ; + secondBestValue = bestValue ; + secondBestValueIQR = bestValueIQR ; + bestValue = mean[indicator][i][j]; + bestValueIQR = stdDev[indicator][i][j]; + bestIndex = j; + } + else if ((mean[indicator][i][j] < secondBestValue) || + ((mean[indicator][i][j] == secondBestValue) && (stdDev[indicator][i][j] < secondBestValueIQR))) + { + secondBestIndex = j ; + secondBestValue = mean[indicator][i][j] ; + secondBestValueIQR = stdDev[indicator][i][j] ; + } // else if + } + } // if + else // indicator to maximize e.g., the HV + { + bestValue = -std::numeric_limits::max(); + bestValueIQR = -std::numeric_limits::max(); + secondBestValue = -std::numeric_limits::max(); + secondBestValueIQR = -std::numeric_limits::max(); + for (int j = 0; j < (algorithmNameList_.size()); j++) + { + if ((mean[indicator][i][j] > bestValue) || + ((mean[indicator][i][j] == bestValue) && (stdDev[indicator][i][j] < bestValueIQR))) + { + secondBestIndex = bestIndex ; + secondBestValue = bestValue ; + secondBestValueIQR = bestValueIQR ; + bestValue = mean[indicator][i][j]; + bestValueIQR = stdDev[indicator][i][j]; + bestIndex = j; + } + else if ((mean[indicator][i][j] > secondBestValue) || + ((mean[indicator][i][j] == secondBestValue) && (stdDev[indicator][i][j] < secondBestValueIQR))) + { + secondBestIndex = j ; + secondBestValue = mean[indicator][i][j] ; + secondBestValueIQR = stdDev[indicator][i][j] ; + } // else if + } // for + } // else + + out << problemList_[i] << " & "; + for (int j = 0; j < (algorithmNameList_.size() - 1); j++) + { + if (j == bestIndex) + { + out << "\\cellcolor{gray95}"; + } + if (j == secondBestIndex) + { + out << "\\cellcolor{gray25}"; + } + + sprintf(m, "%10.2e", mean[indicator][i][j]); + sprintf(s, "%8.1e", stdDev[indicator][i][j]); + out << "$" << m << "_{" << s << "}$ & "; + } + if (bestIndex == (algorithmNameList_.size() - 1)) + { + out << "\\cellcolor{gray95}"; + } + sprintf(m, "%10.2e", mean[indicator][i][algorithmNameList_.size() - 1]); + sprintf(s, "%8.1e", stdDev[indicator][i][algorithmNameList_.size() - 1]); + out << "$" << m << "_{" << s << "}$ \\\\" << std::endl; + } // for + //out << "" + mean[0][problemList_.length-1][algorithmNameList_.length-1] + "\\\\"+ "\n" ) ; + + out << "\\hline" << std::endl; + out << "\\end{tabular}" << std::endl; + out << "\\end{scriptsize}" << std::endl; + out << "\\end{table}" << std::endl; + out.close(); } // printMeanStdDev -void ExperimentReport::printMedianIQR(string fileName, int indicator, double *** median, - double *** IQR) { - std::fstream out(fileName.c_str(), std::ios::out | std::ios::app); - out << "\\" << endl; - out << "\\begin{table}" << endl; - out << "\\caption{" << indicatorList_[indicator] << ". Median and IQR}" << endl; - out << "\\label{table:median." << indicatorList_[indicator] << "}" << endl; - out << "\\begin{scriptsize}" << endl; - out << "\\centering" << endl; - out << "\\begin{tabular}{l"; - - // calculate the number of columns - for (int i = 0; i < algorithmNameList_.size(); i++) { - out << "l"; - } - out << "}" << endl; - - out << "\\hline"; - // write table head - for (int i = -1; i < (int) (algorithmNameList_.size()); i++) { - if (i == -1) { - out << " & "; - } else if (i == (algorithmNameList_.size() - 1)) { - out << " " << algorithmNameList_[i] << "\\\\" << endl; - } else { - out << "" << algorithmNameList_[i] << " & "; +void ExperimentReport::printMedianIQR(std::string fileName, int indicator, double *** median, + double *** IQR) +{ + std::fstream out(fileName.c_str(), std::ios::out | std::ios::app); + out << "\\" << std::endl; + out << "\\begin{table}" << std::endl; + out << "\\caption{" << indicatorList_[indicator] << ". Median and IQR}" << std::endl; + out << "\\label{table:median." << indicatorList_[indicator] << "}" << std::endl; + out << "\\begin{scriptsize}" << std::endl; + out << "\\centering" << std::endl; + out << "\\begin{tabular}{l"; + + // calculate the number of columns + for (int i = 0; i < algorithmNameList_.size(); i++) + { + out << "l"; } - } - out << "\\hline" << endl; - - char m[20], s[20]; - // write lines - for (int i = 0; i < problemList_.size(); i++) { - // find the best value and second best value - double bestValue ; - double bestValueIQR ; - double secondBestValue ; - double secondBestValueIQR ; - int bestIndex = -1 ; - int secondBestIndex = -1 ; - if (indicatorMinimize_[indicatorList_[indicator]] == true) {// minimize by default - bestValue = std::numeric_limits::max(); - bestValueIQR = std::numeric_limits::max(); - secondBestValue = std::numeric_limits::max(); - secondBestValueIQR = std::numeric_limits::max(); - for (int j = 0; j < (algorithmNameList_.size()); j++) { - if ((median[indicator][i][j] < bestValue) || - ((median[indicator][i][j] == bestValue) && (IQR[indicator][i][j] < bestValueIQR))) { - secondBestIndex = bestIndex ; - secondBestValue = bestValue ; - secondBestValueIQR = bestValueIQR ; - bestValue = median[indicator][i][j]; - bestValueIQR = IQR[indicator][i][j]; - bestIndex = j; + out << "}" << std::endl; + + out << "\\hline"; + // write table head + for (int i = -1; i < (int) (algorithmNameList_.size()); i++) + { + if (i == -1) + { + out << " & "; } - else if ((median[indicator][i][j] < secondBestValue) || - ((median[indicator][i][j] == secondBestValue) && (IQR[indicator][i][j] < secondBestValueIQR))) { - secondBestIndex = j ; - secondBestValue = median[indicator][i][j] ; - secondBestValueIQR = IQR[indicator][i][j] ; - } // else if - } // for - } // if - else { // indicator to maximize e.g., the HV - bestValue = -std::numeric_limits::max(); - bestValueIQR = -std::numeric_limits::max(); - secondBestValue = -std::numeric_limits::max(); - secondBestValueIQR = -std::numeric_limits::max(); - for (int j = 0; j < (algorithmNameList_.size()); j++) { - if ((median[indicator][i][j] > bestValue) || - ((median[indicator][i][j] == bestValue) && (IQR[indicator][i][j] < bestValueIQR))) { - secondBestIndex = bestIndex ; - secondBestValue = bestValue ; - secondBestValueIQR = bestValueIQR ; - bestValue = median[indicator][i][j]; - bestValueIQR = IQR[indicator][i][j]; - bestIndex = j; + else if (i == (algorithmNameList_.size() - 1)) + { + out << " " << algorithmNameList_[i] << "\\\\" << std::endl; + } + else + { + out << "" << algorithmNameList_[i] << " & "; } - else if ((median[indicator][i][j] > secondBestValue) || - ((median[indicator][i][j] == secondBestValue) && (IQR[indicator][i][j] < secondBestValueIQR))) { - secondBestIndex = j ; - secondBestValue = median[indicator][i][j] ; - secondBestValueIQR = IQR[indicator][i][j] ; - } // else if - } // for - } // else - - - out << problemList_[i] + " & "; - for (int j = 0; j < (algorithmNameList_.size() - 1); j++) { - if (j == bestIndex) { - out << "\\cellcolor{gray95}"; - } - if (j == secondBestIndex) { - out << "\\cellcolor{gray25}"; - } - sprintf(m, "%10.2e", median[indicator][i][j]); - sprintf(s, "%8.1e", IQR[indicator][i][j]); - out << "$" << m << "_{" << s << "}$ & "; - } - if (bestIndex == (algorithmNameList_.size() - 1)) { - out << "\\cellcolor{gray95}"; } - sprintf(m, "%10.2e", median[indicator][i][algorithmNameList_.size() - 1]); - sprintf(s, "%8.1e", IQR[indicator][i][algorithmNameList_.size() - 1]); - out << "$" << m << "_{" << s << "}$ \\\\" << endl; - } // for - //out << "" << mean[0][problemList_.size()-1][algorithmNameList_.size()-1] << "\\\\" << endl; - - out << "\\hline" << endl; - out << "\\end{tabular}" << endl; - out << "\\end{scriptsize}" << endl; - out << "\\end{table}" << endl; - out.close(); + out << "\\hline" << std::endl; + + char m[20], s[20]; + // write lines + for (int i = 0; i < problemList_.size(); i++) + { + // find the best value and second best value + double bestValue ; + double bestValueIQR ; + double secondBestValue ; + double secondBestValueIQR ; + int bestIndex = -1 ; + int secondBestIndex = -1 ; + if (indicatorMinimize_[indicatorList_[indicator]] == true) // minimize by default + { + bestValue = std::numeric_limits::max(); + bestValueIQR = std::numeric_limits::max(); + secondBestValue = std::numeric_limits::max(); + secondBestValueIQR = std::numeric_limits::max(); + for (int j = 0; j < (algorithmNameList_.size()); j++) + { + if ((median[indicator][i][j] < bestValue) || + ((median[indicator][i][j] == bestValue) && (IQR[indicator][i][j] < bestValueIQR))) + { + secondBestIndex = bestIndex ; + secondBestValue = bestValue ; + secondBestValueIQR = bestValueIQR ; + bestValue = median[indicator][i][j]; + bestValueIQR = IQR[indicator][i][j]; + bestIndex = j; + } + else if ((median[indicator][i][j] < secondBestValue) || + ((median[indicator][i][j] == secondBestValue) && (IQR[indicator][i][j] < secondBestValueIQR))) + { + secondBestIndex = j ; + secondBestValue = median[indicator][i][j] ; + secondBestValueIQR = IQR[indicator][i][j] ; + } // else if + } // for + } // if + else // indicator to maximize e.g., the HV + { + bestValue = -std::numeric_limits::max(); + bestValueIQR = -std::numeric_limits::max(); + secondBestValue = -std::numeric_limits::max(); + secondBestValueIQR = -std::numeric_limits::max(); + for (int j = 0; j < (algorithmNameList_.size()); j++) + { + if ((median[indicator][i][j] > bestValue) || + ((median[indicator][i][j] == bestValue) && (IQR[indicator][i][j] < bestValueIQR))) + { + secondBestIndex = bestIndex ; + secondBestValue = bestValue ; + secondBestValueIQR = bestValueIQR ; + bestValue = median[indicator][i][j]; + bestValueIQR = IQR[indicator][i][j]; + bestIndex = j; + } + else if ((median[indicator][i][j] > secondBestValue) || + ((median[indicator][i][j] == secondBestValue) && (IQR[indicator][i][j] < secondBestValueIQR))) + { + secondBestIndex = j ; + secondBestValue = median[indicator][i][j] ; + secondBestValueIQR = IQR[indicator][i][j] ; + } // else if + } // for + } // else + + + out << problemList_[i] + " & "; + for (int j = 0; j < (algorithmNameList_.size() - 1); j++) + { + if (j == bestIndex) + { + out << "\\cellcolor{gray95}"; + } + if (j == secondBestIndex) + { + out << "\\cellcolor{gray25}"; + } + sprintf(m, "%10.2e", median[indicator][i][j]); + sprintf(s, "%8.1e", IQR[indicator][i][j]); + out << "$" << m << "_{" << s << "}$ & "; + } + if (bestIndex == (algorithmNameList_.size() - 1)) + { + out << "\\cellcolor{gray95}"; + } + sprintf(m, "%10.2e", median[indicator][i][algorithmNameList_.size() - 1]); + sprintf(s, "%8.1e", IQR[indicator][i][algorithmNameList_.size() - 1]); + out << "$" << m << "_{" << s << "}$ \\\\" << std::endl; + } // for + //out << "" << mean[0][problemList_.size()-1][algorithmNameList_.size()-1] << "\\\\" << std::endl; + + out << "\\hline" << std::endl; + out << "\\end{tabular}" << std::endl; + out << "\\end{scriptsize}" << std::endl; + out << "\\end{table}" << std::endl; + out.close(); } // printMedianIQR /** * Invoking the generateScripts method on the RBoxplot class */ -void ExperimentReport::generateRBoxplotScripts (int rows, int cols, vector problems, - string prefix, bool notch, ExperimentReport * experiment) { - RBoxplot::generateScripts(rows, cols, problems, prefix, notch, this); +void ExperimentReport::generateRBoxplotScripts (int rows, int cols, VectorOfString problems, + std::string prefix, bool notch, ExperimentReport * experiment) +{ + RBoxplot::generateScripts(rows, cols, problems, prefix, notch, this); } // generateRBoxplotScripts /** * Invoking the generateScripts method on the RWilcoxon class */ -void ExperimentReport::generateRWilcoxonScripts(vector problems, string prefix, - ExperimentReport * experiment) { - RWilcoxon::generateScripts(problems, prefix, this); +void ExperimentReport::generateRWilcoxonScripts(VectorOfString problems, std::string prefix, + ExperimentReport * experiment) +{ + RWilcoxon::generateScripts(problems, prefix, this); } //generateRWilcoxonScripts diff --git a/src/experiments/ExperimentReport.h b/src/experiments/ExperimentReport.h index f58bf0d..576963b 100644 --- a/src/experiments/ExperimentReport.h +++ b/src/experiments/ExperimentReport.h @@ -2,6 +2,7 @@ // // Author: // Esteban López-Camacho +// Sérgio Vieira // // Copyright (c) 2011 Antonio J. Nebro, Juan J. Durillo // @@ -21,9 +22,7 @@ #ifndef __EXPERIMENT_REPORT__ #define __EXPERIMENT_REPORT__ -#include -#include -#include +#include "JMetalHeader.h" #include #include #include @@ -45,45 +44,47 @@ #include #include -using namespace std; + +using namespace JMetal; /** * Abstract class generating jMetal experiments reports */ -class ExperimentReport : public Experiment { +class ExperimentReport : public Experiment +{ private: - void generateReferenceFronts(); - void calculateStatistics(vector vector_, map * values); - void printHeaderLatexCommands(string fileName); - void printEndLatexCommands(string fileName); - void printMeanStdDev(string fileName, int indicator, double*** mean, - double*** stdDev); - void printMedianIQR(string fileName, int indicator, double*** median, - double*** IQR); + void generateReferenceFronts(); + void calculateStatistics(VectorOfDouble vector_, MapOfStringDouble * values); + void printHeaderLatexCommands(std::string fileName); + void printEndLatexCommands(std::string fileName); + void printMeanStdDev(std::string fileName, int indicator, double*** mean, + double*** stdDev); + void printMedianIQR(std::string fileName, int indicator, double*** median, + double*** IQR); public: - vector paretoFrontFile_; // List of the files containing the pareto - // fronts corresponding to the problems in - // problemList_ - vector indicatorList_; // List of the quality indicators to be applied - string latexDirectory_; // Directory to store the latex files - string paretoFrontDirectory_; // Directory containing the Pareto front files - map indicatorMinimize_; // To indicate whether an indicator - // is to be minimized. Hard-coded - // in the constructor + VectorOfString paretoFrontFile_; // List of the files containing the pareto + // fronts corresponding to the problems in + // problemList_ + VectorOfString indicatorList_; // List of the quality indicators to be applied + std::string latexDirectory_; // Directory to store the latex files + std::string paretoFrontDirectory_; // Directory containing the Pareto front files + MapOfStringBool indicatorMinimize_; // To indicate whether an indicator + // is to be minimized. Hard-coded + // in the constructor - ExperimentReport(); + ExperimentReport(); - void generateQualityIndicators(); - void generateLatexTables(); - void generateRBoxplotScripts(int rows, int cols, vector problems, - string prefix, bool notch, ExperimentReport * experiment); - void generateRWilcoxonScripts(vector problems, string prefix, - ExperimentReport * experiment); + void generateQualityIndicators(); + void generateLatexTables(); + void generateRBoxplotScripts(int rows, int cols, VectorOfString problems, + std::string prefix, bool notch, ExperimentReport * experiment); + void generateRWilcoxonScripts(VectorOfString problems, std::string prefix, + ExperimentReport * experiment); }; // ExperimentReport diff --git a/src/experiments/Settings.cpp b/src/experiments/Settings.cpp index ef2686d..3eea38e 100644 --- a/src/experiments/Settings.cpp +++ b/src/experiments/Settings.cpp @@ -23,14 +23,16 @@ /** * Default constructor */ -Settings::Settings () { +Settings::Settings () +{ } // Settings /** * Constructor */ -Settings::Settings(char * problemName) { - problemName_ = problemName; +Settings::Settings(char * problemName) +{ + problemName_ = problemName; } // Settings /** @@ -43,7 +45,8 @@ Settings::~Settings() { /* do nothing */ } * * To be implemented. Missing the reflection features of Java here */ -Algorithm * Settings::configure(map settings) { - return NULL ; +Algorithm * Settings::configure(MapOfStringFunct settings) +{ + return nullptr ; } // configure diff --git a/src/experiments/Settings.h b/src/experiments/Settings.h index 02e00e8..730431b 100644 --- a/src/experiments/Settings.h +++ b/src/experiments/Settings.h @@ -26,19 +26,20 @@ #include #include -class Settings { +class Settings +{ protected: - Problem * problem_ ; - string problemName_ ; - string paretoFrontFile_ ; + Problem * problem_ ; + string problemName_ ; + string paretoFrontFile_ ; public: - Settings() ; - Settings(char * problemName) ; - virtual ~Settings() = 0; + Settings() ; + Settings(char * problemName) ; + virtual ~Settings() = 0; - virtual Algorithm * configure() = 0 ; - Algorithm * configure(map settings) ; + virtual Algorithm * configure() = 0 ; + Algorithm * configure(map settings) ; }; // Settings #endif //__SETTINGS__ diff --git a/src/experiments/main/CMakeLists.txt b/src/experiments/main/CMakeLists.txt new file mode 100644 index 0000000..e69de29 diff --git a/src/experiments/main/StandardStudyExecution.cpp b/src/experiments/main/StandardStudyExecution.cpp index 7f12743..64e21f5 100644 --- a/src/experiments/main/StandardStudyExecution.cpp +++ b/src/experiments/main/StandardStudyExecution.cpp @@ -2,6 +2,7 @@ // // Author: // Esteban López-Camacho +// Sérgio Vieira // // Copyright (c) 2011 Antonio J. Nebro, Juan J. Durillo // @@ -36,72 +37,77 @@ * @param experimentIndividualId Index of the experiment individual */ Algorithm * StandardStudyExecution::algorithmSettings(string problemName, - int algorithmId, int experimentIndividualId) { - - Algorithm * alg; - - switch (algorithmId) { - case 0: - algorithmSettingsList_[experimentIndividualId] = - new NSGAII_Settings(problemName); - alg = (algorithmSettingsList_[experimentIndividualId])->configure(); - break; - case 1: - algorithmSettingsList_[experimentIndividualId] = - new SMPSO_Settings(problemName); - alg = (algorithmSettingsList_[experimentIndividualId])->configure(); - break; - case 2: - algorithmSettingsList_[experimentIndividualId] = - new GDE3_Settings(problemName); - alg = (algorithmSettingsList_[experimentIndividualId])->configure(); - break; - } - - return alg; + int algorithmId, int experimentIndividualId) +{ + + Algorithm * alg; + + switch (algorithmId) + { + case 0: + algorithmSettingsList_[experimentIndividualId] = + new NSGAII_Settings(problemName); + alg = (algorithmSettingsList_[experimentIndividualId])->configure(); + break; + case 1: + algorithmSettingsList_[experimentIndividualId] = + new SMPSO_Settings(problemName); + alg = (algorithmSettingsList_[experimentIndividualId])->configure(); + break; + case 2: + algorithmSettingsList_[experimentIndividualId] = + new GDE3_Settings(problemName); + alg = (algorithmSettingsList_[experimentIndividualId])->configure(); + break; + } + + return alg; } // algorithmSettings -int main(int argc, char ** argv) { +int main(int argc, char ** argv) +{ - StandardStudyExecution * exp = new StandardStudyExecution() ; + StandardStudyExecution * exp = new StandardStudyExecution() ; - // Name of the experiment: - exp->experimentName_ = "StandardStudy"; + // Name of the experiment: + exp->experimentName_ = "StandardStudy"; - // List of algorithm names to be used in the experiment - // (please, refer to the README to check the possible values): - vector algorithmNameList_ { - "NSGAII", "SMPSO", "GDE3"}; + // List of algorithm names to be used in the experiment + // (please, refer to the README to check the possible values): + vector algorithmNameList_ + { + "NSGAII", "SMPSO", "GDE3"}; - // List of problem names to be used in the experiment - // (please, refer to the README to check the possible values): - vector problemList_ { - "ZDT1", "ZDT2", "ZDT3", "ZDT4", "ZDT6"}; + // List of problem names to be used in the experiment + // (please, refer to the README to check the possible values): + vector problemList_ + { + "ZDT1", "ZDT2", "ZDT3", "ZDT4", "ZDT6"}; - // Directory where the execution results will be stored: - //exp->experimentBaseDirectory_ = "C:/jMetal/pruebas/jmetal-cpp/" + - exp->experimentBaseDirectory_ = "jMetal/pruebas/jmetal-cpp/" + - exp->experimentName_; + // Directory where the execution results will be stored: + //exp->experimentBaseDirectory_ = "C:/jMetal/pruebas/jmetal-cpp/" + + exp->experimentBaseDirectory_ = "jMetal/pruebas/jmetal-cpp/" + + exp->experimentName_; - // Number of independent runs of each algorithm for each problem: - exp->independentRuns_ = 20; + // Number of independent runs of each algorithm for each problem: + exp->independentRuns_ = 20; - // Number of threads to be used to execute the experiment - int numberOfThreads = 8; - - exp->algorithmNameList_ = algorithmNameList_; - exp->problemList_ = problemList_; - int numberOfAlgorithms = exp->algorithmNameList_.size(); + // Number of threads to be used to execute the experiment + int numberOfThreads = 8; - cout << "Experiment (" << exp->experimentName_ << ") is starting." << endl; + exp->algorithmNameList_ = algorithmNameList_; + exp->problemList_ = problemList_; + int numberOfAlgorithms = exp->algorithmNameList_.size(); - exp->runExperiment(numberOfThreads); + cout << "Experiment (" << exp->experimentName_ << ") is starting." << endl; - cout << "Experiment (" << exp->experimentName_ << ") has finished." << endl; + exp->runExperiment(numberOfThreads); - delete exp; + cout << "Experiment (" << exp->experimentName_ << ") has finished." << endl; + + delete exp; } // main diff --git a/src/experiments/main/StandardStudyExecution.h b/src/experiments/main/StandardStudyExecution.h index c15197c..e535aa3 100644 --- a/src/experiments/main/StandardStudyExecution.h +++ b/src/experiments/main/StandardStudyExecution.h @@ -2,6 +2,7 @@ // // Author: // Esteban López-Camacho +// Sérgio Vieira // // Copyright (c) 2011 Antonio J. Nebro, Juan J. Durillo // @@ -33,11 +34,12 @@ * spread and additive epsilon indicators are used for performance assessment. */ -class StandardStudyExecution : public ExperimentExecution { +class StandardStudyExecution : public ExperimentExecution +{ public: - Algorithm * algorithmSettings(string problemName, int algorithmId, - int experimentIndividualId); + Algorithm * algorithmSettings(string problemName, int algorithmId, + int experimentIndividualId); }; diff --git a/src/experiments/main/StandardStudyExecutionSO.cpp b/src/experiments/main/StandardStudyExecutionSO.cpp index c0b2cfa..d50d2cd 100644 --- a/src/experiments/main/StandardStudyExecutionSO.cpp +++ b/src/experiments/main/StandardStudyExecutionSO.cpp @@ -2,6 +2,7 @@ // // Author: // Esteban López-Camacho +// Sérgio Vieira // // Copyright (c) 2011 Antonio J. Nebro, Juan J. Durillo // @@ -36,77 +37,82 @@ * @param experimentIndividualId Index of the experiment individual */ Algorithm * StandardStudyExecutionSO::algorithmSettings(string problemName, - int algorithmId, int experimentIndividualId) { - - Algorithm * alg; - - switch (algorithmId) { - case 0: - algorithmSettingsList_[experimentIndividualId] = - new gGA_Settings(problemName); - alg = (algorithmSettingsList_[experimentIndividualId])->configure(); - break; - case 1: - algorithmSettingsList_[experimentIndividualId] = - new ssGA_Settings(problemName); - alg = (algorithmSettingsList_[experimentIndividualId])->configure(); - break; - case 2: - algorithmSettingsList_[experimentIndividualId] = - new DE_Settings(problemName); - alg = (algorithmSettingsList_[experimentIndividualId])->configure(); - break; - case 3: - algorithmSettingsList_[experimentIndividualId] = - new PSO_Settings(problemName); - alg = (algorithmSettingsList_[experimentIndividualId])->configure(); - break; - } - - return alg; + int algorithmId, int experimentIndividualId) +{ + + Algorithm * alg; + + switch (algorithmId) + { + case 0: + algorithmSettingsList_[experimentIndividualId] = + new gGA_Settings(problemName); + alg = (algorithmSettingsList_[experimentIndividualId])->configure(); + break; + case 1: + algorithmSettingsList_[experimentIndividualId] = + new ssGA_Settings(problemName); + alg = (algorithmSettingsList_[experimentIndividualId])->configure(); + break; + case 2: + algorithmSettingsList_[experimentIndividualId] = + new DE_Settings(problemName); + alg = (algorithmSettingsList_[experimentIndividualId])->configure(); + break; + case 3: + algorithmSettingsList_[experimentIndividualId] = + new PSO_Settings(problemName); + alg = (algorithmSettingsList_[experimentIndividualId])->configure(); + break; + } + + return alg; } // algorithmSettings -int main(int argc, char ** argv) { +int main(int argc, char ** argv) +{ - StandardStudyExecutionSO * exp = new StandardStudyExecutionSO() ; + StandardStudyExecutionSO * exp = new StandardStudyExecutionSO() ; - // Name of the experiment: - exp->experimentName_ = "StandardStudySO"; + // Name of the experiment: + exp->experimentName_ = "StandardStudySO"; - // List of algorithm names to be used in the experiment - // (please, refer to the README to check the possible values): - vector algorithmNameList_ { - "gGA", "ssGA", "DE", "PSO"}; + // List of algorithm names to be used in the experiment + // (please, refer to the README to check the possible values): + vector algorithmNameList_ + { + "gGA", "ssGA", "DE", "PSO"}; - // List of problem names to be used in the experiment - // (please, refer to the README to check the possible values): - vector problemList_ { - "Sphere", "Griewank"}; + // List of problem names to be used in the experiment + // (please, refer to the README to check the possible values): + vector problemList_ + { + "Sphere", "Griewank"}; - // Directory where the execution results will be stored: - exp->experimentBaseDirectory_ = "C:/jMetal/pruebas/jmetal-cpp/" + - exp->experimentName_; + // Directory where the execution results will be stored: + exp->experimentBaseDirectory_ = "C:/jMetal/pruebas/jmetal-cpp/" + + exp->experimentName_; - // Number of independent runs of each algorithm for each problem: - exp->independentRuns_ = 20; + // Number of independent runs of each algorithm for each problem: + exp->independentRuns_ = 20; - // Number of threads to be used to execute the experiment - int numberOfThreads = 3; + // Number of threads to be used to execute the experiment + int numberOfThreads = 3; - exp->algorithmNameList_ = algorithmNameList_; - exp->problemList_ = problemList_; - int numberOfAlgorithms = exp->algorithmNameList_.size(); - exp->isSingleObjective_ = true; + exp->algorithmNameList_ = algorithmNameList_; + exp->problemList_ = problemList_; + int numberOfAlgorithms = exp->algorithmNameList_.size(); + exp->isSingleObjective_ = true; - cout << "Experiment (" << exp->experimentName_ << ") is starting." << endl; + cout << "Experiment (" << exp->experimentName_ << ") is starting." << endl; - exp->runExperiment(numberOfThreads); + exp->runExperiment(numberOfThreads); - cout << "Experiment (" << exp->experimentName_ << ") has finished." << endl; + cout << "Experiment (" << exp->experimentName_ << ") has finished." << endl; - delete exp; + delete exp; } // main diff --git a/src/experiments/main/StandardStudyExecutionSO.h b/src/experiments/main/StandardStudyExecutionSO.h index c9766a4..8f19baf 100644 --- a/src/experiments/main/StandardStudyExecutionSO.h +++ b/src/experiments/main/StandardStudyExecutionSO.h @@ -2,6 +2,7 @@ // // Author: // Esteban López-Camacho +// Sérgio Vieira // // Copyright (c) 2011 Antonio J. Nebro, Juan J. Durillo // @@ -34,11 +35,12 @@ * spread and additive epsilon indicators are used for performance assessment. */ -class StandardStudyExecutionSO : public ExperimentExecution { +class StandardStudyExecutionSO : public ExperimentExecution +{ public: - Algorithm * algorithmSettings(string problemName, int algorithmId, - int experimentIndividualId); + Algorithm * algorithmSettings(string problemName, int algorithmId, + int experimentIndividualId); }; diff --git a/src/experiments/main/StandardStudyReportPF.cpp b/src/experiments/main/StandardStudyReportPF.cpp index 2ca2d9a..60964e5 100644 --- a/src/experiments/main/StandardStudyReportPF.cpp +++ b/src/experiments/main/StandardStudyReportPF.cpp @@ -2,6 +2,7 @@ // // Author: // Esteban López-Camacho +// Sérgio Vieira // // Copyright (c) 2011 Antonio J. Nebro, Juan J. Durillo // @@ -29,74 +30,80 @@ */ -int main(int argc, char ** argv) { - StandardStudyReportPF * exp = new StandardStudyReportPF() ; - - // Name of the experiment: - exp->experimentName_ = "StandardStudy"; - - // List of algorithm names to be analyzed in the experiment - // (please, refer to the README to check the possible values): - vector algorithmNameList_ { - "NSGAII", "SMPSO", "GDE3"}; - exp->algorithmNameList_ = algorithmNameList_; - - // List of problem names to be analyzed in the experiment - // (please, refer to the README to check the possible values): - vector problemList_ { - "ZDT1", "ZDT2", "ZDT3", "ZDT4", "ZDT6"}; - exp->problemList_ = problemList_; - - // List of optimal pareto front files to be used when calculating quality - // indicators. It's not necessary to define this variable when not knowing - // or not wanting to use optimal pareto fronts. - vector paretoFrontFile_ { - "ZDT1.pf", "ZDT2.pf", "ZDT3.pf", "ZDT4.pf", "ZDT6.pf"}; - exp->paretoFrontFile_ = paretoFrontFile_; - - // List of quality indicator names to be calculated in the reports - // (please, refer to the README to check the possible values): - vector indicatorList_ { - "HV", "SPREAD", "EPSILON"}; - exp->indicatorList_ = indicatorList_; - - // Directory from where the execution results will be readed: - exp->experimentBaseDirectory_ = "C:/jMetal/pruebas/jmetal-cpp/" + - exp->experimentName_; - - // Directory from where the optimal pareto front files will be readed. - // Comment this following line to not use pareto fronts in order to - // calculate reference fronts. - exp->paretoFrontDirectory_ = "C:/jMetal/pruebas/data/paretoFronts"; +int main(int argc, char ** argv) +{ + StandardStudyReportPF * exp = new StandardStudyReportPF() ; + + // Name of the experiment: + exp->experimentName_ = "StandardStudy"; + + // List of algorithm names to be analyzed in the experiment + // (please, refer to the README to check the possible values): + vector algorithmNameList_ + { + "NSGAII", "SMPSO", "GDE3"}; + exp->algorithmNameList_ = algorithmNameList_; + + // List of problem names to be analyzed in the experiment + // (please, refer to the README to check the possible values): + vector problemList_ + { + "ZDT1", "ZDT2", "ZDT3", "ZDT4", "ZDT6"}; + exp->problemList_ = problemList_; + + // List of optimal pareto front files to be used when calculating quality + // indicators. It's not necessary to define this variable when not knowing + // or not wanting to use optimal pareto fronts. + vector paretoFrontFile_ + { + "ZDT1.pf", "ZDT2.pf", "ZDT3.pf", "ZDT4.pf", "ZDT6.pf"}; + exp->paretoFrontFile_ = paretoFrontFile_; + + // List of quality indicator names to be calculated in the reports + // (please, refer to the README to check the possible values): + vector indicatorList_ + { + "HV", "SPREAD", "EPSILON"}; + exp->indicatorList_ = indicatorList_; + + // Directory from where the execution results will be readed: + exp->experimentBaseDirectory_ = "C:/jMetal/pruebas/jmetal-cpp/" + + exp->experimentName_; + + // Directory from where the optimal pareto front files will be readed. + // Comment this following line to not use pareto fronts in order to + // calculate reference fronts. + exp->paretoFrontDirectory_ = "C:/jMetal/pruebas/data/paretoFronts"; // // Directory where the calculated references front files will be stored. // // This line is not needed when you are using existing optimal pareto fronts. // exp->referenceFrontDirectory_= "C:/antonio/Softw/pruebas/data/referenceFronts"; - // Number of independent runs of each algorithm for each problem: - exp->independentRuns_ = 20; + // Number of independent runs of each algorithm for each problem: + exp->independentRuns_ = 20; - int numberOfAlgorithms = exp->algorithmNameList_.size(); + int numberOfAlgorithms = exp->algorithmNameList_.size(); - // Generate quality indicators - exp->generateQualityIndicators(); + // Generate quality indicators + exp->generateQualityIndicators(); - // Generate latex tables (comment this sentence is not desired) - exp->generateLatexTables(); + // Generate latex tables (comment this sentence is not desired) + exp->generateLatexTables(); - // Configure the R scripts to be generated - int rows = 3 ; - int columns = 2 ; - string prefix = "ZDT"; - vector problemsValues { - "ZDT1", "ZDT2", "ZDT3", "ZDT4", "ZDT6"}; - vector problems = problemsValues; + // Configure the R scripts to be generated + int rows = 3 ; + int columns = 2 ; + string prefix = "ZDT"; + vector problemsValues + { + "ZDT1", "ZDT2", "ZDT3", "ZDT4", "ZDT6"}; + vector problems = problemsValues; - bool notch; - exp->generateRBoxplotScripts(rows, columns, problems, prefix, notch = false, exp); - exp->generateRWilcoxonScripts(problems, prefix, exp); + bool notch; + exp->generateRBoxplotScripts(rows, columns, problems, prefix, notch = false, exp); + exp->generateRWilcoxonScripts(problems, prefix, exp); - delete exp; + delete exp; } // main diff --git a/src/experiments/main/StandardStudyReportPF.h b/src/experiments/main/StandardStudyReportPF.h index 6a2a043..9d88ac2 100644 --- a/src/experiments/main/StandardStudyReportPF.h +++ b/src/experiments/main/StandardStudyReportPF.h @@ -2,6 +2,7 @@ // // Author: // Esteban López-Camacho +// Sérgio Vieira // // Copyright (c) 2011 Antonio J. Nebro, Juan J. Durillo // diff --git a/src/experiments/main/StandardStudyReportRF.cpp b/src/experiments/main/StandardStudyReportRF.cpp index e6a57fe..e4719b2 100644 --- a/src/experiments/main/StandardStudyReportRF.cpp +++ b/src/experiments/main/StandardStudyReportRF.cpp @@ -2,6 +2,7 @@ // // Author: // Esteban López-Camacho +// Sérgio Vieira // // Copyright (c) 2011 Antonio J. Nebro, Juan J. Durillo // @@ -29,23 +30,26 @@ */ -int main(int argc, char ** argv) { - StandardStudyReportRF * exp = new StandardStudyReportRF() ; +int main(int argc, char ** argv) +{ + StandardStudyReportRF * exp = new StandardStudyReportRF() ; - // Name of the experiment: - exp->experimentName_ = "StandardStudy"; + // Name of the experiment: + exp->experimentName_ = "StandardStudy"; - // List of algorithm names to be analyzed in the experiment - // (please, refer to the README to check the possible values): - vector algorithmNameList_ { - "NSGAII", "SMPSO", "GDE3"}; - exp->algorithmNameList_ = algorithmNameList_; + // List of algorithm names to be analyzed in the experiment + // (please, refer to the README to check the possible values): + vector algorithmNameList_ + { + "NSGAII", "SMPSO", "GDE3"}; + exp->algorithmNameList_ = algorithmNameList_; - // List of problem names to be analyzed in the experiment - // (please, refer to the README to check the possible values): - vector problemList_ { - "ZDT1", "ZDT2", "ZDT3", "ZDT4", "ZDT6"}; - exp->problemList_ = problemList_; + // List of problem names to be analyzed in the experiment + // (please, refer to the README to check the possible values): + vector problemList_ + { + "ZDT1", "ZDT2", "ZDT3", "ZDT4", "ZDT6"}; + exp->problemList_ = problemList_; // // List of optimal pareto front files to be used when calculating quality // // indicators. It's not necessary to define this variable when not knowing @@ -54,15 +58,16 @@ int main(int argc, char ** argv) { // "ZDT1.pf", "ZDT2.pf", "ZDT3.pf", "ZDT4.pf", "ZDT6.pf"}; // exp->paretoFrontFile_.assign(paretoFrontFile_, end(paretoFrontFile_)); - // List of quality indicator names to be calculated in the reports - // (please, refer to the README to check the possible values): - vector indicatorList_ { - "HV", "SPREAD", "EPSILON"}; - exp->indicatorList_ = indicatorList_; + // List of quality indicator names to be calculated in the reports + // (please, refer to the README to check the possible values): + vector indicatorList_ + { + "HV", "SPREAD", "EPSILON"}; + exp->indicatorList_ = indicatorList_; - // Directory from where the execution results will be readed: - exp->experimentBaseDirectory_ = "C:/jMetal/pruebas/jmetal-cpp/" + - exp->experimentName_; + // Directory from where the execution results will be readed: + exp->experimentBaseDirectory_ = "C:/jMetal/pruebas/jmetal-cpp/" + + exp->experimentName_; // // Directory from where the optimal pareto front files will be readed. // // Comment this following line to not use pareto fronts in order to @@ -73,30 +78,31 @@ int main(int argc, char ** argv) { // // This line is not needed when you are using existing optimal pareto fronts. // exp->referenceFrontDirectory_= "C:/antonio/Softw/pruebas/data/referenceFronts"; - // Number of independent runs of each algorithm for each problem: - exp->independentRuns_ = 20; + // Number of independent runs of each algorithm for each problem: + exp->independentRuns_ = 20; - int numberOfAlgorithms = exp->algorithmNameList_.size(); + int numberOfAlgorithms = exp->algorithmNameList_.size(); - // Generate quality indicators - exp->generateQualityIndicators(); + // Generate quality indicators + exp->generateQualityIndicators(); - // Generate latex tables (comment this sentence is not desired) - exp->generateLatexTables(); + // Generate latex tables (comment this sentence is not desired) + exp->generateLatexTables(); - // Configure the R scripts to be generated - int rows = 3 ; - int columns = 2 ; - string prefix = "ZDT"; - vector problemsValues { - "ZDT1", "ZDT2", "ZDT3", "ZDT4", "ZDT6"}; - vector problems = problemsValues; + // Configure the R scripts to be generated + int rows = 3 ; + int columns = 2 ; + string prefix = "ZDT"; + vector problemsValues + { + "ZDT1", "ZDT2", "ZDT3", "ZDT4", "ZDT6"}; + vector problems = problemsValues; - bool notch; - exp->generateRBoxplotScripts(rows, columns, problems, prefix, notch = false, exp); - exp->generateRWilcoxonScripts(problems, prefix, exp); + bool notch; + exp->generateRBoxplotScripts(rows, columns, problems, prefix, notch = false, exp); + exp->generateRWilcoxonScripts(problems, prefix, exp); - delete exp; + delete exp; } // main diff --git a/src/experiments/main/StandardStudyReportRF.h b/src/experiments/main/StandardStudyReportRF.h index 9c02d16..239173d 100644 --- a/src/experiments/main/StandardStudyReportRF.h +++ b/src/experiments/main/StandardStudyReportRF.h @@ -2,6 +2,7 @@ // // Author: // Esteban López-Camacho +// Sérgio Vieira // // Copyright (c) 2011 Antonio J. Nebro, Juan J. Durillo // diff --git a/src/experiments/main/StandardStudyReportSO.cpp b/src/experiments/main/StandardStudyReportSO.cpp index a49251b..5c79fab 100644 --- a/src/experiments/main/StandardStudyReportSO.cpp +++ b/src/experiments/main/StandardStudyReportSO.cpp @@ -2,6 +2,7 @@ // // Author: // Esteban López-Camacho +// Sérgio Vieira // // Copyright (c) 2011 Antonio J. Nebro, Juan J. Durillo // @@ -29,23 +30,26 @@ */ -int main(int argc, char ** argv) { - StandardStudyReportSO * exp = new StandardStudyReportSO() ; +int main(int argc, char ** argv) +{ + StandardStudyReportSO * exp = new StandardStudyReportSO() ; - // Name of the experiment: - exp->experimentName_ = "StandardStudySO"; + // Name of the experiment: + exp->experimentName_ = "StandardStudySO"; - // List of algorithm names to be analyzed in the experiment - // (please, refer to the README to check the possible values): - vector algorithmNameList_ { - "gGA", "ssGA", "DE", "PSO"}; - exp->algorithmNameList_ = algorithmNameList_; + // List of algorithm names to be analyzed in the experiment + // (please, refer to the README to check the possible values): + vector algorithmNameList_ + { + "gGA", "ssGA", "DE", "PSO"}; + exp->algorithmNameList_ = algorithmNameList_; - // List of problem names to be analyzed in the experiment - // (please, refer to the README to check the possible values): - vector problemList_ { - "Sphere", "Griewank"}; - exp->problemList_ = problemList_; + // List of problem names to be analyzed in the experiment + // (please, refer to the README to check the possible values): + vector problemList_ + { + "Sphere", "Griewank"}; + exp->problemList_ = problemList_; // // List of optimal pareto front files to be used when calculating quality // // indicators. It's not necessary to define this variable when not knowing @@ -54,15 +58,16 @@ int main(int argc, char ** argv) { // "ZDT1.pf", "ZDT2.pf", "ZDT3.pf", "ZDT4.pf", "ZDT6.pf"}; // exp->paretoFrontFile_.assign(paretoFrontFile_, end(paretoFrontFile_)); - // List of quality indicator names to be calculated in the reports - // (please, refer to the README to check the possible values): - vector indicatorList_ { - "FIT"}; - exp->indicatorList_ = indicatorList_; + // List of quality indicator names to be calculated in the reports + // (please, refer to the README to check the possible values): + vector indicatorList_ + { + "FIT"}; + exp->indicatorList_ = indicatorList_; - // Directory from where the execution results will be readed: - exp->experimentBaseDirectory_ = "C:/jMetal/pruebas/jmetal-cpp/" + - exp->experimentName_; + // Directory from where the execution results will be readed: + exp->experimentBaseDirectory_ = "C:/jMetal/pruebas/jmetal-cpp/" + + exp->experimentName_; // // Directory from where the optimal pareto front files will be readed. // // Comment this following line to not use pareto fronts in order to @@ -73,31 +78,32 @@ int main(int argc, char ** argv) { // // This line is not needed when you are using existing optimal pareto fronts. // exp->referenceFrontDirectory_= "C:/antonio/Softw/pruebas/data/referenceFronts"; - // Number of independent runs of each algorithm for each problem: - exp->independentRuns_ = 20; + // Number of independent runs of each algorithm for each problem: + exp->independentRuns_ = 20; - int numberOfAlgorithms = exp->algorithmNameList_.size(); - exp->isSingleObjective_ = true; + int numberOfAlgorithms = exp->algorithmNameList_.size(); + exp->isSingleObjective_ = true; - // Generate quality indicators - exp->generateQualityIndicators(); + // Generate quality indicators + exp->generateQualityIndicators(); - // Generate latex tables (comment this sentence is not desired) - exp->generateLatexTables(); + // Generate latex tables (comment this sentence is not desired) + exp->generateLatexTables(); - // Configure the R scripts to be generated - int rows = 3 ; - int columns = 2 ; - string prefix = "SO"; - vector problemsValues { - "Sphere", "Griewank"}; - vector problems = problemsValues; + // Configure the R scripts to be generated + int rows = 3 ; + int columns = 2 ; + string prefix = "SO"; + vector problemsValues + { + "Sphere", "Griewank"}; + vector problems = problemsValues; - bool notch; - exp->generateRBoxplotScripts(rows, columns, problems, prefix, notch = false, exp); - exp->generateRWilcoxonScripts(problems, prefix, exp); + bool notch; + exp->generateRBoxplotScripts(rows, columns, problems, prefix, notch = false, exp); + exp->generateRWilcoxonScripts(problems, prefix, exp); - delete exp; + delete exp; } // main diff --git a/src/experiments/main/StandardStudyReportSO.h b/src/experiments/main/StandardStudyReportSO.h index ab64ce9..d6ba028 100644 --- a/src/experiments/main/StandardStudyReportSO.h +++ b/src/experiments/main/StandardStudyReportSO.h @@ -2,6 +2,7 @@ // // Author: // Esteban López-Camacho +// Sérgio Vieira // // Copyright (c) 2011 Antonio J. Nebro, Juan J. Durillo // diff --git a/src/experiments/settings/CMakeLists.txt b/src/experiments/settings/CMakeLists.txt new file mode 100644 index 0000000..294ec59 --- /dev/null +++ b/src/experiments/settings/CMakeLists.txt @@ -0,0 +1,3 @@ +file(GLOB SOURCES "*.cpp" "*.h") +ListToString(SOURCES ";" ${SOURCES}) +LIST_APPEND("${SOURCES}") \ No newline at end of file diff --git a/src/experiments/settings/DE_Settings.cpp b/src/experiments/settings/DE_Settings.cpp index 04a5ef2..6685cbd 100644 --- a/src/experiments/settings/DE_Settings.cpp +++ b/src/experiments/settings/DE_Settings.cpp @@ -2,6 +2,7 @@ // // Author: // Esteban López-Camacho +// Sérgio Vieira // // Copyright (c) 2011 Antonio J. Nebro, Juan J. Durillo // @@ -23,65 +24,69 @@ /** * Default constructor */ -DE_Settings::DE_Settings () : Settings() { +DE_Settings::DE_Settings () : Settings() +{ } // DE_Settings /** * Destructor */ -DE_Settings::~DE_Settings () { - delete algorithm ; - delete crossover ; // Crossover operator - delete selection ; // Selection operator +DE_Settings::~DE_Settings () +{ + delete algorithm ; + delete crossover ; // Crossover operator + delete selection ; // Selection operator } // ~DE_Settings /** * Constructor */ -DE_Settings::DE_Settings(string problemName) { - problemName_ = problemName ; +DE_Settings::DE_Settings(std::string problemName) +{ + problemName_ = problemName ; - problem_ = ProblemFactory::getProblem((char *) problemName_.c_str()); + problem_ = ProblemFactory::getProblem((char *) problemName_.c_str()); - // Algorithm parameters - populationSize_ = 100; - maxEvaluations_ = 25000; - crParameter_ = 0.5; - fParameter_ = 0.5; - deVariantParameter_ = "rand/1/bin"; + // Algorithm parameters + populationSize_ = 100; + maxEvaluations_ = 25000; + crParameter_ = 0.5; + fParameter_ = 0.5; + deVariantParameter_ = "rand/1/bin"; } // DE_Settings /** * Configure method */ -Algorithm * DE_Settings::configure() { +Algorithm * DE_Settings::configure() +{ - algorithm = new DE(problem_); - algorithm->setInputParameter("populationSize",&populationSize_); - algorithm->setInputParameter("maxEvaluations",&maxEvaluations_); + algorithm = snew DE(problem_); + algorithm->setInputParameter("populationSize",&populationSize_); + algorithm->setInputParameter("maxEvaluations",&maxEvaluations_); - map parameters; + MapOfStringFunct parameters; - // Crossover operator - double crParameter = crParameter_; - double fParameter = fParameter_; - parameters["CR"] = &crParameter; - parameters["F"] = &fParameter; - string deVariantParameter = deVariantParameter_; - parameters["DE_VARIANT"] = &deVariantParameter; - crossover = new DifferentialEvolutionCrossover(parameters); + // Crossover operator + double crParameter = crParameter_; + double fParameter = fParameter_; + parameters["CR"] = &crParameter; + parameters["F"] = &fParameter; + std::string deVariantParameter = deVariantParameter_; + parameters["DE_VARIANT"] = &deVariantParameter; + crossover = snew DifferentialEvolutionCrossover(parameters); - // Selection operator - parameters.clear(); - selection = new DifferentialEvolutionSelection(parameters) ; + // Selection operator + parameters.clear(); + selection = snew DifferentialEvolutionSelection(parameters) ; - // Add the operators to the algorithm - algorithm->addOperator("crossover",crossover); - algorithm->addOperator("selection",selection); + // Add the operators to the algorithm + algorithm->addOperator("crossover",crossover); + algorithm->addOperator("selection",selection); - cout << "DE algorithm initialized." << endl; + std::cout << "DE algorithm initialized." << std::endl; - return algorithm ; + return algorithm ; } // configure diff --git a/src/experiments/settings/DE_Settings.h b/src/experiments/settings/DE_Settings.h index f3d224e..da4b8d8 100644 --- a/src/experiments/settings/DE_Settings.h +++ b/src/experiments/settings/DE_Settings.h @@ -2,6 +2,7 @@ // // Author: // Esteban López-Camacho +// Sérgio Vieira // // Copyright (c) 2011 Antonio J. Nebro, Juan J. Durillo // @@ -26,24 +27,25 @@ #include #include -class DE_Settings : public Settings { +class DE_Settings : public Settings +{ private: - int populationSize_ ; - int maxEvaluations_ ; - double crParameter_ ; - double fParameter_ ; - string deVariantParameter_ ; + int populationSize_ ; + int maxEvaluations_ ; + double crParameter_ ; + double fParameter_ ; + std::string deVariantParameter_ ; - Algorithm * algorithm ; - Operator * crossover ; // Crossover operator - Operator * selection ; // Selection operator + Algorithm * algorithm ; + Operator * crossover ; // Crossover operator + Operator * selection ; // Selection operator public: - DE_Settings() ; - DE_Settings(string problemName) ; - ~DE_Settings() ; + DE_Settings() ; + DE_Settings(std::string problemName) ; + ~DE_Settings() ; - Algorithm * configure() ; + Algorithm * configure() ; }; // DE_Settings #endif // __DE_SETTINGS__ diff --git a/src/experiments/settings/GDE3_Settings.cpp b/src/experiments/settings/GDE3_Settings.cpp index e7920f6..54a2c4b 100644 --- a/src/experiments/settings/GDE3_Settings.cpp +++ b/src/experiments/settings/GDE3_Settings.cpp @@ -2,6 +2,7 @@ // // Author: // Esteban López-Camacho +// Sérgio Vieira // // Copyright (c) 2011 Antonio J. Nebro, Juan J. Durillo // @@ -25,34 +26,37 @@ /** * Default constructor */ -GDE3_Settings::GDE3_Settings () : Settings() { +GDE3_Settings::GDE3_Settings () : Settings() +{ } // GDE3_Settings /** * Destructor */ -GDE3_Settings::~GDE3_Settings () { - delete algorithm ; - delete crossover ; // Crossover operator - delete selection ; // Selection operator +GDE3_Settings::~GDE3_Settings () +{ + delete algorithm ; + delete crossover ; // Crossover operator + delete selection ; // Selection operator } // ~GDE3_Settings /** * Constructor */ -GDE3_Settings::GDE3_Settings(string problemName) { +GDE3_Settings::GDE3_Settings(std::string problemName) +{ - problemName_ = problemName ; + problemName_ = problemName ; - problem_ = ProblemFactory::getProblem((char *) problemName_.c_str()); + problem_ = ProblemFactory::getProblem((char *) problemName_.c_str()); - // Default settings - CR_ = 0.5; - F_ = 0.5; - populationSize_ = 100; - maxIterations_ = 250; + // Default settings + CR_ = 0.5; + F_ = 0.5; + populationSize_ = 100; + maxIterations_ = 250; } // GDE3_Settings @@ -60,32 +64,33 @@ GDE3_Settings::GDE3_Settings(string problemName) { /** * Configure method */ -Algorithm * GDE3_Settings::configure() { +Algorithm * GDE3_Settings::configure() +{ - algorithm = new GDE3(problem_); - algorithm->setInputParameter("populationSize",&populationSize_); - algorithm->setInputParameter("maxIterations",&maxIterations_); + algorithm = snew GDE3(problem_); + algorithm->setInputParameter("populationSize",&populationSize_); + algorithm->setInputParameter("maxIterations",&maxIterations_); - // Mutation and Crossover for Real codification - map parameters; + // Mutation and Crossover for Real codification + MapOfStringFunct parameters; - double CR = CR_; - double F = F_; - parameters["CR"] = &CR; - parameters["F"] = &F; - crossover = new DifferentialEvolutionCrossover(parameters); + double CR = CR_; + double F = F_; + parameters["CR"] = &CR; + parameters["F"] = &F; + crossover = snew DifferentialEvolutionCrossover(parameters); - // Selection Operator - parameters.clear(); - selection = new DifferentialEvolutionSelection(parameters); + // Selection Operator + parameters.clear(); + selection = snew DifferentialEvolutionSelection(parameters); - // Add the operators to the algorithm - algorithm->addOperator("crossover",crossover); - algorithm->addOperator("selection",selection); + // Add the operators to the algorithm + algorithm->addOperator("crossover",crossover); + algorithm->addOperator("selection",selection); - cout << "GDE3 algorithm initialized." << endl; + std::cout << "GDE3 algorithm initialized." << std::endl; - return algorithm ; + return algorithm ; } // configure diff --git a/src/experiments/settings/GDE3_Settings.h b/src/experiments/settings/GDE3_Settings.h index b501788..d5cfbbb 100644 --- a/src/experiments/settings/GDE3_Settings.h +++ b/src/experiments/settings/GDE3_Settings.h @@ -2,6 +2,7 @@ // // Author: // Esteban López-Camacho +// Sérgio Vieira // // Copyright (c) 2011 Antonio J. Nebro, Juan J. Durillo // @@ -26,25 +27,26 @@ #include #include -class GDE3_Settings : public Settings{ +class GDE3_Settings : public Settings +{ private: - double CR_ ; - double F_ ; - int populationSize_ ; - int maxIterations_ ; + double CR_ ; + double F_ ; + int populationSize_ ; + int maxIterations_ ; - Algorithm * algorithm ; - Operator * crossover ; // Crossover operator - Operator * selection ; // Selection operator + Algorithm * algorithm ; + Operator * crossover ; // Crossover operator + Operator * selection ; // Selection operator public: - GDE3_Settings() ; - GDE3_Settings(string problemName) ; - ~GDE3_Settings() ; + GDE3_Settings() ; + GDE3_Settings(std::string problemName) ; + ~GDE3_Settings() ; - Algorithm * configure() ; + Algorithm * configure() ; }; // GDE3_Settings diff --git a/src/experiments/settings/NSGAII_Settings.cpp b/src/experiments/settings/NSGAII_Settings.cpp index 4bbb008..b9c6c93 100644 --- a/src/experiments/settings/NSGAII_Settings.cpp +++ b/src/experiments/settings/NSGAII_Settings.cpp @@ -24,72 +24,76 @@ /** * Default constructor */ -NSGAII_Settings::NSGAII_Settings () : Settings() { +NSGAII_Settings::NSGAII_Settings () : Settings() +{ } // NSGAII_Settings /** * Destructor */ -NSGAII_Settings::~NSGAII_Settings () { - delete algorithm ; - delete crossover ; // Crossover operator - delete mutation ; // Mutation operator - delete selection ; // Selection operator +NSGAII_Settings::~NSGAII_Settings () +{ + delete algorithm ; + delete crossover ; // Crossover operator + delete mutation ; // Mutation operator + delete selection ; // Selection operator } // ~NSGAII_Settings /** * Constructor */ -NSGAII_Settings::NSGAII_Settings(string problemName) { - problemName_ = problemName ; - - problem_ = ProblemFactory::getProblem((char *) problemName_.c_str()); - - // Algorithm parameters - populationSize_ = 100; - maxEvaluations_ = 25000; - mutationProbability_ = 1.0/problem_->getNumberOfVariables() ; - crossoverProbability_ = 0.9 ; - mutationDistributionIndex_ = 20.0 ; - crossoverDistributionIndex_ = 20.0 ; +NSGAII_Settings::NSGAII_Settings(std::string problemName) +{ + problemName_ = problemName ; + + problem_ = ProblemFactory::getProblem((char *) problemName_.c_str()); + + // Algorithm parameters + populationSize_ = 100; + maxEvaluations_ = 25000; + mutationProbability_ = 1.0/problem_->getNumberOfVariables() ; + crossoverProbability_ = 0.9 ; + mutationDistributionIndex_ = 20.0 ; + crossoverDistributionIndex_ = 20.0 ; } // NSGAII_Settings /** * Configure method */ -Algorithm * NSGAII_Settings::configure() { +Algorithm * NSGAII_Settings::configure() +{ - algorithm = new NSGAII(problem_); - algorithm->setInputParameter("populationSize",&populationSize_); - algorithm->setInputParameter("maxEvaluations",&maxEvaluations_); + algorithm = new NSGAII(problem_); + algorithm->setInputParameter("populationSize",&populationSize_); + algorithm->setInputParameter("maxEvaluations",&maxEvaluations_); - // Mutation and Crossover for Real codification - map parameters; + // Mutation and Crossover for Real codification + MapOfStringFunct parameters; - double crossoverProbability = crossoverProbability_; - double crossoverDistributionIndex = crossoverDistributionIndex_ ; - parameters["probability"] = &crossoverProbability; - parameters["distributionIndex"] = &crossoverDistributionIndex; - crossover = new SBXCrossover(parameters); + double crossoverProbability = crossoverProbability_; + double crossoverDistributionIndex = crossoverDistributionIndex_ ; + parameters["probability"] = &crossoverProbability; + parameters["distributionIndex"] = &crossoverDistributionIndex; + crossover = new SBXCrossover(parameters); - parameters.clear(); - double mutationProbability = mutationProbability_; - double mutationDistributionIndex = mutationDistributionIndex_; - parameters["probability"] = &mutationProbability; - parameters["distributionIndex"] = &mutationDistributionIndex; - mutation = new PolynomialMutation(parameters); + parameters.clear(); + double mutationProbability = mutationProbability_; + double mutationDistributionIndex = mutationDistributionIndex_; + parameters["probability"] = &mutationProbability; + parameters["distributionIndex"] = &mutationDistributionIndex; + mutation = new PolynomialMutation(parameters); - // Selection Operator - parameters.clear(); - selection = new BinaryTournament2(parameters); + // Selection Operator + parameters.clear(); + selection = new BinaryTournament2(parameters); - // Add the operators to the algorithm - algorithm->addOperator("crossover",crossover); - algorithm->addOperator("mutation",mutation); - algorithm->addOperator("selection",selection); + // Add the operators to the algorithm + algorithm->addOperator("crossover",crossover); + algorithm->addOperator("mutation",mutation); + algorithm->addOperator("selection",selection); - cout << "NGSAII algorithm initialized." << endl; + std::cout << "NGSAII algorithm initialized." << std::endl; - return algorithm ; + return algorithm ; } // configure diff --git a/src/experiments/settings/NSGAII_Settings.h b/src/experiments/settings/NSGAII_Settings.h index 35183cd..d0b3368 100644 --- a/src/experiments/settings/NSGAII_Settings.h +++ b/src/experiments/settings/NSGAII_Settings.h @@ -28,26 +28,27 @@ #include #include -class NSGAII_Settings : public Settings{ +class NSGAII_Settings : public Settings +{ private: - int populationSize_ ; - int maxEvaluations_ ; - double mutationProbability_ ; - double crossoverProbability_ ; - double mutationDistributionIndex_ ; - double crossoverDistributionIndex_ ; + int populationSize_ ; + int maxEvaluations_ ; + double mutationProbability_ ; + double crossoverProbability_ ; + double mutationDistributionIndex_ ; + double crossoverDistributionIndex_ ; - Algorithm * algorithm ; - Operator * crossover ; // Crossover operator - Operator * mutation ; // Mutation operator - Operator * selection ; // Selection operator + Algorithm * algorithm ; + Operator * crossover ; // Crossover operator + Operator * mutation ; // Mutation operator + Operator * selection ; // Selection operator public: - NSGAII_Settings() ; - NSGAII_Settings(string problemName) ; - ~NSGAII_Settings() ; + NSGAII_Settings() ; + NSGAII_Settings(std::string problemName) ; + ~NSGAII_Settings() ; - Algorithm * configure() ; + Algorithm * configure() ; }; // NSGAII_Settings #endif // __NSGAII_SETTINGS__ diff --git a/src/experiments/settings/PSO_Settings.cpp b/src/experiments/settings/PSO_Settings.cpp index 89e70c5..d6032e9 100644 --- a/src/experiments/settings/PSO_Settings.cpp +++ b/src/experiments/settings/PSO_Settings.cpp @@ -2,6 +2,7 @@ // // Author: // Esteban López-Camacho +// Sérgio Vieira // // Copyright (c) 2011 Antonio J. Nebro, Juan J. Durillo // @@ -25,33 +26,36 @@ /** * Default constructor */ -PSO_Settings::PSO_Settings () : Settings() { +PSO_Settings::PSO_Settings () : Settings() +{ } // PSO_Settings /** * Destructor */ -PSO_Settings::~PSO_Settings () { - delete algorithm ; - delete mutation ; // Mutation operator +PSO_Settings::~PSO_Settings () +{ + delete algorithm ; + delete mutation ; // Mutation operator } // ~PSO_Settings /** * Constructor */ -PSO_Settings::PSO_Settings(string problemName) { +PSO_Settings::PSO_Settings(std::string problemName) +{ - problemName_ = problemName ; + problemName_ = problemName ; - problem_ = ProblemFactory::getProblem((char *) problemName_.c_str()); + problem_ = ProblemFactory::getProblem((char *) problemName_.c_str()); - // Default settings - swarmSize_ = 50 ; - maxIterations_ = 5000 ; - mutationDistributionIndex_ = 20.0 ; - mutationProbability_ = 1.0/problem_->getNumberOfVariables() ; + // Default settings + swarmSize_ = 50 ; + maxIterations_ = 5000 ; + mutationDistributionIndex_ = 20.0 ; + mutationProbability_ = 1.0/problem_->getNumberOfVariables() ; } // PSO_Settings @@ -59,27 +63,28 @@ PSO_Settings::PSO_Settings(string problemName) { /** * Configure method */ -Algorithm * PSO_Settings::configure() { +Algorithm * PSO_Settings::configure() +{ - algorithm = new PSO(problem_); - algorithm->setInputParameter("swarmSize", &swarmSize_); - algorithm->setInputParameter("maxIterations", &maxIterations_); + algorithm = new PSO(problem_); + algorithm->setInputParameter("swarmSize", &swarmSize_); + algorithm->setInputParameter("maxIterations", &maxIterations_); - map parameters; + MapOfStringFunct parameters; - // Mutation operator - double mutationProbability = mutationProbability_; - double mutationDistributionIndex = mutationDistributionIndex_; - parameters["probability"] = &mutationProbability; - parameters["distributionIndex"] = &mutationDistributionIndex; - mutation = new PolynomialMutation(parameters); + // Mutation operator + double mutationProbability = mutationProbability_; + double mutationDistributionIndex = mutationDistributionIndex_; + parameters["probability"] = &mutationProbability; + parameters["distributionIndex"] = &mutationDistributionIndex; + mutation = new PolynomialMutation(parameters); - // Add the operators to the algorithm - algorithm->addOperator("mutation",mutation); + // Add the operators to the algorithm + algorithm->addOperator("mutation",mutation); - cout << "PSO algorithm initialized." << endl; + std::cout << "PSO algorithm initialized." << std::endl; - return algorithm ; + return algorithm ; } // configure diff --git a/src/experiments/settings/PSO_Settings.h b/src/experiments/settings/PSO_Settings.h index ac1ac8f..1646ae3 100644 --- a/src/experiments/settings/PSO_Settings.h +++ b/src/experiments/settings/PSO_Settings.h @@ -2,6 +2,7 @@ // // Author: // Esteban López-Camacho +// Sérgio Vieira // // Copyright (c) 2011 Antonio J. Nebro, Juan J. Durillo // @@ -25,23 +26,24 @@ #include #include -class PSO_Settings : public Settings { +class PSO_Settings : public Settings +{ private: - int swarmSize_ ; - int maxIterations_ ; - double mutationDistributionIndex_ ; - double mutationProbability_ ; + int swarmSize_ ; + int maxIterations_ ; + double mutationDistributionIndex_ ; + double mutationProbability_ ; - Algorithm * algorithm ; - Operator * mutation ; // Mutation operator + Algorithm * algorithm ; + Operator * mutation ; // Mutation operator public: - PSO_Settings() ; - PSO_Settings(string problemName) ; - ~PSO_Settings() ; + PSO_Settings() ; + PSO_Settings(std::string problemName) ; + ~PSO_Settings() ; - Algorithm * configure() ; + Algorithm * configure() ; }; // PSO_Settings #endif // __PSO_SETTINGS__ diff --git a/src/experiments/settings/SMPSO_Settings.cpp b/src/experiments/settings/SMPSO_Settings.cpp index d862f05..24b03bb 100644 --- a/src/experiments/settings/SMPSO_Settings.cpp +++ b/src/experiments/settings/SMPSO_Settings.cpp @@ -2,6 +2,7 @@ // // Author: // Esteban López-Camacho +// Sérgio Vieira // // Copyright (c) 2011 Antonio J. Nebro, Juan J. Durillo // @@ -25,34 +26,37 @@ /** * Default constructor */ -SMPSO_Settings::SMPSO_Settings () : Settings() { +SMPSO_Settings::SMPSO_Settings () : Settings() +{ } // SMPSO_Settings /** * Destructor */ -SMPSO_Settings::~SMPSO_Settings () { - delete algorithm ; - delete mutation ; // Mutation operator +SMPSO_Settings::~SMPSO_Settings () +{ + delete algorithm ; + delete mutation ; // Mutation operator } // ~SMPSO_Settings /** * Constructor */ -SMPSO_Settings::SMPSO_Settings(string problemName) { +SMPSO_Settings::SMPSO_Settings(std::string problemName) +{ - problemName_ = problemName ; + problemName_ = problemName ; - problem_ = ProblemFactory::getProblem((char *) problemName_.c_str()); + problem_ = ProblemFactory::getProblem((char *) problemName_.c_str()); - // Default settings - swarmSize_ = 100 ; - maxIterations_ = 250 ; - archiveSize_ = 100 ; - mutationDistributionIndex_ = 20.0 ; - mutationProbability_ = 1.0/problem_->getNumberOfVariables() ; + // Default settings + swarmSize_ = 100 ; + maxIterations_ = 250 ; + archiveSize_ = 100 ; + mutationDistributionIndex_ = 20.0 ; + mutationProbability_ = 1.0/problem_->getNumberOfVariables() ; } // SMPSO_Settings @@ -60,27 +64,28 @@ SMPSO_Settings::SMPSO_Settings(string problemName) { /** * Configure method */ -Algorithm * SMPSO_Settings::configure() { +Algorithm * SMPSO_Settings::configure() +{ - algorithm = new SMPSO(problem_); - algorithm->setInputParameter("swarmSize", &swarmSize_); - algorithm->setInputParameter("maxIterations", &maxIterations_); - algorithm->setInputParameter("archiveSize", &archiveSize_); + algorithm = new SMPSO(problem_); + algorithm->setInputParameter("swarmSize", &swarmSize_); + algorithm->setInputParameter("maxIterations", &maxIterations_); + algorithm->setInputParameter("archiveSize", &archiveSize_); - map parameters; + MapOfStringFunct parameters; - double mutationProbability = mutationProbability_; - double mutationDistributionIndex = mutationDistributionIndex_; - parameters["probability"] = &mutationProbability; - parameters["distributionIndex"] = &mutationDistributionIndex; - mutation = new PolynomialMutation(parameters); + double mutationProbability = mutationProbability_; + double mutationDistributionIndex = mutationDistributionIndex_; + parameters["probability"] = &mutationProbability; + parameters["distributionIndex"] = &mutationDistributionIndex; + mutation = new PolynomialMutation(parameters); - // Add the operators to the algorithm - algorithm->addOperator("mutation",mutation); + // Add the operators to the algorithm + algorithm->addOperator("mutation",mutation); - cout << "SMPSO algorithm initialized." << endl; + std::cout << "SMPSO algorithm initialized." << std::endl; - return algorithm ; + return algorithm ; } // configure diff --git a/src/experiments/settings/SMPSO_Settings.h b/src/experiments/settings/SMPSO_Settings.h index b656e0c..9173b66 100644 --- a/src/experiments/settings/SMPSO_Settings.h +++ b/src/experiments/settings/SMPSO_Settings.h @@ -2,6 +2,7 @@ // // Author: // Esteban López-Camacho +// Sérgio Vieira // // Copyright (c) 2011 Antonio J. Nebro, Juan J. Durillo // @@ -25,24 +26,25 @@ #include #include -class SMPSO_Settings : public Settings{ +class SMPSO_Settings : public Settings +{ private: - int swarmSize_ ; - int maxIterations_ ; - int archiveSize_ ; - double mutationDistributionIndex_ ; - double mutationProbability_ ; + int swarmSize_ ; + int maxIterations_ ; + int archiveSize_ ; + double mutationDistributionIndex_ ; + double mutationProbability_ ; - Algorithm * algorithm ; - Operator * mutation ; // Mutation operator + Algorithm * algorithm ; + Operator * mutation ; // Mutation operator public: - SMPSO_Settings() ; - SMPSO_Settings(string problemName) ; - ~SMPSO_Settings() ; + SMPSO_Settings() ; + SMPSO_Settings(std::string problemName) ; + ~SMPSO_Settings() ; - Algorithm * configure() ; + Algorithm * configure() ; }; // SMPSO_Settings #endif // __SMPSO_SETTINGS__ diff --git a/src/experiments/settings/gGA_Settings.cpp b/src/experiments/settings/gGA_Settings.cpp index 4ccec2f..30ccbde 100644 --- a/src/experiments/settings/gGA_Settings.cpp +++ b/src/experiments/settings/gGA_Settings.cpp @@ -2,6 +2,7 @@ // // Author: // Esteban López-Camacho +// Sérgio Vieira // // Copyright (c) 2011 Antonio J. Nebro, Juan J. Durillo // @@ -23,72 +24,76 @@ /** * Default constructor */ -gGA_Settings::gGA_Settings () : Settings() { +gGA_Settings::gGA_Settings () : Settings() +{ } // gGA_Settings /** * Destructor */ -gGA_Settings::~gGA_Settings () { - delete algorithm ; - delete crossover ; // Crossover operator - delete mutation ; // Mutation operator - delete selection ; // Selection operator +gGA_Settings::~gGA_Settings () +{ + delete algorithm ; + delete crossover ; // Crossover operator + delete mutation ; // Mutation operator + delete selection ; // Selection operator } // ~gGA_Settings /** * Constructor */ -gGA_Settings::gGA_Settings(string problemName) { - problemName_ = problemName ; - - problem_ = ProblemFactory::getProblem((char *) problemName_.c_str()); - - // Algorithm parameters - populationSize_ = 100; - maxEvaluations_ = 25000; - mutationProbability_ = 1.0/problem_->getNumberOfVariables() ; - crossoverProbability_ = 0.9 ; - mutationDistributionIndex_ = 20.0 ; - crossoverDistributionIndex_ = 20.0 ; +gGA_Settings::gGA_Settings(std::string problemName) +{ + problemName_ = problemName ; + + problem_ = ProblemFactory::getProblem((char *) problemName_.c_str()); + + // Algorithm parameters + populationSize_ = 100; + maxEvaluations_ = 25000; + mutationProbability_ = 1.0/problem_->getNumberOfVariables() ; + crossoverProbability_ = 0.9 ; + mutationDistributionIndex_ = 20.0 ; + crossoverDistributionIndex_ = 20.0 ; } // gGA_Settings /** * Configure method */ -Algorithm * gGA_Settings::configure() { +Algorithm * gGA_Settings::configure() +{ - algorithm = new gGA(problem_); - algorithm->setInputParameter("populationSize",&populationSize_); - algorithm->setInputParameter("maxEvaluations",&maxEvaluations_); + algorithm = snew gGA(problem_); + algorithm->setInputParameter("populationSize",&populationSize_); + algorithm->setInputParameter("maxEvaluations",&maxEvaluations_); - // Mutation and Crossover for Real codification - map parameters; + // Mutation and Crossover for Real codification + MapOfStringFunct parameters; - double crossoverProbability = crossoverProbability_; - double crossoverDistributionIndex = crossoverDistributionIndex_ ; - parameters["probability"] = &crossoverProbability; - parameters["distributionIndex"] = &crossoverDistributionIndex; - crossover = new SBXCrossover(parameters); + double crossoverProbability = crossoverProbability_; + double crossoverDistributionIndex = crossoverDistributionIndex_ ; + parameters["probability"] = &crossoverProbability; + parameters["distributionIndex"] = &crossoverDistributionIndex; + crossover = snew SBXCrossover(parameters); - parameters.clear(); - double mutationProbability = mutationProbability_; - double mutationDistributionIndex = mutationDistributionIndex_; - parameters["probability"] = &mutationProbability; - parameters["distributionIndex"] = &mutationDistributionIndex; - mutation = new PolynomialMutation(parameters); + parameters.clear(); + double mutationProbability = mutationProbability_; + double mutationDistributionIndex = mutationDistributionIndex_; + parameters["probability"] = &mutationProbability; + parameters["distributionIndex"] = &mutationDistributionIndex; + mutation = snew PolynomialMutation(parameters); - // Selection Operator - parameters.clear(); - selection = new BinaryTournament2(parameters); + // Selection Operator + parameters.clear(); + selection = snew BinaryTournament2(parameters); - // Add the operators to the algorithm - algorithm->addOperator("crossover",crossover); - algorithm->addOperator("mutation",mutation); - algorithm->addOperator("selection",selection); + // Add the operators to the algorithm + algorithm->addOperator("crossover",crossover); + algorithm->addOperator("mutation",mutation); + algorithm->addOperator("selection",selection); - cout << "gGA algorithm initialized." << endl; + std::cout << "gGA algorithm initialized." << std::endl; - return algorithm ; + return algorithm ; } // configure diff --git a/src/experiments/settings/gGA_Settings.h b/src/experiments/settings/gGA_Settings.h index 76c16cf..57e9843 100644 --- a/src/experiments/settings/gGA_Settings.h +++ b/src/experiments/settings/gGA_Settings.h @@ -2,6 +2,7 @@ // // Author: // Esteban López-Camacho +// Sérgio Vieira // // Copyright (c) 2011 Antonio J. Nebro, Juan J. Durillo // @@ -27,26 +28,27 @@ #include #include -class gGA_Settings : public Settings { +class gGA_Settings : public Settings +{ private: - int populationSize_ ; - int maxEvaluations_ ; - double mutationProbability_ ; - double crossoverProbability_ ; - double mutationDistributionIndex_ ; - double crossoverDistributionIndex_ ; + int populationSize_ ; + int maxEvaluations_ ; + double mutationProbability_ ; + double crossoverProbability_ ; + double mutationDistributionIndex_ ; + double crossoverDistributionIndex_ ; - Algorithm * algorithm ; - Operator * crossover ; // Crossover operator - Operator * mutation ; // Mutation operator - Operator * selection ; // Selection operator + Algorithm * algorithm ; + Operator * crossover ; // Crossover operator + Operator * mutation ; // Mutation operator + Operator * selection ; // Selection operator public: - gGA_Settings() ; - gGA_Settings(string problemName) ; - ~gGA_Settings() ; + gGA_Settings() ; + gGA_Settings(std::string problemName) ; + ~gGA_Settings() ; - Algorithm * configure() ; + Algorithm * configure() ; }; // gGA_Settings #endif // __GGA_SETTINGS__ diff --git a/src/experiments/settings/ssGA_Settings.cpp b/src/experiments/settings/ssGA_Settings.cpp index ed1117f..6fafd93 100644 --- a/src/experiments/settings/ssGA_Settings.cpp +++ b/src/experiments/settings/ssGA_Settings.cpp @@ -2,6 +2,7 @@ // // Author: // Esteban López-Camacho +// Sérgio Vieira // // Copyright (c) 2011 Antonio J. Nebro, Juan J. Durillo // @@ -23,72 +24,76 @@ /** * Default constructor */ -ssGA_Settings::ssGA_Settings () : Settings() { +ssGA_Settings::ssGA_Settings () : Settings() +{ } // ssGA_Settings /** * Destructor */ -ssGA_Settings::~ssGA_Settings () { - delete algorithm ; - delete crossover ; // Crossover operator - delete mutation ; // Mutation operator - delete selection ; // Selection operator +ssGA_Settings::~ssGA_Settings () +{ + delete algorithm ; + delete crossover ; // Crossover operator + delete mutation ; // Mutation operator + delete selection ; // Selection operator } // ~ssGA_Settings /** * Constructor */ -ssGA_Settings::ssGA_Settings(string problemName) { - problemName_ = problemName ; - - problem_ = ProblemFactory::getProblem((char *) problemName_.c_str()); - - // Algorithm parameters - populationSize_ = 100; - maxEvaluations_ = 25000; - mutationProbability_ = 1.0/problem_->getNumberOfVariables() ; - crossoverProbability_ = 0.9 ; - mutationDistributionIndex_ = 20.0 ; - crossoverDistributionIndex_ = 20.0 ; +ssGA_Settings::ssGA_Settings(std::string problemName) +{ + problemName_ = problemName ; + + problem_ = ProblemFactory::getProblem((char *) problemName_.c_str()); + + // Algorithm parameters + populationSize_ = 100; + maxEvaluations_ = 25000; + mutationProbability_ = 1.0/problem_->getNumberOfVariables() ; + crossoverProbability_ = 0.9 ; + mutationDistributionIndex_ = 20.0 ; + crossoverDistributionIndex_ = 20.0 ; } // ssGA_Settings /** * Configure method */ -Algorithm * ssGA_Settings::configure() { +Algorithm * ssGA_Settings::configure() +{ - algorithm = new ssGA(problem_); - algorithm->setInputParameter("populationSize",&populationSize_); - algorithm->setInputParameter("maxEvaluations",&maxEvaluations_); + algorithm = new ssGA(problem_); + algorithm->setInputParameter("populationSize",&populationSize_); + algorithm->setInputParameter("maxEvaluations",&maxEvaluations_); - // Mutation and Crossover for Real codification - map parameters; + // Mutation and Crossover for Real codification + MapOfStringFunct parameters; - double crossoverProbability = crossoverProbability_; - double crossoverDistributionIndex = crossoverDistributionIndex_ ; - parameters["probability"] = &crossoverProbability; - parameters["distributionIndex"] = &crossoverDistributionIndex; - crossover = new SBXCrossover(parameters); + double crossoverProbability = crossoverProbability_; + double crossoverDistributionIndex = crossoverDistributionIndex_ ; + parameters["probability"] = &crossoverProbability; + parameters["distributionIndex"] = &crossoverDistributionIndex; + crossover = new SBXCrossover(parameters); - parameters.clear(); - double mutationProbability = mutationProbability_; - double mutationDistributionIndex = mutationDistributionIndex_; - parameters["probability"] = &mutationProbability; - parameters["distributionIndex"] = &mutationDistributionIndex; - mutation = new PolynomialMutation(parameters); + parameters.clear(); + double mutationProbability = mutationProbability_; + double mutationDistributionIndex = mutationDistributionIndex_; + parameters["probability"] = &mutationProbability; + parameters["distributionIndex"] = &mutationDistributionIndex; + mutation = new PolynomialMutation(parameters); - // Selection Operator - parameters.clear(); - selection = new BinaryTournament(parameters); + // Selection Operator + parameters.clear(); + selection = new BinaryTournament(parameters); - // Add the operators to the algorithm - algorithm->addOperator("crossover",crossover); - algorithm->addOperator("mutation",mutation); - algorithm->addOperator("selection",selection); + // Add the operators to the algorithm + algorithm->addOperator("crossover",crossover); + algorithm->addOperator("mutation",mutation); + algorithm->addOperator("selection",selection); - cout << "ssGA algorithm initialized." << endl; + std::cout << "ssGA algorithm initialized." << std::endl; - return algorithm ; + return algorithm ; } // configure diff --git a/src/experiments/settings/ssGA_Settings.h b/src/experiments/settings/ssGA_Settings.h index 1a1c3a7..fb0fc1b 100644 --- a/src/experiments/settings/ssGA_Settings.h +++ b/src/experiments/settings/ssGA_Settings.h @@ -2,6 +2,7 @@ // // Author: // Esteban López-Camacho +// Sérgio Vieira // // Copyright (c) 2011 Antonio J. Nebro, Juan J. Durillo // @@ -27,26 +28,27 @@ #include #include -class ssGA_Settings : public Settings { +class ssGA_Settings : public Settings +{ private: - int populationSize_ ; - int maxEvaluations_ ; - double mutationProbability_ ; - double crossoverProbability_ ; - double mutationDistributionIndex_ ; - double crossoverDistributionIndex_ ; + int populationSize_ ; + int maxEvaluations_ ; + double mutationProbability_ ; + double crossoverProbability_ ; + double mutationDistributionIndex_ ; + double crossoverDistributionIndex_ ; - Algorithm * algorithm ; - Operator * crossover ; // Crossover operator - Operator * mutation ; // Mutation operator - Operator * selection ; // Selection operator + Algorithm * algorithm ; + Operator * crossover ; // Crossover operator + Operator * mutation ; // Mutation operator + Operator * selection ; // Selection operator public: - ssGA_Settings() ; - ssGA_Settings(string problemName) ; - ~ssGA_Settings() ; + ssGA_Settings() ; + ssGA_Settings(string problemName) ; + ~ssGA_Settings() ; - Algorithm * configure() ; + Algorithm * configure() ; }; // ssGA_Settings #endif // __SSGA_SETTINGS__ diff --git a/src/experiments/util/CMakeLists.txt b/src/experiments/util/CMakeLists.txt new file mode 100644 index 0000000..294ec59 --- /dev/null +++ b/src/experiments/util/CMakeLists.txt @@ -0,0 +1,3 @@ +file(GLOB SOURCES "*.cpp" "*.h") +ListToString(SOURCES ";" ${SOURCES}) +LIST_APPEND("${SOURCES}") \ No newline at end of file diff --git a/src/experiments/util/FileUtils.cpp b/src/experiments/util/FileUtils.cpp index 3a6ebd3..b2fd9bd 100644 --- a/src/experiments/util/FileUtils.cpp +++ b/src/experiments/util/FileUtils.cpp @@ -2,6 +2,7 @@ // // Author: // Esteban López-Camacho +// Sérgio Vieira // // Copyright (c) 2011 Antonio J. Nebro, Juan J. Durillo // @@ -30,44 +31,56 @@ * 1: path is a folder * 2: path is a file */ -int FileUtils::existsPath(const char* path) { - int res = -1; - struct stat statbuf; - if (stat(path, &statbuf) != -1) { - if (S_ISDIR(statbuf.st_mode)) { - return 1; - } else { - return 2; +int FileUtils::existsPath(const char* path) +{ + int res = -1; + struct stat statbuf; + if (stat(path, &statbuf) != -1) + { + /* + if (S_ISDIR(statbuf.st_mode)) + { + return 1; + } + else + { + return 2; + } + */ } - } else { - return 0; - } - return res; + else + { + return 0; + } + return res; } // existsPath /** * Creates a directory in the specified path */ -int FileUtils::createDirectory(string path) { - int res; - cout << "Creating directory: " << path << endl; +int FileUtils::createDirectory(std::string path) +{ + int res; + std::cout << "Creating directory: " << path << std::endl; + + if (path.size() > 512) + res = 1; + else + { + for (int i = 0; i < path.size(); i++) + if (path[i] == '/' || i == path.size()-1) + { + std::string path2 = path.substr(0, i+1); - if (path.size() > 512) - res = 1; - else { - for (int i = 0; i <= path.size(); i++) - if (path[i] == '/' || i == path.size()-1) { - string path2 = path.substr(0, i+1); +#ifdef WINDOWS + //res = mkdir(path2.c_str()); +#else + res = mkdir(path2.c_str(), S_IRWXU | S_IRWXG | S_IRWXO); +#endif - #ifdef WINDOWS - res = mkdir(path2.c_str()); - #else - res = mkdir(path2.c_str() , S_IRWXU | S_IRWXG | S_IRWXO); - #endif + } + } - } - } - - return res; + return res; } // createDirectory diff --git a/src/experiments/util/FileUtils.h b/src/experiments/util/FileUtils.h index 3977fe8..c1abc72 100644 --- a/src/experiments/util/FileUtils.h +++ b/src/experiments/util/FileUtils.h @@ -2,6 +2,7 @@ // // Author: // Esteban López-Camacho +// Sérgio Vieira // // Copyright (c) 2011 Antonio J. Nebro, Juan J. Durillo // @@ -19,9 +20,9 @@ // along with this program. If not, see . #ifdef WIN32 - #define WINDOWS +#define WINDOWS #elif WIN64 - #define WINDOWS +#define WINDOWS #endif #ifndef __FILEUTILS__ @@ -32,17 +33,18 @@ #include #ifdef WINDOWS - #include +//#include #endif -using namespace std; -class FileUtils { + +class FileUtils +{ public: - static int existsPath(const char* path); - static int createDirectory(string path); + static int existsPath(const char* path); + static int createDirectory(std::string path); }; //FileUtils diff --git a/src/experiments/util/RBoxplot.cpp b/src/experiments/util/RBoxplot.cpp index 689d8f0..ea52260 100644 --- a/src/experiments/util/RBoxplot.cpp +++ b/src/experiments/util/RBoxplot.cpp @@ -2,6 +2,7 @@ // // Author: // Esteban López-Camacho +// Sérgio Vieira // // Copyright (c) 2011 Antonio J. Nebro, Juan J. Durillo // @@ -21,74 +22,84 @@ #include -void RBoxplot::generateScripts(int rows, int cols, vector problems, string prefix, - bool notch, ExperimentReport * experiment) { - - // STEP 1. Creating R output directory - - string rDirectory = "R"; - rDirectory = experiment->experimentBaseDirectory_ + "/" + rDirectory; - cout << "R : " << rDirectory << endl; - if (FileUtils::existsPath(rDirectory.c_str()) == 0) { - FileUtils::createDirectory(rDirectory); - cout << "Creating " << rDirectory << " directory" << endl; - } - - for (int indicator = 0; indicator < experiment->indicatorList_.size(); indicator++) { - cout << "Indicator: " << experiment->indicatorList_[indicator] << endl; - string rFile = rDirectory + "/" + prefix + "." + experiment->indicatorList_[indicator] + ".Boxplot.R"; - - std::ofstream out(rFile.c_str()); - out << "postscript(\"" << prefix << "." << experiment->indicatorList_[indicator] << - ".Boxplot.eps\", horizontal=FALSE, onefile=FALSE, height=8, width=12, pointsize=10)" << - endl; - //out << "resultDirectory<-\"../data/" << experimentName_ << "\"" << endl; - out << "resultDirectory<-\"../data/" << "\"" << endl; - out << "qIndicator <- function(indicator, problem)" << endl; - out << "{" << endl; - - for (int i = 0; i < experiment->algorithmNameList_.size(); i++) { - out << "file" << experiment->algorithmNameList_[i] << "<-paste(resultDirectory, \"" << - experiment->algorithmNameList_[i] << "\", sep=\"/\")" << endl; - out << "file" << experiment->algorithmNameList_[i] << "<-paste(file" << - experiment->algorithmNameList_[i] << ", " << "problem, sep=\"/\")" << endl; - out << "file" << experiment->algorithmNameList_[i] << "<-paste(file" << - experiment->algorithmNameList_[i] << ", " << "indicator, sep=\"/\")" << endl; - out << experiment->algorithmNameList_[i] << "<-scan(" << "file" << - experiment->algorithmNameList_[i] << ")" << endl; - out << endl; - } // for +void RBoxplot::generateScripts(int rows, int cols, VectorOfString problems, std::string prefix, + bool notch, ExperimentReport * experiment) +{ - out << "algs<-c("; - for (int i = 0; i < experiment->algorithmNameList_.size() - 1; i++) { - out << "\"" << experiment->algorithmNameList_[i] << "\","; - } // for - out << "\"" << experiment->algorithmNameList_[ experiment->algorithmNameList_.size() - 1] << - "\")" << endl; + // STEP 1. Creating R output directory - out << "boxplot("; - for (int i = 0; i < experiment->algorithmNameList_.size(); i++) { - out << experiment->algorithmNameList_[i] << ","; - } // for - if (notch) { - out << "names=algs, notch = TRUE)" << endl; - } else { - out << "names=algs, notch = FALSE)" << endl; + std::string rDirectory = "R"; + rDirectory = experiment->experimentBaseDirectory_ + "/" + rDirectory; + std::cout << "R : " << rDirectory << std::endl; + if (FileUtils::existsPath(rDirectory.c_str()) == 0) + { + FileUtils::createDirectory(rDirectory); + std::cout << "Creating " << rDirectory << " directory" << std::endl; } - out << "titulo <-paste(indicator, problem, sep=\":\")" << endl; - out << "title(main=titulo)" << endl; - - out << "}" << endl; - - out << "par(mfrow=c(" << rows << "," << cols << "))" << endl; - out << "indicator<-\"" << experiment->indicatorList_[indicator] << "\"" << endl; - - for (int i = 0; i < problems.size(); i++) { - out << "qIndicator(indicator, \"" << problems[i] << "\")" << endl; - } - - out.close(); - } // for + for (int indicator = 0; indicator < experiment->indicatorList_.size(); indicator++) + { + std::cout << "Indicator: " << experiment->indicatorList_[indicator] << std::endl; + std::string rFile = rDirectory + "/" + prefix + "." + experiment->indicatorList_[indicator] + ".Boxplot.R"; + + std::ofstream out(rFile.c_str()); + out << "postscript(\"" << prefix << "." << experiment->indicatorList_[indicator] << + ".Boxplot.eps\", horizontal=FALSE, onefile=FALSE, height=8, width=12, pointsize=10)" << + std::endl; + //out << "resultDirectory<-\"../data/" << experimentName_ << "\"" << std::endl; + out << "resultDirectory<-\"../data/" << "\"" << std::endl; + out << "qIndicator <- function(indicator, problem)" << std::endl; + out << "{" << std::endl; + + for (int i = 0; i < experiment->algorithmNameList_.size(); i++) + { + out << "file" << experiment->algorithmNameList_[i] << "<-paste(resultDirectory, \"" << + experiment->algorithmNameList_[i] << "\", sep=\"/\")" << std::endl; + out << "file" << experiment->algorithmNameList_[i] << "<-paste(file" << + experiment->algorithmNameList_[i] << ", " << "problem, sep=\"/\")" << std::endl; + out << "file" << experiment->algorithmNameList_[i] << "<-paste(file" << + experiment->algorithmNameList_[i] << ", " << "indicator, sep=\"/\")" << std::endl; + out << experiment->algorithmNameList_[i] << "<-scan(" << "file" << + experiment->algorithmNameList_[i] << ")" << std::endl; + out << std::endl; + } // for + + out << "algs<-c("; + for (int i = 0; i < experiment->algorithmNameList_.size() - 1; i++) + { + out << "\"" << experiment->algorithmNameList_[i] << "\","; + } // for + out << "\"" << experiment->algorithmNameList_[ experiment->algorithmNameList_.size() - 1] << + "\")" << std::endl; + + out << "boxplot("; + for (int i = 0; i < experiment->algorithmNameList_.size(); i++) + { + out << experiment->algorithmNameList_[i] << ","; + } // for + if (notch) + { + out << "names=algs, notch = TRUE)" << std::endl; + } + else + { + out << "names=algs, notch = FALSE)" << std::endl; + } + out << "titulo <-paste(indicator, problem, sep=\":\")" << std::endl; + out << "title(main=titulo)" << std::endl; + + out << "}" << std::endl; + + out << "par(mfrow=c(" << rows << "," << cols << "))" << std::endl; + + out << "indicator<-\"" << experiment->indicatorList_[indicator] << "\"" << std::endl; + + for (int i = 0; i < problems.size(); i++) + { + out << "qIndicator(indicator, \"" << problems[i] << "\")" << std::endl; + } + + out.close(); + } // for } // generateScripts diff --git a/src/experiments/util/RBoxplot.h b/src/experiments/util/RBoxplot.h index e0c6fc2..0307ee6 100644 --- a/src/experiments/util/RBoxplot.h +++ b/src/experiments/util/RBoxplot.h @@ -2,6 +2,7 @@ // // Author: // Esteban López-Camacho +// Sérgio Vieira // // Copyright (c) 2011 Antonio J. Nebro, Juan J. Durillo // @@ -21,20 +22,23 @@ #ifndef __RBOXPLOT__ #define __RBOXPLOT__ -#include +#include "JMetalHeader.h" #include #include +using namespace JMetal; + class ExperimentReport; /** * Class for generating results in form of boxplots */ -class RBoxplot { +class RBoxplot +{ public: - static void generateScripts(int rows, int cols, vector problems, - string prefix, bool notch, ExperimentReport * experiment); + static void generateScripts(int rows, int cols, VectorOfString problems, + std::string prefix, bool notch, ExperimentReport * experiment); }; #endif /* __RBOXPLOT__ */ diff --git a/src/experiments/util/RWilcoxon.cpp b/src/experiments/util/RWilcoxon.cpp index 602b770..4361dc3 100644 --- a/src/experiments/util/RWilcoxon.cpp +++ b/src/experiments/util/RWilcoxon.cpp @@ -2,6 +2,7 @@ // // Author: // Esteban López-Camacho +// Sérgio Vieira // // Copyright (c) 2011 Antonio J. Nebro, Juan J. Durillo // @@ -22,300 +23,312 @@ #include -void RWilcoxon::generateScripts(vector problems, string prefix, ExperimentReport * experiment) { +void RWilcoxon::generateScripts(VectorOfString problems, std::string prefix, ExperimentReport * experiment) +{ - // STEP 1. Creating R output directory + // STEP 1. Creating R output directory - string rDirectory = "R"; - rDirectory = experiment->experimentBaseDirectory_ + "/" + rDirectory; - cout << "R : " << rDirectory << endl; - if (FileUtils::existsPath(rDirectory.c_str()) == 0) { - FileUtils::createDirectory(rDirectory); - cout << "Creating " << rDirectory << " directory" << endl; - } + std::string rDirectory = "R"; + rDirectory = experiment->experimentBaseDirectory_ + "/" + rDirectory; + std::cout << "R : " << rDirectory << std::endl; + if (FileUtils::existsPath(rDirectory.c_str()) == 0) + { + FileUtils::createDirectory(rDirectory); + std::cout << "Creating " << rDirectory << " directory" << std::endl; + } - for (int indicator = 0; indicator < experiment->indicatorList_.size(); indicator++) { - cout << "Indicator: " << experiment->indicatorList_[indicator] << endl; - string rFile = rDirectory + "/" + prefix + "." + experiment->indicatorList_[indicator] + ".Wilcox.R"; - string texFile = rDirectory + "/" + prefix + "." + experiment->indicatorList_[indicator] + ".Wilcox.tex"; + for (int indicator = 0; indicator < experiment->indicatorList_.size(); indicator++) + { + std::cout << "Indicator: " << experiment->indicatorList_[indicator] << std::endl; + std::string rFile = rDirectory + "/" + prefix + "." + experiment->indicatorList_[indicator] + ".Wilcox.R"; + std::string texFile = rDirectory + "/" + prefix + "." + experiment->indicatorList_[indicator] + ".Wilcox.tex"; - std::ofstream out(rFile.c_str()); - string output = "write(\"\", \"" + texFile + "\",append=FALSE)"; - out << output << endl; + std::ofstream out(rFile.c_str()); + std::string output = "write(\"\", \"" + texFile + "\",append=FALSE)"; + out << output << std::endl; - // Generate function latexHeader() - string dataDirectory = experiment->experimentBaseDirectory_ + "/data"; - out << "resultDirectory<-\"" << dataDirectory << "\"" << endl; - out << "latexHeader <- function() {" << endl; - out << " write(\"\\\\documentclass{article}\", \"" + texFile + "\", append=TRUE)" << endl; - out << " write(\"\\\\title{StandardStudy}\", \"" + texFile + "\", append=TRUE)" << endl; - out << " write(\"\\\\usepackage{amssymb}\", \"" + texFile + "\", append=TRUE)" << endl; - out << " write(\"\\\\author{A.J.Nebro}\", \"" + texFile + "\", append=TRUE)" << endl; - out << " write(\"\\\\begin{document}\", \"" + texFile + "\", append=TRUE)" << endl; - out << " write(\"\\\\maketitle\", \"" + texFile + "\", append=TRUE)" << endl; - out << " write(\"\\\\section{Tables}\", \"" + texFile + "\", append=TRUE)" << endl; - out << " write(\"\\\\\", \"" + texFile + "\", append=TRUE)\n}" << endl; - //out << output << endl; + // Generate function latexHeader() + std::string dataDirectory = experiment->experimentBaseDirectory_ + "/data"; + out << "resultDirectory<-\"" << dataDirectory << "\"" << std::endl; + out << "latexHeader <- function() {" << std::endl; + out << " write(\"\\\\documentclass{article}\", \"" + texFile + "\", append=TRUE)" << std::endl; + out << " write(\"\\\\title{StandardStudy}\", \"" + texFile + "\", append=TRUE)" << std::endl; + out << " write(\"\\\\usepackage{amssymb}\", \"" + texFile + "\", append=TRUE)" << std::endl; + out << " write(\"\\\\author{A.J.Nebro}\", \"" + texFile + "\", append=TRUE)" << std::endl; + out << " write(\"\\\\begin{document}\", \"" + texFile + "\", append=TRUE)" << std::endl; + out << " write(\"\\\\maketitle\", \"" + texFile + "\", append=TRUE)" << std::endl; + out << " write(\"\\\\section{Tables}\", \"" + texFile + "\", append=TRUE)" << std::endl; + out << " write(\"\\\\\", \"" + texFile + "\", append=TRUE)\n}" << std::endl; + //out << output << std::endl; - // Write function latexTableHeader - string latexTableLabel = ""; - string latexTabularAlignment = ""; - string latexTableFirstLine = ""; - string latexTableCaption = ""; + // Write function latexTableHeader + std::string latexTableLabel = ""; + std::string latexTabularAlignment = ""; + std::string latexTableFirstLine = ""; + std::string latexTableCaption = ""; - latexTableCaption = " write(\"\\\\caption{\", \"" + texFile + "\", append=TRUE)" + "\n" + - " write(problem, \"" + texFile + "\", append=TRUE)" + "\n" + - " write(\"." + experiment->indicatorList_[indicator] + ".}\", \"" + texFile + "\", append=TRUE)" + "\n"; - latexTableLabel = " write(\"\\\\label{Table:\", \"" + texFile + "\", append=TRUE)" + "\n" + - " write(problem, \"" + texFile + "\", append=TRUE)" + "\n" + - " write(\"." + experiment->indicatorList_[indicator] + ".}\", \"" + texFile + "\", append=TRUE)" + "\n"; - latexTabularAlignment = "l"; - latexTableFirstLine = "\\\\hline "; + latexTableCaption = " write(\"\\\\caption{\", \"" + texFile + "\", append=TRUE)" + "\n" + + " write(problem, \"" + texFile + "\", append=TRUE)" + "\n" + + " write(\"." + experiment->indicatorList_[indicator] + ".}\", \"" + texFile + "\", append=TRUE)" + "\n"; + latexTableLabel = " write(\"\\\\label{Table:\", \"" + texFile + "\", append=TRUE)" + "\n" + + " write(problem, \"" + texFile + "\", append=TRUE)" + "\n" + + " write(\"." + experiment->indicatorList_[indicator] + ".}\", \"" + texFile + "\", append=TRUE)" + "\n"; + latexTabularAlignment = "l"; + latexTableFirstLine = "\\\\hline "; - for (int i = 1; i < experiment->algorithmNameList_.size(); i++) { - latexTabularAlignment += "c"; - latexTableFirstLine += " & " + experiment->algorithmNameList_[i]; - } // for - //latexTableFirstLine += "\\\\\\\\\",\"" + texFile + "\", append=TRUE)" + "\n"; - latexTableFirstLine += "\\\\\\\\ \""; + for (int i = 1; i < experiment->algorithmNameList_.size(); i++) + { + latexTabularAlignment += "c"; + latexTableFirstLine += " & " + experiment->algorithmNameList_[i]; + } // for + //latexTableFirstLine += "\\\\\\\\\",\"" + texFile + "\", append=TRUE)" + "\n"; + latexTableFirstLine += "\\\\\\\\ \""; - // Generate function latexTableHeader() - out << "latexTableHeader <- function(problem, tabularString, latexTableFirstLine) {" << endl; - out << " write(\"\\\\begin{table}\", \"" + texFile + "\", append=TRUE)" << endl; - out << latexTableCaption << endl; - out << latexTableLabel << endl; - out << " write(\"\\\\centering\", \"" + texFile + "\", append=TRUE)" << endl; - out << " write(\"\\\\begin{scriptsize}\", \"" + texFile + "\", append=TRUE)" << endl; - //out << " write(\"\\\\begin{tabular}{" + latexTabularAlignment + "}\", \"" + texFile + "\", append=TRUE)" << endl; - out << " write(\"\\\\begin{tabular}{\", \"" + texFile + "\", append=TRUE)" << endl; - out << " write(tabularString, \"" + texFile + "\", append=TRUE)" << endl; - out << " write(\"}\", \"" + texFile + "\", append=TRUE)" << endl; - //out << latexTableFirstLine + - out << " write(latexTableFirstLine, \"" + texFile + "\", append=TRUE)" << endl; - out << " write(\"\\\\hline \", \"" + texFile + "\", append=TRUE)" + "\n" + "}" << endl; - //out << output << endl; + // Generate function latexTableHeader() + out << "latexTableHeader <- function(problem, tabularString, latexTableFirstLine) {" << std::endl; + out << " write(\"\\\\begin{table}\", \"" + texFile + "\", append=TRUE)" << std::endl; + out << latexTableCaption << std::endl; + out << latexTableLabel << std::endl; + out << " write(\"\\\\centering\", \"" + texFile + "\", append=TRUE)" << std::endl; + out << " write(\"\\\\begin{scriptsize}\", \"" + texFile + "\", append=TRUE)" << std::endl; + //out << " write(\"\\\\begin{tabular}{" + latexTabularAlignment + "}\", \"" + texFile + "\", append=TRUE)" << std::endl; + out << " write(\"\\\\begin{tabular}{\", \"" + texFile + "\", append=TRUE)" << std::endl; + out << " write(tabularString, \"" + texFile + "\", append=TRUE)" << std::endl; + out << " write(\"}\", \"" + texFile + "\", append=TRUE)" << std::endl; + //out << latexTableFirstLine + + out << " write(latexTableFirstLine, \"" + texFile + "\", append=TRUE)" << std::endl; + out << " write(\"\\\\hline \", \"" + texFile + "\", append=TRUE)" + "\n" + "}" << std::endl; + //out << output << std::endl; - // Generate function latexTableTail() - out << "latexTableTail <- function() { " << endl; - out << " write(\"\\\\hline\", \"" + texFile + "\", append=TRUE)" << endl; - out << " write(\"\\\\end{tabular}\", \"" + texFile + "\", append=TRUE)" << endl; - out << " write(\"\\\\end{scriptsize}\", \"" + texFile + "\", append=TRUE)" << endl; - out << " write(\"\\\\end{table}\", \"" + texFile + "\", append=TRUE)" + "\n" + "}" << endl; - //out << output << endl; + // Generate function latexTableTail() + out << "latexTableTail <- function() { " << std::endl; + out << " write(\"\\\\hline\", \"" + texFile + "\", append=TRUE)" << std::endl; + out << " write(\"\\\\end{tabular}\", \"" + texFile + "\", append=TRUE)" << std::endl; + out << " write(\"\\\\end{scriptsize}\", \"" + texFile + "\", append=TRUE)" << std::endl; + out << " write(\"\\\\end{table}\", \"" + texFile + "\", append=TRUE)" + "\n" + "}" << std::endl; + //out << output << std::endl; - // Generate function latexTail() - out << "latexTail <- function() { " << endl; - out << " write(\"\\\\end{document}\", \"" + texFile + "\", append=TRUE)" + "\n" + "}" << endl; - //out << output << endl; + // Generate function latexTail() + out << "latexTail <- function() { " << std::endl; + out << " write(\"\\\\end{document}\", \"" + texFile + "\", append=TRUE)" + "\n" + "}" << std::endl; + //out << output << std::endl; - if ((bool) experiment->indicatorMinimize_[experiment->indicatorList_[indicator]] == true) {// minimize by default - // Generate function printTableLine() - out << "printTableLine <- function(indicator, algorithm1, algorithm2, i, j, problem) { " << endl; - out << " file1<-paste(resultDirectory, algorithm1, sep=\"/\")" << endl; - out << " file1<-paste(file1, problem, sep=\"/\")" << endl; - out << " file1<-paste(file1, indicator, sep=\"/\")" << endl; - out << " data1<-scan(file1)" << endl; - out << " file2<-paste(resultDirectory, algorithm2, sep=\"/\")" << endl; - out << " file2<-paste(file2, problem, sep=\"/\")" << endl; - out << " file2<-paste(file2, indicator, sep=\"/\")" << endl; - out << " data2<-scan(file2)" << endl; - out << " if (i == j) {" << endl; - out << " write(\"-- \", \"" + texFile + "\", append=TRUE)" << endl; - out << " }" << endl; - out << " else if (i < j) {" << endl; - out << " if (wilcox.test(data1, data2)$p.value <= 0.05) {" << endl; - out << " if (median(data1) <= median(data2)) {" << endl; - out << " write(\"$\\\\blacktriangle$\", \"" + texFile + "\", append=TRUE)" << endl; - out << " }" << endl; - out << " else {" << endl; - out << " write(\"$\\\\triangledown$\", \"" + texFile + "\", append=TRUE) " << endl; - out << " }" << endl; - out << " }" << endl; - out << " else {" << endl; - out << " write(\"--\", \"" + texFile + "\", append=TRUE) " << endl; - out << " }" << endl; - out << " }" << endl; - out << " else {" << endl; - out << " write(\" \", \"" + texFile + "\", append=TRUE)" << endl; - out << " }" << endl; - out << "}" << endl; - } // if - else { - // Generate function printTableLine() - out << "printTableLine <- function(indicator, algorithm1, algorithm2, i, j, problem) { " << endl; - out << " file1<-paste(resultDirectory, algorithm1, sep=\"/\")" << endl; - out << " file1<-paste(file1, problem, sep=\"/\")" << endl; - out << " file1<-paste(file1, indicator, sep=\"/\")" << endl; - out << " data1<-scan(file1)" << endl; - out << " file2<-paste(resultDirectory, algorithm2, sep=\"/\")" << endl; - out << " file2<-paste(file2, problem, sep=\"/\")" << endl; - out << " file2<-paste(file2, indicator, sep=\"/\")" << endl; - out << " data2<-scan(file2)" << endl; - out << " if (i == j) {" << endl; - out << " write(\"--\", \"" + texFile + "\", append=TRUE)" << endl; - out << " }" << endl; - out << " else if (i < j) {" << endl; - out << " if (wilcox.test(data1, data2)$p.value <= 0.05) {" << endl; - out << " if (median(data1) >= median(data2)) {" << endl; - out << " write(\"$\\\\blacktriangle$\", \"" + texFile + "\", append=TRUE)" << endl; - out << " }" << endl; - out << " else {" << endl; - out << " write(\"$\\\\triangledown$\", \"" + texFile + "\", append=TRUE) " << endl; - out << " }" << endl; - out << " }" << endl; - out << " else {" << endl; - out << " write(\"--\", \"" + texFile + "\", append=TRUE) " << endl; - out << " }" << endl; - out << " }" << endl; - out << " else {" << endl; - out << " write(\" \", \"" + texFile + "\", append=TRUE)" << endl; - out << " }" << endl; - out << "}" << endl; - } - //out << output << endl; + if ((bool) experiment->indicatorMinimize_[experiment->indicatorList_[indicator]] == true) // minimize by default + { + // Generate function printTableLine() + out << "printTableLine <- function(indicator, algorithm1, algorithm2, i, j, problem) { " << std::endl; + out << " file1<-paste(resultDirectory, algorithm1, sep=\"/\")" << std::endl; + out << " file1<-paste(file1, problem, sep=\"/\")" << std::endl; + out << " file1<-paste(file1, indicator, sep=\"/\")" << std::endl; + out << " data1<-scan(file1)" << std::endl; + out << " file2<-paste(resultDirectory, algorithm2, sep=\"/\")" << std::endl; + out << " file2<-paste(file2, problem, sep=\"/\")" << std::endl; + out << " file2<-paste(file2, indicator, sep=\"/\")" << std::endl; + out << " data2<-scan(file2)" << std::endl; + out << " if (i == j) {" << std::endl; + out << " write(\"-- \", \"" + texFile + "\", append=TRUE)" << std::endl; + out << " }" << std::endl; + out << " else if (i < j) {" << std::endl; + out << " if (wilcox.test(data1, data2)$p.value <= 0.05) {" << std::endl; + out << " if (median(data1) <= median(data2)) {" << std::endl; + out << " write(\"$\\\\blacktriangle$\", \"" + texFile + "\", append=TRUE)" << std::endl; + out << " }" << std::endl; + out << " else {" << std::endl; + out << " write(\"$\\\\triangledown$\", \"" + texFile + "\", append=TRUE) " << std::endl; + out << " }" << std::endl; + out << " }" << std::endl; + out << " else {" << std::endl; + out << " write(\"--\", \"" + texFile + "\", append=TRUE) " << std::endl; + out << " }" << std::endl; + out << " }" << std::endl; + out << " else {" << std::endl; + out << " write(\" \", \"" + texFile + "\", append=TRUE)" << std::endl; + out << " }" << std::endl; + out << "}" << std::endl; + } // if + else + { + // Generate function printTableLine() + out << "printTableLine <- function(indicator, algorithm1, algorithm2, i, j, problem) { " << std::endl; + out << " file1<-paste(resultDirectory, algorithm1, sep=\"/\")" << std::endl; + out << " file1<-paste(file1, problem, sep=\"/\")" << std::endl; + out << " file1<-paste(file1, indicator, sep=\"/\")" << std::endl; + out << " data1<-scan(file1)" << std::endl; + out << " file2<-paste(resultDirectory, algorithm2, sep=\"/\")" << std::endl; + out << " file2<-paste(file2, problem, sep=\"/\")" << std::endl; + out << " file2<-paste(file2, indicator, sep=\"/\")" << std::endl; + out << " data2<-scan(file2)" << std::endl; + out << " if (i == j) {" << std::endl; + out << " write(\"--\", \"" + texFile + "\", append=TRUE)" << std::endl; + out << " }" << std::endl; + out << " else if (i < j) {" << std::endl; + out << " if (wilcox.test(data1, data2)$p.value <= 0.05) {" << std::endl; + out << " if (median(data1) >= median(data2)) {" << std::endl; + out << " write(\"$\\\\blacktriangle$\", \"" + texFile + "\", append=TRUE)" << std::endl; + out << " }" << std::endl; + out << " else {" << std::endl; + out << " write(\"$\\\\triangledown$\", \"" + texFile + "\", append=TRUE) " << std::endl; + out << " }" << std::endl; + out << " }" << std::endl; + out << " else {" << std::endl; + out << " write(\"--\", \"" + texFile + "\", append=TRUE) " << std::endl; + out << " }" << std::endl; + out << " }" << std::endl; + out << " else {" << std::endl; + out << " write(\" \", \"" + texFile + "\", append=TRUE)" << std::endl; + out << " }" << std::endl; + out << "}" << std::endl; + } + //out << output << std::endl; - // Start of the R script - output = "### START OF SCRIPT "; - out << output << endl; + // Start of the R script + output = "### START OF SCRIPT "; + out << output << std::endl; - string problemList = "problemList <-c("; - string algorithmList = "algorithmList <-c("; + std::string problemList = "problemList <-c("; + std::string algorithmList = "algorithmList <-c("; - for (int i = 0; i < (problems.size() - 1); i++) { - problemList += "\"" + problems[i] + "\", "; - } - problemList += "\"" + problems[problems.size() - 1] + "\") "; + for (int i = 0; i < (problems.size() - 1); i++) + { + problemList += "\"" + problems[i] + "\", "; + } + problemList += "\"" + problems[problems.size() - 1] + "\") "; - for (int i = 0; i < (experiment->algorithmNameList_.size() - 1); i++) { - algorithmList += "\"" + experiment->algorithmNameList_[i] + "\", "; - } - algorithmList += "\"" + experiment->algorithmNameList_[experiment->algorithmNameList_.size() - 1] + "\") "; + for (int i = 0; i < (experiment->algorithmNameList_.size() - 1); i++) + { + algorithmList += "\"" + experiment->algorithmNameList_[i] + "\", "; + } + algorithmList += "\"" + experiment->algorithmNameList_[experiment->algorithmNameList_.size() - 1] + "\") "; - latexTabularAlignment = "l"; - for (int i = 1; i < experiment->algorithmNameList_.size(); i++) { - latexTabularAlignment += "c"; - } // for - string tabularString = "tabularString <-c(\""+ latexTabularAlignment + "\") "; - string tableFirstLine = "latexTableFirstLine <-c(\"" + latexTableFirstLine + ") "; + latexTabularAlignment = "l"; + for (int i = 1; i < experiment->algorithmNameList_.size(); i++) + { + latexTabularAlignment += "c"; + } // for + std::string tabularString = "tabularString <-c(\""+ latexTabularAlignment + "\") "; + std::string tableFirstLine = "latexTableFirstLine <-c(\"" + latexTableFirstLine + ") "; - output = "# Constants\n" + - problemList + "\n" + - algorithmList + "\n" + - tabularString + "\n" + - tableFirstLine + "\n" + - "indicator<-\"" + experiment->indicatorList_[indicator] + "\""; - out << output << endl; + output = "# Constants\n" + + problemList + "\n" + + algorithmList + "\n" + + tabularString + "\n" + + tableFirstLine + "\n" + + "indicator<-\"" + experiment->indicatorList_[indicator] + "\""; + out << output << std::endl; - out << "\n# Step 1. Writes the latex header" << endl; - out << "latexHeader()" << endl << endl;; - //out << output << endl; + out << "\n# Step 1. Writes the latex header" << std::endl; + out << "latexHeader()" << std::endl << std::endl;; + //out << output << std::endl; - // Generate tables per problem - out << "# Step 2. Problem loop" << endl; - out << "for (problem in problemList) {" << endl; - out << " latexTableHeader(problem, tabularString, latexTableFirstLine)" << endl << endl; - out << " indx = 0" << endl; - out << " for (i in algorithmList) {" << endl; - out << " if (i != \"" + experiment->algorithmNameList_[experiment->algorithmNameList_.size() - 1]+ "\") {" << endl; - out << " write(i , \"" + texFile + "\", append=TRUE)" << endl; - out << " write(\" & \", \"" + texFile + "\", append=TRUE)" << endl; - out << " jndx = 0 " << endl; - out << " for (j in algorithmList) {" << endl; - out << " if (jndx != 0) {" << endl; - out << " if (indx != jndx) {" << endl; - out << " printTableLine(indicator, i, j, indx, jndx, problem)" << endl; - out << " }" << endl; - out << " else {" << endl; - out << " write(\" \", \"" + texFile + "\", append=TRUE)" << endl; - out << " }" << endl; - out << " if (j != \"" + experiment->algorithmNameList_[experiment->algorithmNameList_.size() - 1] + "\") {" << endl; - out << " write(\" & \", \"" + texFile + "\", append=TRUE)" << endl; - out << " }" << endl; - out << " else {" << endl; - out << " write(\" \\\\\\\\ \", \"" + texFile + "\", append=TRUE)" << endl; - out << " }" << endl; - out << " }" << endl; - out << " jndx = jndx + 1" << endl; - out << " }" << endl; - out << " indx = indx + 1" << endl; - out << " }" << endl; - out << " }" << endl << endl; - out << " latexTableTail()" << endl; - out << "} # for problem" << endl; - //out << output << endl; + // Generate tables per problem + out << "# Step 2. Problem loop" << std::endl; + out << "for (problem in problemList) {" << std::endl; + out << " latexTableHeader(problem, tabularString, latexTableFirstLine)" << std::endl << std::endl; + out << " indx = 0" << std::endl; + out << " for (i in algorithmList) {" << std::endl; + out << " if (i != \"" + experiment->algorithmNameList_[experiment->algorithmNameList_.size() - 1]+ "\") {" << std::endl; + out << " write(i , \"" + texFile + "\", append=TRUE)" << std::endl; + out << " write(\" & \", \"" + texFile + "\", append=TRUE)" << std::endl; + out << " jndx = 0 " << std::endl; + out << " for (j in algorithmList) {" << std::endl; + out << " if (jndx != 0) {" << std::endl; + out << " if (indx != jndx) {" << std::endl; + out << " printTableLine(indicator, i, j, indx, jndx, problem)" << std::endl; + out << " }" << std::endl; + out << " else {" << std::endl; + out << " write(\" \", \"" + texFile + "\", append=TRUE)" << std::endl; + out << " }" << std::endl; + out << " if (j != \"" + experiment->algorithmNameList_[experiment->algorithmNameList_.size() - 1] + "\") {" << std::endl; + out << " write(\" & \", \"" + texFile + "\", append=TRUE)" << std::endl; + out << " }" << std::endl; + out << " else {" << std::endl; + out << " write(\" \\\\\\\\ \", \"" + texFile + "\", append=TRUE)" << std::endl; + out << " }" << std::endl; + out << " }" << std::endl; + out << " jndx = jndx + 1" << std::endl; + out << " }" << std::endl; + out << " indx = indx + 1" << std::endl; + out << " }" << std::endl; + out << " }" << std::endl << std::endl; + out << " latexTableTail()" << std::endl; + out << "} # for problem" << std::endl; + //out << output << std::endl; - // Generate full table - problemList = ""; - for (int i = 0; i < problems.size(); i++) { - problemList += problems[i] + " "; - } - // The tabular environment and the latexTableFirstLine variable must be redefined - stringstream ssLatexTableFirstLine; - latexTabularAlignment = "| l | "; - ssLatexTableFirstLine << "\\\\hline \\\\multicolumn{1}{|c|}{}"; - for (int i = 1; i < experiment->algorithmNameList_.size(); i++) { - for (int j = 0; j < problems.size(); j++) { - latexTabularAlignment += "p{0.15cm} "; - //latexTabularAlignment += "c "; - } // for - ssLatexTableFirstLine << " & \\\\multicolumn{" << problems.size() << "}{c|}{" - << experiment->algorithmNameList_[i] << "}"; - latexTabularAlignment += " | " ; - } // for - ssLatexTableFirstLine << " \\\\\\\\"; - latexTableFirstLine = ssLatexTableFirstLine.str(); + // Generate full table + problemList = ""; + for (int i = 0; i < problems.size(); i++) + { + problemList += problems[i] + " "; + } + // The tabular environment and the latexTableFirstLine variable must be redefined + stringstream ssLatexTableFirstLine; + latexTabularAlignment = "| l | "; + ssLatexTableFirstLine << "\\\\hline \\\\multicolumn{1}{|c|}{}"; + for (int i = 1; i < experiment->algorithmNameList_.size(); i++) + { + for (int j = 0; j < problems.size(); j++) + { + latexTabularAlignment += "p{0.15cm} "; + //latexTabularAlignment += "c "; + } // for + ssLatexTableFirstLine << " & \\\\multicolumn{" << problems.size() << "}{c|}{" + << experiment->algorithmNameList_[i] << "}"; + latexTabularAlignment += " | " ; + } // for + ssLatexTableFirstLine << " \\\\\\\\"; + latexTableFirstLine = ssLatexTableFirstLine.str(); - tabularString = "tabularString <-c(\""+ latexTabularAlignment + "\") "; - latexTableFirstLine = "latexTableFirstLine <-c(\""+ latexTableFirstLine + "\") "; + tabularString = "tabularString <-c(\""+ latexTabularAlignment + "\") "; + latexTableFirstLine = "latexTableFirstLine <-c(\""+ latexTableFirstLine + "\") "; - output = tabularString; - out << output + "\n" << endl; - output = latexTableFirstLine ; - out << output + "\n" << endl; + output = tabularString; + out << output + "\n" << std::endl; + output = latexTableFirstLine ; + out << output + "\n" << std::endl; - out << "# Step 3. Problem loop" << endl; - out << "latexTableHeader(\"" + problemList + "\", tabularString, latexTableFirstLine)" << endl << endl; - out << "indx = 0" << endl; - out << "for (i in algorithmList) {" << endl; - out << " if (i != \"" + experiment->algorithmNameList_[experiment->algorithmNameList_.size() - 1]+ "\") {" << endl; - out << " write(i , \"" + texFile + "\", append=TRUE)" << endl; - out << " write(\" & \", \"" + texFile + "\", append=TRUE)" << endl << endl; - out << " jndx = 0" << endl; - out << " for (j in algorithmList) {" << endl; - out << " for (problem in problemList) {" << endl; - out << " if (jndx != 0) {" << endl; - out << " if (i != j) {" << endl; - out << " printTableLine(indicator, i, j, indx, jndx, problem)" << endl; - out << " }" << endl; - out << " else {" << endl; - out << " write(\" \", \"" + texFile + "\", append=TRUE)" << endl; - out << " } " << endl; - out << " if (problem == \"" + problems[problems.size() - 1] + "\") {" << endl; - out << " if (j == \"" + experiment->algorithmNameList_[experiment->algorithmNameList_.size() - 1] + "\") {" << endl; - out << " write(\" \\\\\\\\ \", \"" + texFile + "\", append=TRUE)" << endl; - out << " } " << endl; - out << " else {" << endl; - out << " write(\" & \", \"" + texFile + "\", append=TRUE)" << endl; - out << " }" << endl; - out << " }" << endl; - out << " else {" << endl; - out << " write(\"&\", \"" + texFile + "\", append=TRUE)" << endl; - out << " }" << endl; - out << " }" << endl; - out << " }" << endl; - out << " jndx = jndx + 1" << endl; - out << " }" << endl; - out << " indx = indx + 1" << endl; - out << " }" << endl; - out << "} # for algorithm" << endl << endl; - out << "latexTableTail()" << endl; - //out << output << endl; + out << "# Step 3. Problem loop" << std::endl; + out << "latexTableHeader(\"" + problemList + "\", tabularString, latexTableFirstLine)" << std::endl << std::endl; + out << "indx = 0" << std::endl; + out << "for (i in algorithmList) {" << std::endl; + out << " if (i != \"" + experiment->algorithmNameList_[experiment->algorithmNameList_.size() - 1]+ "\") {" << std::endl; + out << " write(i , \"" + texFile + "\", append=TRUE)" << std::endl; + out << " write(\" & \", \"" + texFile + "\", append=TRUE)" << std::endl << std::endl; + out << " jndx = 0" << std::endl; + out << " for (j in algorithmList) {" << std::endl; + out << " for (problem in problemList) {" << std::endl; + out << " if (jndx != 0) {" << std::endl; + out << " if (i != j) {" << std::endl; + out << " printTableLine(indicator, i, j, indx, jndx, problem)" << std::endl; + out << " }" << std::endl; + out << " else {" << std::endl; + out << " write(\" \", \"" + texFile + "\", append=TRUE)" << std::endl; + out << " } " << std::endl; + out << " if (problem == \"" + problems[problems.size() - 1] + "\") {" << std::endl; + out << " if (j == \"" + experiment->algorithmNameList_[experiment->algorithmNameList_.size() - 1] + "\") {" << std::endl; + out << " write(\" \\\\\\\\ \", \"" + texFile + "\", append=TRUE)" << std::endl; + out << " } " << std::endl; + out << " else {" << std::endl; + out << " write(\" & \", \"" + texFile + "\", append=TRUE)" << std::endl; + out << " }" << std::endl; + out << " }" << std::endl; + out << " else {" << std::endl; + out << " write(\"&\", \"" + texFile + "\", append=TRUE)" << std::endl; + out << " }" << std::endl; + out << " }" << std::endl; + out << " }" << std::endl; + out << " jndx = jndx + 1" << std::endl; + out << " }" << std::endl; + out << " indx = indx + 1" << std::endl; + out << " }" << std::endl; + out << "} # for algorithm" << std::endl << std::endl; + out << "latexTableTail()" << std::endl; + //out << output << std::endl; - // Generate end of file - out << "#Step 4. Writes the end of latex file " << endl; - out << "latexTail()" << endl; + // Generate end of file + out << "#Step 4. Writes the end of latex file " << std::endl; + out << "latexTail()" << std::endl; - out.close(); - } // for + out.close(); + } // for } // generateScripts diff --git a/src/experiments/util/RWilcoxon.h b/src/experiments/util/RWilcoxon.h index 9ad64e8..d15f36d 100644 --- a/src/experiments/util/RWilcoxon.h +++ b/src/experiments/util/RWilcoxon.h @@ -2,6 +2,7 @@ // // Author: // Esteban López-Camacho +// Sérgio Vieira // // Copyright (c) 2011 Antonio J. Nebro, Juan J. Durillo // @@ -21,9 +22,11 @@ #ifndef __RWILCOXON__ #define __RWILCOXON__ -#include +#include "JMetalHeader.h" #include +using namespace JMetal; + class ExperimentReport; /** @@ -31,10 +34,11 @@ class ExperimentReport; * rank-sum test */ -class RWilcoxon { +class RWilcoxon +{ public: - static void generateScripts(vector problems, string prefix, - ExperimentReport * experiment); + static void generateScripts(VectorOfString problems, std::string prefix, + ExperimentReport * experiment); }; // RWilcoxon diff --git a/src/experiments/util/RunExperiment.cpp b/src/experiments/util/RunExperiment.cpp index 2b036b5..ae14ae3 100644 --- a/src/experiments/util/RunExperiment.cpp +++ b/src/experiments/util/RunExperiment.cpp @@ -2,6 +2,7 @@ // // Author: // Esteban López-Camacho +// Sérgio Vieira // // Copyright (c) 2011 Antonio J. Nebro, Juan J. Durillo // @@ -30,152 +31,163 @@ /** * Constructor */ -RunExperiment::RunExperiment(ExperimentExecution * experiment, map map, - int id, int numberOfThreads, int numberOfProblems, int threadIndex, - mutex * mtx) { +RunExperiment::RunExperiment(ExperimentExecution * experiment,MapOfStringFunct map, + int id, int numberOfThreads, int numberOfProblems, int threadIndex, + mutex * mtx) +{ - threadIndex_ = threadIndex; + threadIndex_ = threadIndex; - experiment_ = experiment; - id_ = id; - map_ = map; - numberOfThreads_ = numberOfThreads; - numberOfProblems_ = numberOfProblems; + experiment_ = experiment; + id_ = id; + map_ = map; + numberOfThreads_ = numberOfThreads; + numberOfProblems_ = numberOfProblems; - mutex_ = mtx; + mutex_ = mtx; - int partitions = numberOfProblems / numberOfThreads; + int partitions = numberOfProblems / numberOfThreads; } // RunExperiment -void RunExperiment::run() { +void RunExperiment::run() +{ - Algorithm * algorithm; // jMetal algorithm to be executed + Algorithm * algorithm; // jMetal algorithm to be executed - string experimentName = *(string*) map_["name"]; - cout << experimentName << endl; - experimentBaseDirectory_ = *(string*) map_["experimentDirectory"]; - cout << experimentBaseDirectory_ << endl; - algorithmNameList_ = *(vector*) map_["algorithmNameList"]; - problemList_ = *(vector*) map_["problemList"]; - independentRuns_ = *(int*) map_["independentRuns"]; - cout << independentRuns_ << endl; - outputParetoFrontFile_ = *(string*) map_["outputParetoFrontFile"]; - cout << outputParetoFrontFile_ << endl; - outputParetoSetFile_ = *(string*) map_["outputParetoSetFile"]; - cout << outputParetoSetFile_ << endl; + std::string experimentName = *(string*) map_["name"]; + std::cout << experimentName << std::endl; + experimentBaseDirectory_ = *(string*) map_["experimentDirectory"]; + std::cout << experimentBaseDirectory_ << std::endl; + algorithmNameList_ = *(VectorOfString*) map_["algorithmNameList"]; + problemList_ = *(VectorOfString*) map_["problemList"]; + independentRuns_ = *(int*) map_["independentRuns"]; + std::cout << independentRuns_ << std::endl; + outputParetoFrontFile_ = *(string*) map_["outputParetoFrontFile"]; + std::cout << outputParetoFrontFile_ << std::endl; + outputParetoSetFile_ = *(string*) map_["outputParetoSetFile"]; + std::cout << outputParetoSetFile_ << std::endl; - int numberOfAlgorithms = algorithmNameList_.size(); + int numberOfAlgorithms = algorithmNameList_.size(); - cout << "Experiment name: " << experimentName << endl; - cout << "Experiment directory: " << experimentBaseDirectory_ << endl; - cout << "Number of threads: " << numberOfThreads_ << endl; + std::cout << "Experiment name: " << experimentName << std::endl; + std::cout << "Experiment directory: " << experimentBaseDirectory_ << std::endl; + std::cout << "Number of threads: " << numberOfThreads_ << std::endl; - SolutionSet * resultFront = NULL; + SolutionSet * resultFront = nullptr; - int problemIndex = -1; - int algorithmIndex = -1; - int numRun = -1; + int problemIndex = -1; + int algorithmIndex = -1; + int numRun = -1; - bool end = false; + bool end = false; - while (!end) { + while (!end) + { - // WAIT MUTEX + // WAIT MUTEX // int result = pthread_mutex_lock(mutex_) ; // if (result != 0) { -// cerr << "RUNEXPERIMENT[" << threadIndex_ << "]: ERROR LOCKING THE MUTEX" << endl; +// cerr << "RUNEXPERIMENT[" << threadIndex_ << "]: ERROR LOCKING THE MUTEX" << std::endl; // exit(-1) ; // } - mutex_->lock(); - - int experimentIndividualListIndex = experiment_->experimentIndividualListIndex_; - // cout << "Thread[" << threadIndex_ << "] experimentIndividualListIndex = " << - // experimentIndividualListIndex << endl; - // cout << "Thread[" << threadIndex_ << "] experiment_->experimentIndividualList_.size() = " << - // experiment_->experimentIndividualList_.size() << endl; - if (experimentIndividualListIndex < experiment_->experimentIndividualList_.size()) { - ExperimentIndividual * expIndv - = experiment_->experimentIndividualList_[experimentIndividualListIndex]; - problemIndex = expIndv->getProblemIndex(); - algorithmIndex = expIndv->getAlgorithmIndex(); - numRun = expIndv->getNumRun(); - experiment_->experimentIndividualListIndex_ = experimentIndividualListIndex + 1; - } else { - // cout << "Thread[" << threadIndex_ << "] is finishing." << endl; - end = true; - } - - // SIGNAL MUTEX + mutex_->lock(); + + int experimentIndividualListIndex = experiment_->experimentIndividualListIndex_; + // std::cout << "Thread[" << threadIndex_ << "] experimentIndividualListIndex = " << + // experimentIndividualListIndex << std::endl; + // std::cout << "Thread[" << threadIndex_ << "] experiment_->experimentIndividualList_.size() = " << + // experiment_->experimentIndividualList_.size() << std::endl; + if (experimentIndividualListIndex < experiment_->experimentIndividualList_.size()) + { + ExperimentIndividual * expIndv + = experiment_->experimentIndividualList_[experimentIndividualListIndex]; + problemIndex = expIndv->getProblemIndex(); + algorithmIndex = expIndv->getAlgorithmIndex(); + numRun = expIndv->getNumRun(); + experiment_->experimentIndividualListIndex_ = experimentIndividualListIndex + 1; + } + else + { + // std::cout << "Thread[" << threadIndex_ << "] is finishing." << std::endl; + end = true; + } + + // SIGNAL MUTEX // result = pthread_mutex_unlock(mutex_) ; // if (result != 0) { -// cerr << "RUNEXPERIMENT[" << threadIndex_ << "]: ERROR UNLOCKING THE MUTEX" << endl; +// cerr << "RUNEXPERIMENT[" << threadIndex_ << "]: ERROR UNLOCKING THE MUTEX" << std::endl; // exit(-1) ; // } - mutex_->unlock(); - - if (!end) { - - Problem * problem; // The problem to solve - string problemName; - string pfFilePath = ""; - - // Get the problem from the list - problemName = problemList_[problemIndex] ; - - char * problemName_ = (char *) problemName.c_str(); - // TODO: Improve Settings - algorithm = experiment_->algorithmSettings(problemName, algorithmIndex, - experimentIndividualListIndex); - - problem = algorithm->getProblem(); - - // Create output directories - string directory; - directory = experimentBaseDirectory_ + "/data/" + algorithmNameList_[algorithmIndex] + "/" + - problemList_[problemIndex]; - if (FileUtils::existsPath(directory.c_str()) != 1) { - FileUtils::createDirectory(directory); - cout << "Creating directory: " << directory << endl; - } - - // Run the algorithm - cout << "Thread[" << threadIndex_ << "]: Start of algorithm: " << - algorithmNameList_[algorithmIndex] << ", problem: " << - problemList_[problemIndex] << ", run: " << numRun << endl; - resultFront= algorithm->execute(); - - // Put the results in the output directory - stringstream outputParetoFrontFilePath; - stringstream outputParetoSetFilePath; - if (experiment_->isSingleObjective_) { - outputParetoFrontFilePath << directory << "/" << outputParetoFrontFile_; - outputParetoSetFilePath << directory << "/" << outputParetoSetFile_; - } else { - outputParetoFrontFilePath << directory << "/" << outputParetoFrontFile_ - << "." << numRun; - outputParetoSetFilePath << directory << "/" << outputParetoSetFile_ - << "." << numRun; - } - - resultFront->printObjectivesToFile(outputParetoFrontFilePath.str(), - experiment_->isSingleObjective_); - resultFront->printVariablesToFile(outputParetoSetFilePath.str(), - experiment_->isSingleObjective_); - - cout << "Thread[" << threadIndex_ << "]: End of algorithm: " << - algorithmNameList_[algorithmIndex] << ", problem: " << - problemList_[problemIndex] << ", run: " << numRun << endl; - - delete resultFront; - delete experiment_->algorithmSettingsList_[experimentIndividualListIndex]; - - } // if - - } // while - - cout << "Thread[" << threadIndex_ << "] has finished." << endl; + mutex_->unlock(); + + if (!end) + { + + Problem * problem; // The problem to solve + std::string problemName; + std::string pfFilePath = ""; + + // Get the problem from the list + problemName = problemList_[problemIndex] ; + + char * problemName_ = (char *) problemName.c_str(); + // TODO: Improve Settings + algorithm = experiment_->algorithmSettings(problemName, algorithmIndex, + experimentIndividualListIndex); + + problem = algorithm->getProblem(); + + // Create output directories + std::string directory; + directory = experimentBaseDirectory_ + "/data/" + algorithmNameList_[algorithmIndex] + "/" + + problemList_[problemIndex]; + if (FileUtils::existsPath(directory.c_str()) != 1) + { + FileUtils::createDirectory(directory); + std::cout << "Creating directory: " << directory << std::endl; + } + + // Run the algorithm + std::cout << "Thread[" << threadIndex_ << "]: Start of algorithm: " << + algorithmNameList_[algorithmIndex] << ", problem: " << + problemList_[problemIndex] << ", run: " << numRun << std::endl; + resultFront= algorithm->execute(); + + // Put the results in the output directory + stringstream outputParetoFrontFilePath; + stringstream outputParetoSetFilePath; + if (experiment_->isSingleObjective_) + { + outputParetoFrontFilePath << directory << "/" << outputParetoFrontFile_; + outputParetoSetFilePath << directory << "/" << outputParetoSetFile_; + } + else + { + outputParetoFrontFilePath << directory << "/" << outputParetoFrontFile_ + << "." << numRun; + outputParetoSetFilePath << directory << "/" << outputParetoSetFile_ + << "." << numRun; + } + + resultFront->printObjectivesToFile(outputParetoFrontFilePath.str(), + experiment_->isSingleObjective_); + resultFront->printVariablesToFile(outputParetoSetFilePath.str(), + experiment_->isSingleObjective_); + + std::cout << "Thread[" << threadIndex_ << "]: End of algorithm: " << + algorithmNameList_[algorithmIndex] << ", problem: " << + problemList_[problemIndex] << ", run: " << numRun << std::endl; + + delete resultFront; + delete experiment_->algorithmSettingsList_[experimentIndividualListIndex]; + + } // if + + } // while + + std::cout << "Thread[" << threadIndex_ << "] has finished." << std::endl; } // run diff --git a/src/experiments/util/RunExperiment.h b/src/experiments/util/RunExperiment.h index cd1291c..343d486 100644 --- a/src/experiments/util/RunExperiment.h +++ b/src/experiments/util/RunExperiment.h @@ -2,6 +2,7 @@ // // Author: // Esteban López-Camacho +// Sérgio Vieira // // Copyright (c) 2011 Antonio J. Nebro, Juan J. Durillo // @@ -35,45 +36,46 @@ #include #include -using namespace std; + class ExperimentExecution; -class RunExperiment { +class RunExperiment +{ public: - ExperimentExecution * experiment_; - int id_; - map map_; - int numberOfThreads_; - int numberOfProblems_; + ExperimentExecution * experiment_; + int id_; + MapOfStringFunct map_; + int numberOfThreads_; + int numberOfProblems_; - RunExperiment(ExperimentExecution * experiment, map map, int id, - int numberOfThreads, int numberOfProblems, int threadIndex, - mutex * mtx); - void run(); + RunExperiment(ExperimentExecution * experiment,MapOfStringFunct map, int id, + int numberOfThreads, int numberOfProblems, int threadIndex, + mutex * mtx); + void run(); private: - int threadIndex_; + int threadIndex_; - mutex * mutex_; + mutex * mutex_; - string experimentName_; - vector algorithmNameList_; // List of the names of the algorithms to - // be executed - vector problemList_; // List of problems to be solved - string experimentBaseDirectory_; // Directory to store the results - string latexDirectory_; // Directory to store the latex files - string rDirectory_; // Directory to store the generated R scripts - string paretoFrontDirectory_; // Directory containing the Pareto front files - string outputParetoFrontFile_; // Name of the file containing the output - // Pareto front - string outputParetoSetFile_; // Name of the file containing the output - // Pareto set - int independentRuns_; // Number of independent runs per algorithm - // TODO: Settings[] algorithmSettings_; // Parameter settings of each algorithm + std::string experimentName_; + VectorOfString algorithmNameList_; // List of the names of the algorithms to + // be executed + VectorOfString problemList_; // List of problems to be solved + std::string experimentBaseDirectory_; // Directory to store the results + std::string latexDirectory_; // Directory to store the latex files + std::string rDirectory_; // Directory to store the generated R scripts + std::string paretoFrontDirectory_; // Directory containing the Pareto front files + std::string outputParetoFrontFile_; // Name of the file containing the output + // Pareto front + std::string outputParetoSetFile_; // Name of the file containing the output + // Pareto set + int independentRuns_; // Number of independent runs per algorithm + // TODO: Settings[] algorithmSettings_; // Parameter settings of each algorithm }; // RunExperiment diff --git a/src/experiments/util/Statistics.cpp b/src/experiments/util/Statistics.cpp index 831443e..abc1369 100644 --- a/src/experiments/util/Statistics.cpp +++ b/src/experiments/util/Statistics.cpp @@ -2,6 +2,7 @@ // // Author: // Esteban López-Camacho +// Sérgio Vieira // // Copyright (c) 2011 Antonio J. Nebro, Juan J. Durillo // @@ -30,19 +31,23 @@ * @param last index of last position to consider in the vector * @return The median */ -double Statistics::calculateMedian(vector vector_, int first, int last) { - double median = 0.0; +double Statistics::calculateMedian(VectorOfDouble vector_, int first, int last) +{ + double median = 0.0; - int size = last - first + 1; - // cout << "size: " << size << "first: " << first << " last: " << last << endl; + int size = last - first + 1; + // std::cout << "size: " << size << "first: " << first << " last: " << last << std::endl; - if (size % 2 != 0) { - median = vector_[first + size / 2]; - } else { - median = (vector_[first + size / 2 - 1] + vector_[first + size / 2]) / 2.0; - } + if (size % 2 != 0) + { + median = vector_[first + size / 2]; + } + else + { + median = (vector_[first + size / 2 - 1] + vector_[first + size / 2]) / 2.0; + } - return median; + return median; } // calculatemedian @@ -51,23 +56,28 @@ double Statistics::calculateMedian(vector vector_, int first, int last) * @param vector * @return The IQR */ -double Statistics::calculateIQR(vector vector_) { - double q3 = 0.0; - double q1 = 0.0; +double Statistics::calculateIQR(VectorOfDouble vector_) +{ + double q3 = 0.0; + double q1 = 0.0; - if (vector_.size() > 1) { // == 1 implies IQR = 0 - if (vector_.size() % 2 != 0) { - q3 = calculateMedian(vector_, vector_.size() / 2 + 1, vector_.size() - 1); - q1 = calculateMedian(vector_, 0, vector_.size() / 2 - 1); - //cout << "Q1: [" << 0 << ", " << (vector.size()/2 - 1) << "] = " << q1 << endl; - //cout << "Q3: [" << (vector.size()/2+1) << ", " << (vector.size()-1) << "]= " << q3 << endl; - } else { - q3 = calculateMedian(vector_, vector_.size() / 2, vector_.size() - 1); - q1 = calculateMedian(vector_, 0, vector_.size() / 2 - 1); - //cout << "Q1: [" << 0 << ", " << (vector.size()/2 - 1) << "] = " << q1 << endl; - //cout << "Q3: [" << (vector.size()/2) << ", " << (vector.size()-1) << "]= " << q3 << endl; - } // else - } // if + if (vector_.size() > 1) // == 1 implies IQR = 0 + { + if (vector_.size() % 2 != 0) + { + q3 = calculateMedian(vector_, vector_.size() / 2 + 1, vector_.size() - 1); + q1 = calculateMedian(vector_, 0, vector_.size() / 2 - 1); + //std::cout << "Q1: [" << 0 << ", " << (vector.size()/2 - 1) << "] = " << q1 << std::endl; + //std::cout << "Q3: [" << (vector.size()/2+1) << ", " << (vector.size()-1) << "]= " << q3 << std::endl; + } + else + { + q3 = calculateMedian(vector_, vector_.size() / 2, vector_.size() - 1); + q1 = calculateMedian(vector_, 0, vector_.size() / 2 - 1); + //std::cout << "Q1: [" << 0 << ", " << (vector.size()/2 - 1) << "] = " << q1 << std::endl; + //std::cout << "Q3: [" << (vector.size()/2) << ", " << (vector.size()-1) << "]= " << q3 << std::endl; + } // else + } // if - return q3 - q1; + return q3 - q1; } // calculateIQR diff --git a/src/experiments/util/Statistics.h b/src/experiments/util/Statistics.h index 269ccf7..1c90630 100644 --- a/src/experiments/util/Statistics.h +++ b/src/experiments/util/Statistics.h @@ -2,6 +2,7 @@ // // Author: // Esteban López-Camacho +// Sérgio Vieira // // Copyright (c) 2011 Antonio J. Nebro, Juan J. Durillo // @@ -21,19 +22,20 @@ #ifndef __STATISTICS__ #define __STATISTICS__ -#include +#include "JMetalHeader.h" -using namespace std; +using namespace JMetal; /** * This class provides methods for computing some statistics */ -class Statistics { +class Statistics +{ public: - static double calculateMedian(vector vector_, int first, int last); - static double calculateIQR(vector vector_); + static double calculateMedian(VectorOfDouble vector_, int first, int last); + static double calculateIQR(VectorOfDouble vector_); }; diff --git a/src/main/CMAES_main.cpp b/src/main/CMAES_main.cpp index 4900848..fd36aa5 100644 --- a/src/main/CMAES_main.cpp +++ b/src/main/CMAES_main.cpp @@ -2,6 +2,7 @@ // // Author: // Esteban López-Camacho +// Sérgio Vieira // // Copyright (c) 2011 Antonio J. Nebro, Juan J. Durillo // @@ -26,48 +27,52 @@ #include #include -int main(int argc, char ** argv) { +int main(int argc, char ** argv) +{ - clock_t t_ini, t_fin; + clock_t t_ini, t_fin; - Problem * problem ; // The problem to solve - Algorithm * algorithm ; // The algorithm to use + Problem * problem ; // The problem to solve + Algorithm * algorithm ; // The algorithm to use - if (argc>=2) { - problem = ProblemFactory::getProblem(argc, argv); - cout << "Selected problem: " << problem->getName() << endl; - } else { - cout << "No problem selected." << endl; - cout << "Default problem will be used: Sphere" << endl; - problem = ProblemFactory::getProblem(const_cast("Sphere")); - } + if (argc>=2) + { + problem = ProblemFactory::getProblem(argc, argv); + cout << "Selected problem: " << problem->getName() << endl; + } + else + { + cout << "No problem selected." << endl; + cout << "Default problem will be used: Sphere" << endl; + problem = ProblemFactory::getProblem(const_cast("Sphere")); + } - algorithm = new CMAES(problem); + algorithm = new CMAES(problem); - // Algorithm parameters - int populationSizeValue = 20; - int maxEvaluationsValue = 1000000; - algorithm->setInputParameter("populationSize",&populationSizeValue); - algorithm->setInputParameter("maxEvaluations",&maxEvaluationsValue); + // Algorithm parameters + int populationSizeValue = 20; + int maxEvaluationsValue = 1000000; + algorithm->setInputParameter("populationSize",&populationSizeValue); + algorithm->setInputParameter("maxEvaluations",&maxEvaluationsValue); - // Add the indicator object to the algorithm - //algorithm->setInputParameter("indicators", indicators) ; + // Add the indicator object to the algorithm + //algorithm->setInputParameter("indicators", indicators) ; - // Execute the Algorithm - t_ini = clock(); - SolutionSet * population = algorithm->execute(); - t_fin = clock(); - double secs = (double) (t_fin - t_ini); - secs = secs / CLOCKS_PER_SEC; + // Execute the Algorithm + t_ini = clock(); + SolutionSet * population = algorithm->execute(); + t_fin = clock(); + double secs = (double) (t_fin - t_ini); + secs = secs / CLOCKS_PER_SEC; - // Result messages - cout << "Total execution time: " << secs << "s" << endl; - cout << "Variables values have been written to file VAR" << endl; - population->printVariablesToFile("VAR"); - cout << "Objectives values have been written to file FUN" << endl; - population->printObjectivesToFile("FUN"); - - delete population; - delete algorithm; + // Result messages + cout << "Total execution time: " << secs << "s" << endl; + cout << "Variables values have been written to file VAR" << endl; + population->printVariablesToFile("VAR"); + cout << "Objectives values have been written to file FUN" << endl; + population->printObjectivesToFile("FUN"); + + delete population; + delete algorithm; } // main diff --git a/src/main/CMakeLists.txt b/src/main/CMakeLists.txt new file mode 100644 index 0000000..e365a04 --- /dev/null +++ b/src/main/CMakeLists.txt @@ -0,0 +1,4 @@ +include_directories(${PROJECT_SOURCE_DIR}/src) +link_directories(${PROJECT_SOURCE_DIR}/src) +add_executable(OMOPSO_main OMOPSO_main.cpp) +target_link_libraries(OMOPSO_main jMetalCpp) diff --git a/src/main/DE_main.cpp b/src/main/DE_main.cpp index e16e6f9..a96b431 100644 --- a/src/main/DE_main.cpp +++ b/src/main/DE_main.cpp @@ -2,6 +2,7 @@ // // Author: // Esteban López-Camacho +// Sérgio Vieira // // Copyright (c) 2011 Antonio J. Nebro, Juan J. Durillo // @@ -30,74 +31,78 @@ #include #include -int main(int argc, char ** argv) { - - clock_t t_ini, t_fin; - - Problem * problem ; // The problem to solve - Algorithm * algorithm ; // The algorithm to use - Operator * crossover ; // Crossover operator - Operator * mutation ; // Mutation operator - Operator * selection ; // Selection operator - - map parameters; - - //TODO: QualityIndicator * indicators; - - if (argc>=2) { - problem = ProblemFactory::getProblem(argc, argv); - cout << "Selected problem: " << problem->getName() << endl; - } else { - cout << "No problem selected." << endl; - cout << "Default problem will be used: Sphere" << endl; - problem = ProblemFactory::getProblem(const_cast("Sphere")); - } - - algorithm = new DE(problem); - - // Algorithm parameters - int populationSizeValue = 100; - int maxEvaluationsValue = 1000000; - algorithm->setInputParameter("populationSize",&populationSizeValue); - algorithm->setInputParameter("maxEvaluations",&maxEvaluationsValue); - - // Crossover operator - double crParameter = 0.5; - double fParameter = 0.5; - parameters["CR"] = &crParameter; - parameters["F"] = &fParameter; - string deVariantParameter = "rand/1/bin"; - parameters["DE_VARIANT"] = &deVariantParameter; - crossover = new DifferentialEvolutionCrossover(parameters); - - // Selection operator - parameters.clear(); - selection = new DifferentialEvolutionSelection(parameters) ; - - // Add the operators to the algorithm - algorithm->addOperator("crossover",crossover); - algorithm->addOperator("selection",selection); - - // Add the indicator object to the algorithm - //algorithm->setInputParameter("indicators", indicators); - - // Execute the Algorithm - t_ini = clock(); - SolutionSet * population = algorithm->execute(); - t_fin = clock(); - double secs = (double) (t_fin - t_ini); - secs = secs / CLOCKS_PER_SEC; - - // Result messages - cout << "Total execution time: " << secs << "s" << endl; - cout << "Variables values have been written to file VAR" << endl; - population->printVariablesToFile("VAR"); - cout << "Objectives values have been written to file FUN" << endl; - population->printObjectivesToFile("FUN"); - - delete crossover; - delete selection; - delete population; - delete algorithm; +int main(int argc, char ** argv) +{ + + clock_t t_ini, t_fin; + + Problem * problem ; // The problem to solve + Algorithm * algorithm ; // The algorithm to use + Operator * crossover ; // Crossover operator + Operator * mutation ; // Mutation operator + Operator * selection ; // Selection operator + + map parameters; + + //TODO: QualityIndicator * indicators; + + if (argc>=2) + { + problem = ProblemFactory::getProblem(argc, argv); + cout << "Selected problem: " << problem->getName() << endl; + } + else + { + cout << "No problem selected." << endl; + cout << "Default problem will be used: Sphere" << endl; + problem = ProblemFactory::getProblem(const_cast("Sphere")); + } + + algorithm = new DE(problem); + + // Algorithm parameters + int populationSizeValue = 100; + int maxEvaluationsValue = 1000000; + algorithm->setInputParameter("populationSize",&populationSizeValue); + algorithm->setInputParameter("maxEvaluations",&maxEvaluationsValue); + + // Crossover operator + double crParameter = 0.5; + double fParameter = 0.5; + parameters["CR"] = &crParameter; + parameters["F"] = &fParameter; + string deVariantParameter = "rand/1/bin"; + parameters["DE_VARIANT"] = &deVariantParameter; + crossover = new DifferentialEvolutionCrossover(parameters); + + // Selection operator + parameters.clear(); + selection = new DifferentialEvolutionSelection(parameters) ; + + // Add the operators to the algorithm + algorithm->addOperator("crossover",crossover); + algorithm->addOperator("selection",selection); + + // Add the indicator object to the algorithm + //algorithm->setInputParameter("indicators", indicators); + + // Execute the Algorithm + t_ini = clock(); + SolutionSet * population = algorithm->execute(); + t_fin = clock(); + double secs = (double) (t_fin - t_ini); + secs = secs / CLOCKS_PER_SEC; + + // Result messages + cout << "Total execution time: " << secs << "s" << endl; + cout << "Variables values have been written to file VAR" << endl; + population->printVariablesToFile("VAR"); + cout << "Objectives values have been written to file FUN" << endl; + population->printObjectivesToFile("FUN"); + + delete crossover; + delete selection; + delete population; + delete algorithm; } // main diff --git a/src/main/FastSMSEMOA_main.cpp b/src/main/FastSMSEMOA_main.cpp index a6f57bd..f0bca43 100755 --- a/src/main/FastSMSEMOA_main.cpp +++ b/src/main/FastSMSEMOA_main.cpp @@ -32,88 +32,92 @@ -int main(int argc, char ** argv) { - - clock_t t_ini, t_fin; - - Problem * problem ; // The problem to solve - Algorithm * algorithm ; // The algorithm to use - Operator * crossover ; // Crossover operator - Operator * mutation ; // Mutation operator - Operator * selection ; // Selection operator - - if (argc>=2) { - problem = ProblemFactory::getProblem(argc, argv); - cout << "Selected problem: " << problem->getName() << endl; - } else { - cout << "No problem selected." << endl; - cout << "Default problem will be used: Fonseca" << endl; - problem = ProblemFactory::getProblem(const_cast("Fonseca")); - } - - //TODO: Quality Indicators - //QualityIndicator indicators ; // Object to get quality indicators - //indicators = null ; - - algorithm = new FastSMSEMOA(problem); - - // Algorithm parameters - int populationSize = 100; - int maxEvaluations = 500; - double offset = 100; - - algorithm->setInputParameter("populationSize",&populationSize); - algorithm->setInputParameter("maxEvaluations",&maxEvaluations); - algorithm->setInputParameter("offset",&offset); - - // Mutation - map parameters; - double crossoverProbability = 0.9; - double crossoverDistributionIndex = 20.0; - parameters["probability"] = &crossoverProbability; - parameters["distributionIndex"] = &crossoverDistributionIndex; - crossover = new SBXCrossover(parameters); - - //Crossover - parameters.clear(); - double mutationProbability = 1.0/problem->getNumberOfVariables(); - double mutationDistributionIndex = 20.0; - parameters["probability"] = &mutationProbability; - parameters["distributionIndex"] = &mutationDistributionIndex; - mutation = new PolynomialMutation(parameters); - - // Selection Operator - parameters.clear(); - selection = new RandomSelection(parameters); - - // Add the operators to the algorithm - algorithm->addOperator("crossover",crossover); - algorithm->addOperator("mutation",mutation); - algorithm->addOperator("selection",selection); - - // Add the indicator object to the algorithm - //algorithm->setInputParameter("indicators", indicators) ; - - // Execute the Algorithm - t_ini = clock(); - - SolutionSet * population = algorithm->execute(); - - t_fin = clock(); - double secs = (double) (t_fin - t_ini); - secs = secs / CLOCKS_PER_SEC; - - // Result messages - cout << "Total execution time: " << secs << "s" << endl; - cout << "Variables values have been written to file VAR" << endl; - population->printVariablesToFile("VAR"); - cout << "Objectives values have been written to file FUN" << endl; - population->printObjectivesToFile("FUN"); - - delete mutation; - delete crossover; - delete selection; - delete population; - delete algorithm; +int main(int argc, char ** argv) +{ + + clock_t t_ini, t_fin; + + Problem * problem ; // The problem to solve + Algorithm * algorithm ; // The algorithm to use + Operator * crossover ; // Crossover operator + Operator * mutation ; // Mutation operator + Operator * selection ; // Selection operator + + if (argc>=2) + { + problem = ProblemFactory::getProblem(argc, argv); + cout << "Selected problem: " << problem->getName() << endl; + } + else + { + cout << "No problem selected." << endl; + cout << "Default problem will be used: Fonseca" << endl; + problem = ProblemFactory::getProblem(const_cast("Fonseca")); + } + + //TODO: Quality Indicators + //QualityIndicator indicators ; // Object to get quality indicators + //indicators = null ; + + algorithm = new FastSMSEMOA(problem); + + // Algorithm parameters + int populationSize = 100; + int maxEvaluations = 500; + double offset = 100; + + algorithm->setInputParameter("populationSize",&populationSize); + algorithm->setInputParameter("maxEvaluations",&maxEvaluations); + algorithm->setInputParameter("offset",&offset); + + // Mutation + map parameters; + double crossoverProbability = 0.9; + double crossoverDistributionIndex = 20.0; + parameters["probability"] = &crossoverProbability; + parameters["distributionIndex"] = &crossoverDistributionIndex; + crossover = new SBXCrossover(parameters); + + //Crossover + parameters.clear(); + double mutationProbability = 1.0/problem->getNumberOfVariables(); + double mutationDistributionIndex = 20.0; + parameters["probability"] = &mutationProbability; + parameters["distributionIndex"] = &mutationDistributionIndex; + mutation = new PolynomialMutation(parameters); + + // Selection Operator + parameters.clear(); + selection = new RandomSelection(parameters); + + // Add the operators to the algorithm + algorithm->addOperator("crossover",crossover); + algorithm->addOperator("mutation",mutation); + algorithm->addOperator("selection",selection); + + // Add the indicator object to the algorithm + //algorithm->setInputParameter("indicators", indicators) ; + + // Execute the Algorithm + t_ini = clock(); + + SolutionSet * population = algorithm->execute(); + + t_fin = clock(); + double secs = (double) (t_fin - t_ini); + secs = secs / CLOCKS_PER_SEC; + + // Result messages + cout << "Total execution time: " << secs << "s" << endl; + cout << "Variables values have been written to file VAR" << endl; + population->printVariablesToFile("VAR"); + cout << "Objectives values have been written to file FUN" << endl; + population->printObjectivesToFile("FUN"); + + delete mutation; + delete crossover; + delete selection; + delete population; + delete algorithm; } // main diff --git a/src/main/GDE3_main.cpp b/src/main/GDE3_main.cpp index 97a273d..8ba2a5a 100644 --- a/src/main/GDE3_main.cpp +++ b/src/main/GDE3_main.cpp @@ -2,6 +2,7 @@ // // Author: // Esteban López-Camacho +// Sérgio Vieira // // Copyright (c) 2011 Antonio J. Nebro, Juan J. Durillo // @@ -30,71 +31,75 @@ #include #include -int main(int argc, char ** argv) { - - clock_t t_ini, t_fin; - - Problem * problem ; // The problem to solve - Algorithm * algorithm ; // The algorithm to use - Operator * crossover ; // Crossover operator - Operator * selection ; // Selection operator - - map parameters; - - //TODO: QualityIndicator * indicators; - - if (argc>=2) { - problem = ProblemFactory::getProblem(argc, argv); - cout << "Selected problem: " << problem->getName() << endl; - } else { - cout << "No problem selected." << endl; - cout << "Default problem will be used: Fonseca" << endl; - problem = ProblemFactory::getProblem(const_cast("Fonseca")); - } - - algorithm = new GDE3(problem); - - // Algorithm parameters - int populationSizeValue = 100; - int maxIterationsValue = 250; - algorithm->setInputParameter("populationSize",&populationSizeValue); - algorithm->setInputParameter("maxIterations",&maxIterationsValue); - - // Crossover operator - double crParameter = 0.5; - double fParameter = 0.5; - parameters["CR"] = &crParameter; - parameters["F"] = &fParameter; - crossover = new DifferentialEvolutionCrossover(parameters); - - // Selection operator - parameters.clear(); - selection = new DifferentialEvolutionSelection(parameters) ; - - // Add the operators to the algorithm - algorithm->addOperator("crossover",crossover); - algorithm->addOperator("selection",selection); - - // Add the indicator object to the algorithm - //algorithm->setInputParameter("indicators", indicators) ; - - // Execute the Algorithm - t_ini = clock(); - SolutionSet * population = algorithm->execute(); - t_fin = clock(); - double secs = (double) (t_fin - t_ini); - secs = secs / CLOCKS_PER_SEC; - - // Result messages - cout << "Total execution time: " << secs << "s" << endl; - cout << "Variables values have been written to file VAR" << endl; - population->printVariablesToFile("VAR"); - cout << "Objectives values have been written to file FUN" << endl; - population->printObjectivesToFile("FUN"); - - delete selection; - delete crossover; - delete population; - delete algorithm; +int main(int argc, char ** argv) +{ + + clock_t t_ini, t_fin; + + Problem * problem ; // The problem to solve + Algorithm * algorithm ; // The algorithm to use + Operator * crossover ; // Crossover operator + Operator * selection ; // Selection operator + + map parameters; + + //TODO: QualityIndicator * indicators; + + if (argc>=2) + { + problem = ProblemFactory::getProblem(argc, argv); + cout << "Selected problem: " << problem->getName() << endl; + } + else + { + cout << "No problem selected." << endl; + cout << "Default problem will be used: Fonseca" << endl; + problem = ProblemFactory::getProblem(const_cast("Fonseca")); + } + + algorithm = new GDE3(problem); + + // Algorithm parameters + int populationSizeValue = 100; + int maxIterationsValue = 250; + algorithm->setInputParameter("populationSize",&populationSizeValue); + algorithm->setInputParameter("maxIterations",&maxIterationsValue); + + // Crossover operator + double crParameter = 0.5; + double fParameter = 0.5; + parameters["CR"] = &crParameter; + parameters["F"] = &fParameter; + crossover = new DifferentialEvolutionCrossover(parameters); + + // Selection operator + parameters.clear(); + selection = new DifferentialEvolutionSelection(parameters) ; + + // Add the operators to the algorithm + algorithm->addOperator("crossover",crossover); + algorithm->addOperator("selection",selection); + + // Add the indicator object to the algorithm + //algorithm->setInputParameter("indicators", indicators) ; + + // Execute the Algorithm + t_ini = clock(); + SolutionSet * population = algorithm->execute(); + t_fin = clock(); + double secs = (double) (t_fin - t_ini); + secs = secs / CLOCKS_PER_SEC; + + // Result messages + cout << "Total execution time: " << secs << "s" << endl; + cout << "Variables values have been written to file VAR" << endl; + population->printVariablesToFile("VAR"); + cout << "Objectives values have been written to file FUN" << endl; + population->printObjectivesToFile("FUN"); + + delete selection; + delete crossover; + delete population; + delete algorithm; } // main diff --git a/src/main/MOCHC_main.cpp b/src/main/MOCHC_main.cpp index 218290e..d977ad7 100644 --- a/src/main/MOCHC_main.cpp +++ b/src/main/MOCHC_main.cpp @@ -48,87 +48,91 @@ * 5th International Conference, EMO 2009, pp: 183-197. * April 2009) */ -int main(int argc, char ** argv) { - - clock_t t_ini, t_fin; - - Problem * problem ; // The problem to solve - Algorithm * algorithm ; // The algorithm to use - HUXCrossover * crossover ; // Crossover operator - BitFlipMutation * mutation ; // Mutation operator - BinaryTournament * selection ; // Selection operator - - if (argc>=2) { - problem = ProblemFactory::getProblem(argc, argv); - cout << "Selected problem: " << problem->getName() << endl; - } else { - cout << "No problem selected." << endl; - cout << "Default problem will be used: Fonseca" << endl; - problem = ProblemFactory::getProblem(const_cast("ZDT5")); - } - +int main(int argc, char ** argv) +{ + + clock_t t_ini, t_fin; + + Problem * problem ; // The problem to solve + Algorithm * algorithm ; // The algorithm to use + HUXCrossover * crossover ; // Crossover operator + BitFlipMutation * mutation ; // Mutation operator + BinaryTournament * selection ; // Selection operator + + if (argc>=2) + { + problem = ProblemFactory::getProblem(argc, argv); + cout << "Selected problem: " << problem->getName() << endl; + } + else + { + cout << "No problem selected." << endl; + cout << "Default problem will be used: Fonseca" << endl; + problem = ProblemFactory::getProblem(const_cast("ZDT5")); + } + // QualityIndicator * indicators ; // Object to get quality indicators // indicators = NULL ; - algorithm = new MOCHC(problem); + algorithm = new MOCHC(problem); - // Algorithm parameters - int populationSize = 100; - int maxEvaluations = 25000; - double initialConvergenceCount = 0.25; - double preservedPopulation = 0.05; - int convergenceValue = 3; - algorithm->setInputParameter("populationSize",&populationSize); - algorithm->setInputParameter("maxEvaluations",&maxEvaluations); - algorithm->setInputParameter("initialConvergenceCount",&initialConvergenceCount); - algorithm->setInputParameter("preservedPopulation",&preservedPopulation); - algorithm->setInputParameter("convergenceValue",&convergenceValue); + // Algorithm parameters + int populationSize = 100; + int maxEvaluations = 25000; + double initialConvergenceCount = 0.25; + double preservedPopulation = 0.05; + int convergenceValue = 3; + algorithm->setInputParameter("populationSize",&populationSize); + algorithm->setInputParameter("maxEvaluations",&maxEvaluations); + algorithm->setInputParameter("initialConvergenceCount",&initialConvergenceCount); + algorithm->setInputParameter("preservedPopulation",&preservedPopulation); + algorithm->setInputParameter("convergenceValue",&convergenceValue); - // Mutation and Crossover for Real codification - map parameters; + // Mutation and Crossover for Real codification + map parameters; - double crossoverProbability = 1.0; - double crossoverDistributionIndex = 20.0; - parameters["probability"] = &crossoverProbability; - crossover = new HUXCrossover(parameters); + double crossoverProbability = 1.0; + double crossoverDistributionIndex = 20.0; + parameters["probability"] = &crossoverProbability; + crossover = new HUXCrossover(parameters); - parameters.clear(); - double mutationProbability = 0.35; - parameters["probability"] = &mutationProbability; + parameters.clear(); + double mutationProbability = 0.35; + parameters["probability"] = &mutationProbability; - mutation = new BitFlipMutation(parameters); + mutation = new BitFlipMutation(parameters); - // Selection Operator - parameters.clear(); - selection = new BinaryTournament(parameters); + // Selection Operator + parameters.clear(); + selection = new BinaryTournament(parameters); - // Add the operators to the algorithm - algorithm->addOperator("crossover",crossover); - algorithm->addOperator("mutation",mutation); - algorithm->addOperator("parentSelection",selection); + // Add the operators to the algorithm + algorithm->addOperator("crossover",crossover); + algorithm->addOperator("mutation",mutation); + algorithm->addOperator("parentSelection",selection); - // Add the indicator object to the algorithm + // Add the indicator object to the algorithm // algorithm->setInputParameter("indicators", indicators) ; - // Execute the Algorithm - t_ini = clock(); - SolutionSet * population = algorithm->execute(); - t_fin = clock(); - double secs = (double) (t_fin - t_ini); - secs = secs / CLOCKS_PER_SEC; - - // Result messages - cout << "Total execution time: " << secs << "s" << endl; - cout << "Variables values have been written to file VAR" << endl; - population->printVariablesToFile("VAR"); - cout << "Objectives values have been written to file FUN" << endl; - population->printObjectivesToFile("FUN"); - - - delete selection; - delete mutation; - delete crossover; - delete population; - delete algorithm; + // Execute the Algorithm + t_ini = clock(); + SolutionSet * population = algorithm->execute(); + t_fin = clock(); + double secs = (double) (t_fin - t_ini); + secs = secs / CLOCKS_PER_SEC; + + // Result messages + cout << "Total execution time: " << secs << "s" << endl; + cout << "Variables values have been written to file VAR" << endl; + population->printVariablesToFile("VAR"); + cout << "Objectives values have been written to file FUN" << endl; + population->printObjectivesToFile("FUN"); + + + delete selection; + delete mutation; + delete crossover; + delete population; + delete algorithm; } // main diff --git a/src/main/MOEAD_main.cpp b/src/main/MOEAD_main.cpp index 125afdf..db9c9d9 100644 --- a/src/main/MOEAD_main.cpp +++ b/src/main/MOEAD_main.cpp @@ -2,6 +2,7 @@ // // Author: // Esteban López-Camacho +// Sérgio Vieira // // Copyright (c) 2011 Antonio J. Nebro, Juan J. Durillo // @@ -31,93 +32,97 @@ /** * This class executes the algorithm described in: - * H. Li and Q. Zhang, - * "Multiobjective Optimization Problems with Complicated Pareto Sets, MOEA/D - * and NSGA-II". IEEE Trans on Evolutionary Computation, vol. 12, no 2, - * pp 284-302, April/2009. + * H. Li and Q. Zhang, + * "Multiobjective Optimization Problems with Complicated Pareto Sets, MOEA/D + * and NSGA-II". IEEE Trans on Evolutionary Computation, vol. 12, no 2, + * pp 284-302, April/2009. */ -int main(int argc, char ** argv) { - - clock_t t_ini, t_fin; - - Problem * problem; // The problem to solve - Algorithm * algorithm; // The algorithm to use - Operator * crossover; // Crossover operator - Operator * mutation; // Mutation operator - - //QualityIndicator * indicators ; // Object to get quality indicators - - map parameters; // Operator parameters - - //TODO: QualityIndicator * indicators; // Object to get quality indicators - - if (argc>=2) { - problem = ProblemFactory::getProblem(argc, argv); - cout << "Selected problem: " << problem->getName() << endl; - } else { - cout << "No problem selected." << endl; - cout << "Default problem will be used: Kursawe" << endl; - problem = ProblemFactory::getProblem(const_cast("Kursawe")); - } - - algorithm = new MOEAD(problem); - - // Algorithm parameters - int populationSizeValue = 300; - int maxEvaluationsValue = 150000; - algorithm->setInputParameter("populationSize",&populationSizeValue); - algorithm->setInputParameter("maxEvaluations",&maxEvaluationsValue); - - // Directory with the files containing the weight vectors used in - // Q. Zhang, W. Liu, and H Li, The Performance of a New Version of MOEA/D - // on CEC09 Unconstrained MOP Test Instances Working Report CES-491, School - // of CS & EE, University of Essex, 02/2009. - // http://dces.essex.ac.uk/staff/qzhang/MOEAcompetition/CEC09final/code/ZhangMOEADcode/moead0305.rar - string dataDirectoryValue = - "../../data/Weight"; - algorithm->setInputParameter("dataDirectory", &dataDirectoryValue); - - // Crossover operator - double crParameter = 1.0; - double fParameter = 0.5; - parameters["CR"] = &crParameter; - parameters["F"] = &fParameter; - crossover = new DifferentialEvolutionCrossover(parameters); - - // Mutation operator - parameters.clear(); - double probabilityParameter = 1.0/(problem->getNumberOfVariables()); - double distributionIndexParameter = 20.0; - parameters["probability"] = &probabilityParameter; - parameters["distributionIndex"] = &distributionIndexParameter; - mutation = new PolynomialMutation(parameters); - - // Add the operators to the algorithm - algorithm->addOperator("crossover",crossover); - algorithm->addOperator("mutation",mutation); - - // Add the indicator object to the algorithm - //algorithm->setInputParameter("indicators", indicators) ; - - // Execute the Algorithm - t_ini = clock(); - SolutionSet * population = algorithm->execute(); - t_fin = clock(); - double secs = (double) (t_fin - t_ini); - secs = secs / CLOCKS_PER_SEC; - - // Result messages - cout << "Total execution time: " << secs << "s" << endl; - cout << "Variables values have been written to file VAR" << endl; - population->printVariablesToFile("VAR"); - cout << "Objectives values have been written to file FUN" << endl; - population->printObjectivesToFile("FUN"); - - delete mutation; - delete crossover; - delete population; - delete algorithm; +int main(int argc, char ** argv) +{ + + clock_t t_ini, t_fin; + + Problem * problem; // The problem to solve + Algorithm * algorithm; // The algorithm to use + Operator * crossover; // Crossover operator + Operator * mutation; // Mutation operator + + //QualityIndicator * indicators ; // Object to get quality indicators + + map parameters; // Operator parameters + + //TODO: QualityIndicator * indicators; // Object to get quality indicators + + if (argc>=2) + { + problem = ProblemFactory::getProblem(argc, argv); + cout << "Selected problem: " << problem->getName() << endl; + } + else + { + cout << "No problem selected." << endl; + cout << "Default problem will be used: Kursawe" << endl; + problem = ProblemFactory::getProblem(const_cast("Kursawe")); + } + + algorithm = new MOEAD(problem); + + // Algorithm parameters + int populationSizeValue = 300; + int maxEvaluationsValue = 150000; + algorithm->setInputParameter("populationSize",&populationSizeValue); + algorithm->setInputParameter("maxEvaluations",&maxEvaluationsValue); + + // Directory with the files containing the weight vectors used in + // Q. Zhang, W. Liu, and H Li, The Performance of a New Version of MOEA/D + // on CEC09 Unconstrained MOP Test Instances Working Report CES-491, School + // of CS & EE, University of Essex, 02/2009. + // http://dces.essex.ac.uk/staff/qzhang/MOEAcompetition/CEC09final/code/ZhangMOEADcode/moead0305.rar + string dataDirectoryValue = + "../../data/Weight"; + algorithm->setInputParameter("dataDirectory", &dataDirectoryValue); + + // Crossover operator + double crParameter = 1.0; + double fParameter = 0.5; + parameters["CR"] = &crParameter; + parameters["F"] = &fParameter; + crossover = new DifferentialEvolutionCrossover(parameters); + + // Mutation operator + parameters.clear(); + double probabilityParameter = 1.0/(problem->getNumberOfVariables()); + double distributionIndexParameter = 20.0; + parameters["probability"] = &probabilityParameter; + parameters["distributionIndex"] = &distributionIndexParameter; + mutation = new PolynomialMutation(parameters); + + // Add the operators to the algorithm + algorithm->addOperator("crossover",crossover); + algorithm->addOperator("mutation",mutation); + + // Add the indicator object to the algorithm + //algorithm->setInputParameter("indicators", indicators) ; + + // Execute the Algorithm + t_ini = clock(); + SolutionSet * population = algorithm->execute(); + t_fin = clock(); + double secs = (double) (t_fin - t_ini); + secs = secs / CLOCKS_PER_SEC; + + // Result messages + cout << "Total execution time: " << secs << "s" << endl; + cout << "Variables values have been written to file VAR" << endl; + population->printVariablesToFile("VAR"); + cout << "Objectives values have been written to file FUN" << endl; + population->printObjectivesToFile("FUN"); + + delete mutation; + delete crossover; + delete population; + delete algorithm; } // main diff --git a/src/main/NSGAII_main.cpp b/src/main/NSGAII_main.cpp index 76662cb..fcf5764 100644 --- a/src/main/NSGAII_main.cpp +++ b/src/main/NSGAII_main.cpp @@ -2,6 +2,7 @@ // // Author: // Esteban López-Camacho +// Sérgio Vieira // // Copyright (c) 2011 Antonio J. Nebro, Juan J. Durillo // @@ -47,78 +48,82 @@ * 5th International Conference, EMO 2009, pp: 183-197. * April 2009) */ -int main(int argc, char ** argv) { - - clock_t t_ini, t_fin; - - Problem * problem ; // The problem to solve - Algorithm * algorithm ; // The algorithm to use - Operator * crossover ; // Crossover operator - Operator * mutation ; // Mutation operator - Operator * selection ; // Selection operator - - if (argc>=2) { - problem = ProblemFactory::getProblem(argc, argv); - cout << "Selected problem: " << problem->getName() << endl; - } else { - cout << "No problem selected." << endl; - cout << "Default problem will be used: Fonseca" << endl; - problem = ProblemFactory::getProblem(const_cast("Fonseca")); - } - +int main(int argc, char ** argv) +{ + + clock_t t_ini, t_fin; + + Problem * problem ; // The problem to solve + Algorithm * algorithm ; // The algorithm to use + Operator * crossover ; // Crossover operator + Operator * mutation ; // Mutation operator + Operator * selection ; // Selection operator + + if (argc>=2) + { + problem = ProblemFactory::getProblem(argc, argv); + cout << "Selected problem: " << problem->getName() << endl; + } + else + { + cout << "No problem selected." << endl; + cout << "Default problem will be used: Fonseca" << endl; + problem = ProblemFactory::getProblem(const_cast("Fonseca")); + } + // QualityIndicator * indicators ; // Object to get quality indicators // indicators = NULL ; - algorithm = new NSGAII(problem); + algorithm = new NSGAII(problem); - // Algorithm parameters - int populationSize = 100; - int maxEvaluations = 25000; - algorithm->setInputParameter("populationSize",&populationSize); - algorithm->setInputParameter("maxEvaluations",&maxEvaluations); + // Algorithm parameters + int populationSize = 100; + int maxEvaluations = 25000; + algorithm->setInputParameter("populationSize",&populationSize); + algorithm->setInputParameter("maxEvaluations",&maxEvaluations); - // Mutation and Crossover for Real codification - map parameters; + // Mutation and Crossover for Real codification + map parameters; - double crossoverProbability = 0.9; - double crossoverDistributionIndex = 20.0; - parameters["probability"] = &crossoverProbability; - parameters["distributionIndex"] = &crossoverDistributionIndex; - crossover = new SBXCrossover(parameters); + double crossoverProbability = 0.9; + double crossoverDistributionIndex = 20.0; + parameters["probability"] = &crossoverProbability; + parameters["distributionIndex"] = &crossoverDistributionIndex; + crossover = new SBXCrossover(parameters); - parameters.clear(); - double mutationProbability = 1.0/problem->getNumberOfVariables(); - double mutationDistributionIndex = 20.0; - parameters["probability"] = &mutationProbability; - parameters["distributionIndex"] = &mutationDistributionIndex; - mutation = new PolynomialMutation(parameters); + parameters.clear(); + double mutationProbability = 1.0/problem->getNumberOfVariables(); + double mutationDistributionIndex = 20.0; + parameters["probability"] = &mutationProbability; + parameters["distributionIndex"] = &mutationDistributionIndex; + mutation = new PolynomialMutation(parameters); - // Selection Operator - parameters.clear(); - selection = new BinaryTournament2(parameters); + // Selection Operator + parameters.clear(); + selection = new BinaryTournament2(parameters); - // Add the operators to the algorithm - algorithm->addOperator("crossover",crossover); - algorithm->addOperator("mutation",mutation); - algorithm->addOperator("selection",selection); + // Add the operators to the algorithm + algorithm->addOperator("crossover",crossover); + algorithm->addOperator("mutation",mutation); + algorithm->addOperator("selection",selection); - // Add the indicator object to the algorithm + // Add the indicator object to the algorithm // algorithm->setInputParameter("indicators", indicators) ; - // Execute the Algorithm - t_ini = clock(); - SolutionSet * population = algorithm->execute(); - t_fin = clock(); - double secs = (double) (t_fin - t_ini); - secs = secs / CLOCKS_PER_SEC; - - // Result messages - cout << "Total execution time: " << secs << "s" << endl; - cout << "Variables values have been written to file VAR" << endl; - population->printVariablesToFile("VAR"); - cout << "Objectives values have been written to file FUN" << endl; - population->printObjectivesToFile("FUN"); - + // Execute the Algorithm + t_ini = clock(); + SolutionSet * population = algorithm->execute(); + t_fin = clock(); + double secs = (double) (t_fin - t_ini); + secs = secs / CLOCKS_PER_SEC; + + // Result messages + cout << "Total execution time: " << secs << "s" << endl; + cout << "Variables values have been written to file VAR" << endl; + population->printVariablesToFile("VAR"); + cout << "Objectives values have been written to file FUN" << endl; + population->printObjectivesToFile("FUN"); + // if (indicators != NULL) { // cout << "Quality indicators" << endl; // cout << "Hypervolume: " << indicators->getHypervolume(population) << endl; @@ -126,15 +131,15 @@ int main(int argc, char ** argv) { // cout << "IGD : " << indicators->getIGD(population) << endl; // cout << "Spread : " << indicators->getSpread(population) << endl; // cout << "Epsilon : " << indicators->getEpsilon(population) << endl; -// +// // int evaluations = *(int *) algorithm->getOutputParameter("evaluations");; // cout << "Speed : " << evaluations << " evaluations" << endl; // } // if - delete selection; - delete mutation; - delete crossover; - delete population; - delete algorithm; + delete selection; + delete mutation; + delete crossover; + delete population; + delete algorithm; } // main diff --git a/src/main/NSGAIIbin_main.cpp b/src/main/NSGAIIbin_main.cpp index 13ed677..22e0fa4 100644 --- a/src/main/NSGAIIbin_main.cpp +++ b/src/main/NSGAIIbin_main.cpp @@ -33,91 +33,95 @@ /** * Class implementing the NSGA-II algorithm -> binary encoding version */ -int main(int argc, char ** argv) { - - clock_t t_ini, t_fin; - - Problem * problem ; // The problem to solve - Algorithm * algorithm ; // The algorithm to use - Operator * crossover ; // Crossover operator - Operator * mutation ; // Mutation operator - Operator * selection ; // Selection operator - - if (argc>=2) { - problem = ProblemFactory::getProblem(argc, argv); - cout << "Selected problem: " << problem->getName() << endl; - } else { - - cout << "No problem selected." << endl; - cout << "Default problem will be used: OneMax" << endl; - - char ** argv = new char*[2]; - argv[0] = new char[3]; - strcpy(argv[0], "200"); - argv[1] = new char[1]; - strcpy(argv[1], "2"); - char * problemName = new char[6]; - strcpy(problemName, "OneMax"); - - problem = ProblemFactory::getProblem(problemName, 2, argv); - - delete argv[0]; - delete argv[1]; - delete [] argv; - delete problemName; - - } - - algorithm = new NSGAII(problem); - - // Algorithm parameters - int populationSize = 100; - int maxEvaluations = 25000; - algorithm->setInputParameter("populationSize",&populationSize); - algorithm->setInputParameter("maxEvaluations",&maxEvaluations); - - map parameters; - - // Mutation operator - parameters.clear(); - double mutationProbability = 1.0/problem->getNumberOfBits(); - parameters["probability"] = &mutationProbability; - mutation = new BitFlipMutation(parameters); - - // Crossover operator - parameters.clear(); - double crossoverProbability = 0.9; - parameters["probability"] = &crossoverProbability; - crossover = new SinglePointCrossover(parameters); - - // Selection Operator - parameters.clear(); - selection = new BinaryTournament2(parameters) ; - - // Add the operators to the algorithm - algorithm->addOperator("crossover",crossover); - algorithm->addOperator("mutation",mutation); - algorithm->addOperator("selection",selection); - - // Execute the Algorithm - t_ini = clock(); - SolutionSet * population = algorithm->execute(); - t_fin = clock(); - double secs = (double) (t_fin - t_ini); - secs = secs / CLOCKS_PER_SEC; - - // Result messages - cout << "Total execution time: " << secs << "s" << endl; - cout << "Variables values have been written to file VAR" << endl; - population->printVariablesToFile("VAR"); - cout << "Objectives values have been written to file FUN" << endl; - population->printObjectivesToFile("FUN"); - - delete selection; - delete mutation; - delete crossover; - delete population; - delete algorithm; +int main(int argc, char ** argv) +{ + + clock_t t_ini, t_fin; + + Problem * problem ; // The problem to solve + Algorithm * algorithm ; // The algorithm to use + Operator * crossover ; // Crossover operator + Operator * mutation ; // Mutation operator + Operator * selection ; // Selection operator + + if (argc>=2) + { + problem = ProblemFactory::getProblem(argc, argv); + cout << "Selected problem: " << problem->getName() << endl; + } + else + { + + cout << "No problem selected." << endl; + cout << "Default problem will be used: OneMax" << endl; + + char ** argv = new char*[2]; + argv[0] = new char[3]; + strcpy(argv[0], "200"); + argv[1] = new char[1]; + strcpy(argv[1], "2"); + char * problemName = new char[7]; + strcpy(problemName, "OneMax"); + + problem = ProblemFactory::getProblem(problemName, 2, argv); + + delete argv[0]; + delete argv[1]; + delete [] argv; + delete [] problemName; + + } + + algorithm = new NSGAII(problem); + + // Algorithm parameters + int populationSize = 100; + int maxEvaluations = 25000; + algorithm->setInputParameter("populationSize",&populationSize); + algorithm->setInputParameter("maxEvaluations",&maxEvaluations); + + map parameters; + + // Mutation operator + parameters.clear(); + double mutationProbability = 1.0/problem->getNumberOfBits(); + parameters["probability"] = &mutationProbability; + mutation = new BitFlipMutation(parameters); + + // Crossover operator + parameters.clear(); + double crossoverProbability = 0.9; + parameters["probability"] = &crossoverProbability; + crossover = new SinglePointCrossover(parameters); + + // Selection Operator + parameters.clear(); + selection = new BinaryTournament2(parameters) ; + + // Add the operators to the algorithm + algorithm->addOperator("crossover",crossover); + algorithm->addOperator("mutation",mutation); + algorithm->addOperator("selection",selection); + + // Execute the Algorithm + t_ini = clock(); + SolutionSet * population = algorithm->execute(); + t_fin = clock(); + double secs = (double) (t_fin - t_ini); + secs = secs / CLOCKS_PER_SEC; + + // Result messages + cout << "Total execution time: " << secs << "s" << endl; + cout << "Variables values have been written to file VAR" << endl; + population->printVariablesToFile("VAR"); + cout << "Objectives values have been written to file FUN" << endl; + population->printObjectivesToFile("FUN"); + + delete selection; + delete mutation; + delete crossover; + delete population; + delete algorithm; } // main diff --git a/src/main/OMOPSO_main.cpp b/src/main/OMOPSO_main.cpp index 9a4272e..e62a61b 100644 --- a/src/main/OMOPSO_main.cpp +++ b/src/main/OMOPSO_main.cpp @@ -2,6 +2,7 @@ // // Author: // Esteban López-Camacho +// Sérgio Vieira // // Copyright (c) 2014 Antonio J. Nebro // @@ -24,96 +25,95 @@ #include #include +#include "metaheuristics/smpso/SMPSO.h" +#include "operators/mutation/PolynomialMutation.h" #include #include #include #include - +#include "RangeMutation.h" #include #include +#include "problems/SIGA/BarrosF1F2.h" +#include "problems/SIGA/BarrosF1F3.h" +#include "problems/SIGA/BarrosF1F4.h" +#include "problems/SIGA/BarrosF1F5.h" +#include "problems/SIGA/BarrosF5F3.h" /** * Method for configuring and running the OMOPSO algorithm */ -int main(int argc, char ** argv) { - - clock_t t_ini, t_fin; - - Problem *problem; // The problem to solve - Algorithm *algorithm; // The algorithm to use - Mutation *uniformMutation; - Mutation *nonUniformMutation; - - QualityIndicator *indicators ; // Object to get quality indicators - - map parameters; // Operator parameters - - indicators = NULL; - - if (argc>=2) { - problem = ProblemFactory::getProblem(argc, argv); - cout << "Selected problem: " << problem->getName() << endl; - } else { - cout << "No problem selected." << endl; - cout << "Default problem will be used: Kursawe" << endl; - problem = ProblemFactory::getProblem(const_cast("Kursawe")); - } - - algorithm = new OMOPSO(problem); - - int maxIterations = 250; - double perturbationIndex = 0.5; - double mutationProbability = 1.0/problem->getNumberOfVariables(); - int swarmSize = 100; - int archiveSize = 100; - - // Algorithm parameters - algorithm->setInputParameter("swarmSize",&swarmSize); - algorithm->setInputParameter("archiveSize",&archiveSize); - algorithm->setInputParameter("maxIterations",&maxIterations); - - parameters["probability"] = &mutationProbability; - parameters["perturbation"] = &perturbationIndex; - uniformMutation = new UniformMutation(parameters); - - parameters.clear(); - parameters["probability"] = &mutationProbability; - parameters["perturbation"] = &perturbationIndex; - parameters["maxIterations"] = &maxIterations; - nonUniformMutation = new NonUniformMutation(parameters); - - - // Add the operators to the algorithm - algorithm->addOperator("uniformMutation",uniformMutation); - algorithm->addOperator("nonUniformMutation",nonUniformMutation); - - // Execute the Algorithm - t_ini = clock(); - SolutionSet * population = algorithm->execute(); - t_fin = clock(); - double secs = (double) (t_fin - t_ini); - secs = secs / CLOCKS_PER_SEC; - - // Print the results - cout << "Total execution time: " << secs << "s" << endl; - cout << "Variables values have been written to file VAR" << endl; - population->printVariablesToFile("VAR"); - cout << "Objectives values have been written to file FUN" << endl; - population->printObjectivesToFile("FUN"); - - if (indicators != NULL) { - cout << "Quality indicators" << endl ; - cout << "Hypervolume: " << indicators->getHypervolume(population) << endl; - cout << "GD : " << indicators->getGD(population) << endl ; - cout << "IGD : " << indicators->getIGD(population) << endl ; - cout << "Spread : " << indicators->getSpread(population) << endl ; - cout << "Epsilon : " << indicators->getEpsilon(population) << endl ; - } // if - - delete uniformMutation; - delete nonUniformMutation; - delete population; - delete algorithm; - +int main(int argc, char ** argv) +{ + clock_t t_ini, t_fin; + Problem *problem = nullptr; // The problem to solve + Algorithm *algorithm = nullptr; // The algorithm to use + Mutation *uniformMutation = nullptr; + Mutation *nonUniformMutation = nullptr; + QualityIndicator *indicators = nullptr; // Object to get quality indicators + MapOfStringFunct parameters; // Operator parameters + if (argc>=2) + { + problem = ProblemFactory::getProblem(argc, argv); + std::cout << "Selected problem: " << problem->getName() << std::endl; + } + else + { + std::cout << "No problem selected." << std::endl; + std::cout << "Default problem will be used: Kursawe" << std::endl; + //problem = ProblemFactory::getProblem(const_cast("Kursawe")); + problem = snew BarrosF1F3("Real"); + } + //indicators = snew QualityIndicator(problem, "paretofront.txt"); + algorithm = snew SMPSO(problem); + int maxIterations = 100; + double perturbationIndex = 0.5; + double mutationProbability = 1.0 / problem->getNumberOfVariables(); + int swarmSize = 150; + int archiveSize = 100; + // Algorithm parameters + algorithm->setInputParameter("swarmSize",&swarmSize); + algorithm->setInputParameter("archiveSize",&archiveSize); + algorithm->setInputParameter("maxIterations",&maxIterations); + parameters["probability"] = &mutationProbability; + //parameters["perturbation"] = &perturbationIndex; + parameters["distributionIndex"] = &perturbationIndex; + //uniformMutation = snew UniformMutation(parameters); + uniformMutation = snew PolynomialMutation(parameters); + + parameters.clear(); + parameters["probability"] = &mutationProbability; + parameters["perturbation"] = &perturbationIndex; + parameters["maxIterations"] = &maxIterations; + nonUniformMutation = snew NonUniformMutation(parameters); + // Add the operators to the algorithm + algorithm->addOperator("mutation", uniformMutation); + //algorithm->addOperator("uniformMutation", uniformMutation); + //algorithm->addOperator("nonUniformMutation", nonUniformMutation); + // Execute the Algorithm + t_ini = clock(); + SolutionSet * population = algorithm->execute(); + t_fin = clock(); + double secs = (double) (t_fin - t_ini); + secs = secs / CLOCKS_PER_SEC; + // Print the results + std::cout << "Total execution time: " << secs << "s" << std::endl; + std::cout << "Variables values have been written to file VAR" << std::endl; + //population->printVariablesToFile("variables.txt"); + std::cout << "Objectives values have been written to file FUN" << std::endl; + population->printObjectivesToFile("objectives-" + problem->getName() + ".txt"); + if (indicators != nullptr) + { + std::cout << "Quality indicators" << std::endl ; + std::cout << "Hypervolume: " << indicators->getHypervolume(population) << std::endl; + std::cout << "GD : " << indicators->getGD(population) << std::endl ; + std::cout << "IGD : " << indicators->getIGD(population) << std::endl ; + std::cout << "Spread : " << indicators->getSpread(population) << std::endl ; + std::cout << "Epsilon : " << indicators->getEpsilon(population) << std::endl ; + } // if + delete uniformMutation; + delete nonUniformMutation; + delete population; + delete algorithm; } // main diff --git a/src/main/PAES_main.cpp b/src/main/PAES_main.cpp index e184078..3c9cc7d 100644 --- a/src/main/PAES_main.cpp +++ b/src/main/PAES_main.cpp @@ -29,72 +29,76 @@ #include #include -int main(int argc, char ** argv) { - - clock_t t_ini, t_fin; - Problem * problem ; // The problem to solve - Algorithm * algorithm ; // The algorithm to use - Operator * mutation ; // Mutation operator - - if (argc>=2) { - problem = ProblemFactory::getProblem(argc, argv); - cout << "Selected problem: " << problem->getName() << endl; - } else { - cout << "No problem selected." << endl; - cout << "Default problem will be used: Fonseca" << endl; - problem = ProblemFactory::getProblem(const_cast("Fonseca")); - } - - //QualityIndicator indicators ; // Object to get quality indicators - - algorithm = new paes(problem); - - // Algorithm parameters - int archiveSizeValue = 100; - int *archiveSizePtr = &archiveSizeValue; - int biSectionsValue = 5; - int *biSectionsPtr = &biSectionsValue; - int maxEvaluationsValue = 25000; - int *maxEvaluationsPtr = &maxEvaluationsValue; - - algorithm->setInputParameter("archiveSize",archiveSizePtr); - algorithm->setInputParameter("biSections",biSectionsPtr); - algorithm->setInputParameter("maxEvaluations",maxEvaluationsPtr); - - // Mutation (Real variables) - map parameters; // Operator parameters - parameters.clear(); - double probabilityValue1 = 1.0/problem->getNumberOfVariables(); - double *probabilityPtr1 = &probabilityValue1; - double distributionIndexValue1 = 20.0; - double *distributionIndexPtr1 = &distributionIndexValue1; - parameters["probability"] = probabilityPtr1 ; - parameters["distributionIndex"] = distributionIndexPtr1 ; - mutation = new PolynomialMutation(parameters); - - // Mutation (BinaryReal variables) - //mutation = MutationFactory.getMutationOperator("BitFlipMutation"); - //mutation.setParameter("probability",0.1); - algorithm->addOperator("mutation",mutation); - - // Checking parameters - //cout << "PolynomialMutation:" << endl; - //cout << *(double *) algorithm->getOperator("mutation")->getParameter("probability") << endl; - //cout << *(double *) algorithm->getOperator("mutation")->getParameter("distributionIndex") << endl; - - t_ini = clock(); - SolutionSet * population = algorithm->execute(); - t_fin = clock(); - double secs = (double) (t_fin - t_ini); - secs = secs / CLOCKS_PER_SEC; - - // Result messages - cout << "Total execution time: " << secs << "s" << endl; - cout << "Variables values have been writen to file VAR" << endl; - population->printVariablesToFile("VAR"); - cout << "Objectives values have been writen to file FUN" << endl; - population->printObjectivesToFile("FUN"); - +int main(int argc, char ** argv) +{ + + clock_t t_ini, t_fin; + Problem * problem ; // The problem to solve + Algorithm * algorithm ; // The algorithm to use + Operator * mutation ; // Mutation operator + + if (argc>=2) + { + problem = ProblemFactory::getProblem(argc, argv); + cout << "Selected problem: " << problem->getName() << endl; + } + else + { + cout << "No problem selected." << endl; + cout << "Default problem will be used: Fonseca" << endl; + problem = ProblemFactory::getProblem(const_cast("Fonseca")); + } + + //QualityIndicator indicators ; // Object to get quality indicators + + algorithm = new paes(problem); + + // Algorithm parameters + int archiveSizeValue = 100; + int *archiveSizePtr = &archiveSizeValue; + int biSectionsValue = 5; + int *biSectionsPtr = &biSectionsValue; + int maxEvaluationsValue = 25000; + int *maxEvaluationsPtr = &maxEvaluationsValue; + + algorithm->setInputParameter("archiveSize",archiveSizePtr); + algorithm->setInputParameter("biSections",biSectionsPtr); + algorithm->setInputParameter("maxEvaluations",maxEvaluationsPtr); + + // Mutation (Real variables) + map parameters; // Operator parameters + parameters.clear(); + double probabilityValue1 = 1.0/problem->getNumberOfVariables(); + double *probabilityPtr1 = &probabilityValue1; + double distributionIndexValue1 = 20.0; + double *distributionIndexPtr1 = &distributionIndexValue1; + parameters["probability"] = probabilityPtr1 ; + parameters["distributionIndex"] = distributionIndexPtr1 ; + mutation = new PolynomialMutation(parameters); + + // Mutation (BinaryReal variables) + //mutation = MutationFactory.getMutationOperator("BitFlipMutation"); + //mutation.setParameter("probability",0.1); + algorithm->addOperator("mutation",mutation); + + // Checking parameters + //cout << "PolynomialMutation:" << endl; + //cout << *(double *) algorithm->getOperator("mutation")->getParameter("probability") << endl; + //cout << *(double *) algorithm->getOperator("mutation")->getParameter("distributionIndex") << endl; + + t_ini = clock(); + SolutionSet * population = algorithm->execute(); + t_fin = clock(); + double secs = (double) (t_fin - t_ini); + secs = secs / CLOCKS_PER_SEC; + + // Result messages + cout << "Total execution time: " << secs << "s" << endl; + cout << "Variables values have been writen to file VAR" << endl; + population->printVariablesToFile("VAR"); + cout << "Objectives values have been writen to file FUN" << endl; + population->printObjectivesToFile("FUN"); + // if (indicators != NULL) { // cout << "Quality indicators" << endl; // cout << "Hypervolume: " << indicators->getHypervolume(population) << endl; @@ -102,11 +106,11 @@ int main(int argc, char ** argv) { // cout << "IGD : " << indicators->getIGD(population) << endl; // cout << "Spread : " << indicators->getSpread(population) << endl; // cout << "Epsilon : " << indicators->getEpsilon(population) << endl; -// +// // int evaluations = *(int *) algorithm->getOutputParameter("evaluations");; // cout << "Speed : " << evaluations << " evaluations" << endl; // } // if - + } // main diff --git a/src/main/PSO_main.cpp b/src/main/PSO_main.cpp index 3e23431..dd78c7d 100644 --- a/src/main/PSO_main.cpp +++ b/src/main/PSO_main.cpp @@ -2,6 +2,7 @@ // // Author: // Esteban López-Camacho +// Sérgio Vieira // // Copyright (c) 2011 Antonio J. Nebro, Juan J. Durillo // @@ -27,58 +28,62 @@ #include #include -int main(int argc, char ** argv) { +int main(int argc, char ** argv) +{ - clock_t t_ini, t_fin; + clock_t t_ini, t_fin; - Problem * problem ; // The problem to solve - Algorithm * algorithm ; // The algorithm to use - Operator * mutation ; // Mutation operator + Problem * problem ; // The problem to solve + Algorithm * algorithm ; // The algorithm to use + Operator * mutation ; // Mutation operator - if (argc>=2) { - problem = ProblemFactory::getProblem(argc, argv); - cout << "Selected problem: " << problem->getName() << endl; - } else { - cout << "No problem selected." << endl; - cout << "Default problem will be used: Sphere" << endl; - problem = ProblemFactory::getProblem(const_cast("Sphere")); - } + if (argc>=2) + { + problem = ProblemFactory::getProblem(argc, argv); + cout << "Selected problem: " << problem->getName() << endl; + } + else + { + cout << "No problem selected." << endl; + cout << "Default problem will be used: Sphere" << endl; + problem = ProblemFactory::getProblem(const_cast("Sphere")); + } - algorithm = new PSO(problem); + algorithm = new PSO(problem); - // Algorithm parameters - int swarmSize = 50; - int maxIterations = 5000; - algorithm->setInputParameter("swarmSize",&swarmSize); - algorithm->setInputParameter("maxIterations",&maxIterations); + // Algorithm parameters + int swarmSize = 50; + int maxIterations = 5000; + algorithm->setInputParameter("swarmSize",&swarmSize); + algorithm->setInputParameter("maxIterations",&maxIterations); - // Mutation operator - map parameters; - double probability = 1.0/problem->getNumberOfVariables(); - double distributionIndex = 20.0; - parameters["probability"] = &probability; - parameters["distributionIndex"] = &distributionIndex; - mutation = new PolynomialMutation(parameters); + // Mutation operator + map parameters; + double probability = 1.0/problem->getNumberOfVariables(); + double distributionIndex = 20.0; + parameters["probability"] = &probability; + parameters["distributionIndex"] = &distributionIndex; + mutation = new PolynomialMutation(parameters); - // Add the operators to the algorithm - algorithm->addOperator("mutation",mutation); + // Add the operators to the algorithm + algorithm->addOperator("mutation",mutation); - // Execute the Algorithm - t_ini = clock(); - SolutionSet * population = algorithm->execute(); - t_fin = clock(); - double secs = (double) (t_fin - t_ini); - secs = secs / CLOCKS_PER_SEC; + // Execute the Algorithm + t_ini = clock(); + SolutionSet * population = algorithm->execute(); + t_fin = clock(); + double secs = (double) (t_fin - t_ini); + secs = secs / CLOCKS_PER_SEC; - // Result messages - cout << "Total execution time: " << secs << "s" << endl; - cout << "Variables values have been written to file VAR" << endl; - population->printVariablesToFile("VAR"); - cout << "Objectives values have been written to file FUN" << endl; - population->printObjectivesToFile("FUN"); + // Result messages + cout << "Total execution time: " << secs << "s" << endl; + cout << "Variables values have been written to file VAR" << endl; + population->printVariablesToFile("VAR"); + cout << "Objectives values have been written to file FUN" << endl; + population->printObjectivesToFile("FUN"); - delete mutation; - delete population; - delete algorithm; + delete mutation; + delete population; + delete algorithm; } // main diff --git a/src/main/SMPSO_main.cpp b/src/main/SMPSO_main.cpp index e21a78a..a667b48 100644 --- a/src/main/SMPSO_main.cpp +++ b/src/main/SMPSO_main.cpp @@ -2,6 +2,7 @@ // // Author: // Esteban López-Camacho +// Sérgio Vieira // // Copyright (c) 2011 Antonio J. Nebro, Juan J. Durillo // @@ -37,66 +38,70 @@ * (MCDM 2009), pp: 66-73. March 2009 */ -int main(int argc, char ** argv) { - - clock_t t_ini, t_fin; - - Problem * problem; // The problem to solve - Algorithm * algorithm; // The algorithm to use - Operator * mutation; // "Turbulence" operator - - map parameters; // Operator parameters - - //TODO: QualityIndicator * indicators; // Object to get quality indicators - - if (argc>=2) { - problem = ProblemFactory::getProblem(argc, argv); - cout << "Selected problem: " << problem->getName() << endl; - } else { - cout << "No problem selected." << endl; - cout << "Default problem will be used: Kursawe" << endl; - problem = ProblemFactory::getProblem(const_cast("Kursawe")); - } - - algorithm = new SMPSO(problem); - - // Algorithm parameters - int swarmSizeValue = 100; - int archiveSizeValue = 100; - int maxIterationsValue = 250; - algorithm->setInputParameter("swarmSize",&swarmSizeValue); - algorithm->setInputParameter("archiveSize",&archiveSizeValue); - algorithm->setInputParameter("maxIterations",&maxIterationsValue); - - // Mutation operator - double probabilityParameter = 1.0/(problem->getNumberOfVariables()); - double distributionIndexParameter = 20.0; - parameters["probability"] = &probabilityParameter; - parameters["distributionIndex"] = &distributionIndexParameter; - mutation = new PolynomialMutation(parameters); - - // Add the operators to the algorithm - algorithm->addOperator("mutation",mutation); - - // Add the indicator object to the algorithm - //algorithm->setInputParameter("indicators", indicators) ; - - // Execute the Algorithm - t_ini = clock(); - SolutionSet * population = algorithm->execute(); - t_fin = clock(); - double secs = (double) (t_fin - t_ini); - secs = secs / CLOCKS_PER_SEC; - - // Result messages - cout << "Total execution time: " << secs << "s" << endl; - cout << "Variables values have been written to file VAR" << endl; - population->printVariablesToFile("VAR"); - cout << "Objectives values have been written to file FUN" << endl; - population->printObjectivesToFile("FUN"); - - delete mutation; - delete population; - delete algorithm; +int main(int argc, char ** argv) +{ + + clock_t t_ini, t_fin; + + Problem * problem; // The problem to solve + Algorithm * algorithm; // The algorithm to use + Operator * mutation; // "Turbulence" operator + + map parameters; // Operator parameters + + //TODO: QualityIndicator * indicators; // Object to get quality indicators + + if (argc>=2) + { + problem = ProblemFactory::getProblem(argc, argv); + cout << "Selected problem: " << problem->getName() << endl; + } + else + { + cout << "No problem selected." << endl; + cout << "Default problem will be used: Kursawe" << endl; + problem = ProblemFactory::getProblem(const_cast("Kursawe")); + } + + algorithm = new SMPSO(problem); + + // Algorithm parameters + int swarmSizeValue = 100; + int archiveSizeValue = 100; + int maxIterationsValue = 250; + algorithm->setInputParameter("swarmSize",&swarmSizeValue); + algorithm->setInputParameter("archiveSize",&archiveSizeValue); + algorithm->setInputParameter("maxIterations",&maxIterationsValue); + + // Mutation operator + double probabilityParameter = 1.0/(problem->getNumberOfVariables()); + double distributionIndexParameter = 20.0; + parameters["probability"] = &probabilityParameter; + parameters["distributionIndex"] = &distributionIndexParameter; + mutation = new PolynomialMutation(parameters); + + // Add the operators to the algorithm + algorithm->addOperator("mutation",mutation); + + // Add the indicator object to the algorithm + //algorithm->setInputParameter("indicators", indicators) ; + + // Execute the Algorithm + t_ini = clock(); + SolutionSet * population = algorithm->execute(); + t_fin = clock(); + double secs = (double) (t_fin - t_ini); + secs = secs / CLOCKS_PER_SEC; + + // Result messages + cout << "Total execution time: " << secs << "s" << endl; + cout << "Variables values have been written to file VAR" << endl; + population->printVariablesToFile("VAR"); + cout << "Objectives values have been written to file FUN" << endl; + population->printObjectivesToFile("FUN"); + + delete mutation; + delete population; + delete algorithm; } // main diff --git a/src/main/SMPSOhv_main.cpp b/src/main/SMPSOhv_main.cpp index 0c96b80..aee4b86 100644 --- a/src/main/SMPSOhv_main.cpp +++ b/src/main/SMPSOhv_main.cpp @@ -2,6 +2,7 @@ // // Author: // Esteban López-Camacho +// Sérgio Vieira // // Copyright (c) 2014 Antonio J. Nebro // @@ -40,75 +41,80 @@ * IEEE Congress on Evolutionary Computation 2013: 3153-3160 */ -int main(int argc, char ** argv) { - - clock_t t_ini, t_fin; - - Problem *problem; // The problem to solve - Algorithm *algorithm; // The algorithm to use - Mutation *mutation; - - QualityIndicator *indicators ; // Object to get quality indicators - - map parameters; // Operator parameters - - indicators = NULL; - - if (argc>=2) { - problem = ProblemFactory::getProblem(argc, argv); - cout << "Selected problem: " << problem->getName() << endl; - } else { - cout << "No problem selected." << endl; - cout << "Default problem will be used: Kursawe" << endl; - problem = ProblemFactory::getProblem(const_cast("Kursawe")); - } - - algorithm = new SMPSOhv(problem); - - int maxIterations = 250; - int swarmSize = 100; - int archiveSize = 100; - - double distributionIndex = 20.0; - double mutationProbability = 1.0/problem->getNumberOfVariables(); - - // Algorithm parameters - algorithm->setInputParameter("swarmSize",&swarmSize); - algorithm->setInputParameter("archiveSize",&archiveSize); - algorithm->setInputParameter("maxIterations",&maxIterations); - - parameters["probability"] = &mutationProbability; - parameters["distributionIndex"] = &distributionIndex; - mutation = new PolynomialMutation(parameters); - - // Add the operators to the algorithm - algorithm->addOperator("mutation",mutation); - - // Execute the Algorithm - t_ini = clock(); - SolutionSet * population = algorithm->execute(); - t_fin = clock(); - double secs = (double) (t_fin - t_ini); - secs = secs / CLOCKS_PER_SEC; - - // Print the results - cout << "Total execution time: " << secs << "s" << endl; - cout << "Variables values have been written to file VAR" << endl; - population->printVariablesToFile("VAR"); - cout << "Objectives values have been written to file FUN" << endl; - population->printObjectivesToFile("FUN"); - - if (indicators != NULL) { - cout << "Quality indicators" << endl ; - cout << "Hypervolume: " << indicators->getHypervolume(population) << endl; - cout << "GD : " << indicators->getGD(population) << endl ; - cout << "IGD : " << indicators->getIGD(population) << endl ; - cout << "Spread : " << indicators->getSpread(population) << endl ; - cout << "Epsilon : " << indicators->getEpsilon(population) << endl ; - } // if - - delete mutation; - delete population; - delete algorithm; +int main(int argc, char ** argv) +{ + + clock_t t_ini, t_fin; + + Problem *problem; // The problem to solve + Algorithm *algorithm; // The algorithm to use + Mutation *mutation; + + QualityIndicator *indicators ; // Object to get quality indicators + + map parameters; // Operator parameters + + indicators = NULL; + + if (argc>=2) + { + problem = ProblemFactory::getProblem(argc, argv); + cout << "Selected problem: " << problem->getName() << endl; + } + else + { + cout << "No problem selected." << endl; + cout << "Default problem will be used: Kursawe" << endl; + problem = ProblemFactory::getProblem(const_cast("Kursawe")); + } + + algorithm = new SMPSOhv(problem); + + int maxIterations = 250; + int swarmSize = 100; + int archiveSize = 100; + + double distributionIndex = 20.0; + double mutationProbability = 1.0/problem->getNumberOfVariables(); + + // Algorithm parameters + algorithm->setInputParameter("swarmSize",&swarmSize); + algorithm->setInputParameter("archiveSize",&archiveSize); + algorithm->setInputParameter("maxIterations",&maxIterations); + + parameters["probability"] = &mutationProbability; + parameters["distributionIndex"] = &distributionIndex; + mutation = new PolynomialMutation(parameters); + + // Add the operators to the algorithm + algorithm->addOperator("mutation",mutation); + + // Execute the Algorithm + t_ini = clock(); + SolutionSet * population = algorithm->execute(); + t_fin = clock(); + double secs = (double) (t_fin - t_ini); + secs = secs / CLOCKS_PER_SEC; + + // Print the results + cout << "Total execution time: " << secs << "s" << endl; + cout << "Variables values have been written to file VAR" << endl; + population->printVariablesToFile("VAR"); + cout << "Objectives values have been written to file FUN" << endl; + population->printObjectivesToFile("FUN"); + + if (indicators != NULL) + { + cout << "Quality indicators" << endl ; + cout << "Hypervolume: " << indicators->getHypervolume(population) << endl; + cout << "GD : " << indicators->getGD(population) << endl ; + cout << "IGD : " << indicators->getIGD(population) << endl ; + cout << "Spread : " << indicators->getSpread(population) << endl ; + cout << "Epsilon : " << indicators->getEpsilon(population) << endl ; + } // if + + delete mutation; + delete population; + delete algorithm; } // main diff --git a/src/main/SMSEMOA_main.cpp b/src/main/SMSEMOA_main.cpp index cad8716..41f2992 100755 --- a/src/main/SMSEMOA_main.cpp +++ b/src/main/SMSEMOA_main.cpp @@ -32,88 +32,92 @@ -int main(int argc, char ** argv) { - - clock_t t_ini, t_fin; - - Problem * problem ; // The problem to solve - Algorithm * algorithm ; // The algorithm to use - Operator * crossover ; // Crossover operator - Operator * mutation ; // Mutation operator - Operator * selection ; // Selection operator - - if (argc>=2) { - problem = ProblemFactory::getProblem(argc, argv); - cout << "Selected problem: " << problem->getName() << endl; - } else { - cout << "No problem selected." << endl; - cout << "Default problem will be used: Fonseca" << endl; - problem = ProblemFactory::getProblem(const_cast("Fonseca")); - } - - //TODO: Quality Indicators - //QualityIndicator indicators ; // Object to get quality indicators - //indicators = null ; - - algorithm = new SMSEMOA(problem); - - // Algorithm parameters - int populationSize = 100; - int maxEvaluations = 25000; - double offset = 100; - - algorithm->setInputParameter("populationSize",&populationSize); - algorithm->setInputParameter("maxEvaluations",&maxEvaluations); - algorithm->setInputParameter("offset",&offset); - - // Mutation - map parameters; - double crossoverProbability = 0.9; - double crossoverDistributionIndex = 20.0; - parameters["probability"] = &crossoverProbability; - parameters["distributionIndex"] = &crossoverDistributionIndex; - crossover = new SBXCrossover(parameters); - - //Crossover - parameters.clear(); - double mutationProbability = 1.0/problem->getNumberOfVariables(); - double mutationDistributionIndex = 20.0; - parameters["probability"] = &mutationProbability; - parameters["distributionIndex"] = &mutationDistributionIndex; - mutation = new PolynomialMutation(parameters); - - // Selection Operator - parameters.clear(); - selection = new RandomSelection(parameters); - - // Add the operators to the algorithm - algorithm->addOperator("crossover",crossover); - algorithm->addOperator("mutation",mutation); - algorithm->addOperator("selection",selection); - - // Add the indicator object to the algorithm - //algorithm->setInputParameter("indicators", indicators) ; - - // Execute the Algorithm - t_ini = clock(); - - SolutionSet * population = algorithm->execute(); - - t_fin = clock(); - double secs = (double) (t_fin - t_ini); - secs = secs / CLOCKS_PER_SEC; - - // Result messages - cout << "Total execution time: " << secs << "s" << endl; - cout << "Variables values have been written to file VAR" << endl; - population->printVariablesToFile("VAR"); - cout << "Objectives values have been written to file FUN" << endl; - population->printObjectivesToFile("FUN"); - - delete mutation; - delete crossover; - delete selection; - delete population; - delete algorithm; +int main(int argc, char ** argv) +{ + + clock_t t_ini, t_fin; + + Problem * problem ; // The problem to solve + Algorithm * algorithm ; // The algorithm to use + Operator * crossover ; // Crossover operator + Operator * mutation ; // Mutation operator + Operator * selection ; // Selection operator + + if (argc>=2) + { + problem = ProblemFactory::getProblem(argc, argv); + cout << "Selected problem: " << problem->getName() << endl; + } + else + { + cout << "No problem selected." << endl; + cout << "Default problem will be used: Fonseca" << endl; + problem = ProblemFactory::getProblem(const_cast("Fonseca")); + } + + //TODO: Quality Indicators + //QualityIndicator indicators ; // Object to get quality indicators + //indicators = null ; + + algorithm = new SMSEMOA(problem); + + // Algorithm parameters + int populationSize = 100; + int maxEvaluations = 25000; + double offset = 100; + + algorithm->setInputParameter("populationSize",&populationSize); + algorithm->setInputParameter("maxEvaluations",&maxEvaluations); + algorithm->setInputParameter("offset",&offset); + + // Mutation + map parameters; + double crossoverProbability = 0.9; + double crossoverDistributionIndex = 20.0; + parameters["probability"] = &crossoverProbability; + parameters["distributionIndex"] = &crossoverDistributionIndex; + crossover = new SBXCrossover(parameters); + + //Crossover + parameters.clear(); + double mutationProbability = 1.0/problem->getNumberOfVariables(); + double mutationDistributionIndex = 20.0; + parameters["probability"] = &mutationProbability; + parameters["distributionIndex"] = &mutationDistributionIndex; + mutation = new PolynomialMutation(parameters); + + // Selection Operator + parameters.clear(); + selection = new RandomSelection(parameters); + + // Add the operators to the algorithm + algorithm->addOperator("crossover",crossover); + algorithm->addOperator("mutation",mutation); + algorithm->addOperator("selection",selection); + + // Add the indicator object to the algorithm + //algorithm->setInputParameter("indicators", indicators) ; + + // Execute the Algorithm + t_ini = clock(); + + SolutionSet * population = algorithm->execute(); + + t_fin = clock(); + double secs = (double) (t_fin - t_ini); + secs = secs / CLOCKS_PER_SEC; + + // Result messages + cout << "Total execution time: " << secs << "s" << endl; + cout << "Variables values have been written to file VAR" << endl; + population->printVariablesToFile("VAR"); + cout << "Objectives values have been written to file FUN" << endl; + population->printObjectivesToFile("FUN"); + + delete mutation; + delete crossover; + delete selection; + delete population; + delete algorithm; } // main diff --git a/src/main/StandardPSO2007_main.cpp b/src/main/StandardPSO2007_main.cpp index ddb0aeb..dcd53c8 100644 --- a/src/main/StandardPSO2007_main.cpp +++ b/src/main/StandardPSO2007_main.cpp @@ -2,6 +2,7 @@ // // Author: // Esteban López-Camacho +// Sérgio Vieira // Antonio J. Nebro // // Copyright (c) 2014 Antonio J. Nebro @@ -28,48 +29,52 @@ #include #include -int main(int argc, char ** argv) { +int main(int argc, char ** argv) +{ - clock_t t_ini, t_fin; + clock_t t_ini, t_fin; - Problem * problem ; // The problem to solve - Algorithm * algorithm ; // The algorithm to use - //Operator * mutation ; // "Turbulence" operator + Problem * problem ; // The problem to solve + Algorithm * algorithm ; // The algorithm to use + //Operator * mutation ; // "Turbulence" operator - if (argc>=2) { - problem = ProblemFactory::getProblem(argc, argv); - cout << "Selected problem: " << problem->getName() << endl; - } else { - cout << "No problem selected." << endl; - cout << "Default problem will be used: Sphere" << endl; - problem = ProblemFactory::getProblem(const_cast("Sphere")); - } + if (argc>=2) + { + problem = ProblemFactory::getProblem(argc, argv); + cout << "Selected problem: " << problem->getName() << endl; + } + else + { + cout << "No problem selected." << endl; + cout << "Default problem will be used: Sphere" << endl; + problem = ProblemFactory::getProblem(const_cast("Sphere")); + } - algorithm = new StandardPSO2007(problem); + algorithm = new StandardPSO2007(problem); - // Algorithm parameters - int swarmSize = 10 + (int) (2 * sqrt(problem->getNumberOfVariables())); - int maxIterations = 80000; - int numberOfParticlesToInform = 3; - algorithm->setInputParameter("swarmSize",&swarmSize); - algorithm->setInputParameter("maxIterations",&maxIterations); - algorithm->setInputParameter("numberOfParticlesToInform", &numberOfParticlesToInform); + // Algorithm parameters + int swarmSize = 10 + (int) (2 * sqrt(problem->getNumberOfVariables())); + int maxIterations = 80000; + int numberOfParticlesToInform = 3; + algorithm->setInputParameter("swarmSize",&swarmSize); + algorithm->setInputParameter("maxIterations",&maxIterations); + algorithm->setInputParameter("numberOfParticlesToInform", &numberOfParticlesToInform); - // Execute the Algorithm - t_ini = clock(); - SolutionSet * population = algorithm->execute(); - t_fin = clock(); - double secs = (double) (t_fin - t_ini); - secs = secs / CLOCKS_PER_SEC; + // Execute the Algorithm + t_ini = clock(); + SolutionSet * population = algorithm->execute(); + t_fin = clock(); + double secs = (double) (t_fin - t_ini); + secs = secs / CLOCKS_PER_SEC; - // Result messages - cout << "Total execution time: " << secs << "s" << endl; - cout << "Variables values have been written to file VAR" << endl; - population->printVariablesToFile("VAR"); - cout << "Objectives values have been written to file FUN" << endl; - population->printObjectivesToFile("FUN"); + // Result messages + cout << "Total execution time: " << secs << "s" << endl; + cout << "Variables values have been written to file VAR" << endl; + population->printVariablesToFile("VAR"); + cout << "Objectives values have been written to file FUN" << endl; + population->printObjectivesToFile("FUN"); - delete population; - delete algorithm; + delete population; + delete algorithm; } // main diff --git a/src/main/StandardPSO2011_main.cpp b/src/main/StandardPSO2011_main.cpp index 06401b8..58e1e3a 100644 --- a/src/main/StandardPSO2011_main.cpp +++ b/src/main/StandardPSO2011_main.cpp @@ -2,6 +2,7 @@ // // Author: // Esteban López-Camacho +// Sérgio Vieira // Antonio J. Nebro // // Copyright (c) 2014 Antonio J. Nebro @@ -28,48 +29,52 @@ #include #include -int main(int argc, char ** argv) { +int main(int argc, char ** argv) +{ - clock_t t_ini, t_fin; + clock_t t_ini, t_fin; - Problem * problem ; // The problem to solve - Algorithm * algorithm ; // The algorithm to use - //Operator * mutation ; // "Turbulence" operator + Problem * problem ; // The problem to solve + Algorithm * algorithm ; // The algorithm to use + //Operator * mutation ; // "Turbulence" operator - if (argc>=2) { - problem = ProblemFactory::getProblem(argc, argv); - cout << "Selected problem: " << problem->getName() << endl; - } else { - cout << "No problem selected." << endl; - cout << "Default problem will be used: Sphere" << endl; - problem = ProblemFactory::getProblem(const_cast("Sphere")); - } + if (argc>=2) + { + problem = ProblemFactory::getProblem(argc, argv); + cout << "Selected problem: " << problem->getName() << endl; + } + else + { + cout << "No problem selected." << endl; + cout << "Default problem will be used: Sphere" << endl; + problem = ProblemFactory::getProblem(const_cast("Sphere")); + } - algorithm = new StandardPSO2011(problem); + algorithm = new StandardPSO2011(problem); - // Algorithm parameters - int swarmSize = 100; - int maxIterations = 8000; - int numberOfParticlesToInform = 3; - algorithm->setInputParameter("swarmSize",&swarmSize); - algorithm->setInputParameter("maxIterations",&maxIterations); - algorithm->setInputParameter("numberOfParticlesToInform", &numberOfParticlesToInform); + // Algorithm parameters + int swarmSize = 100; + int maxIterations = 8000; + int numberOfParticlesToInform = 3; + algorithm->setInputParameter("swarmSize",&swarmSize); + algorithm->setInputParameter("maxIterations",&maxIterations); + algorithm->setInputParameter("numberOfParticlesToInform", &numberOfParticlesToInform); - // Execute the Algorithm - t_ini = clock(); - SolutionSet * population = algorithm->execute(); - t_fin = clock(); - double secs = (double) (t_fin - t_ini); - secs = secs / CLOCKS_PER_SEC; + // Execute the Algorithm + t_ini = clock(); + SolutionSet * population = algorithm->execute(); + t_fin = clock(); + double secs = (double) (t_fin - t_ini); + secs = secs / CLOCKS_PER_SEC; - // Result messages - cout << "Total execution time: " << secs << "s" << endl; - cout << "Variables values have been written to file VAR" << endl; - population->printVariablesToFile("VAR"); - cout << "Objectives values have been written to file FUN" << endl; - population->printObjectivesToFile("FUN"); + // Result messages + cout << "Total execution time: " << secs << "s" << endl; + cout << "Variables values have been written to file VAR" << endl; + population->printVariablesToFile("VAR"); + cout << "Objectives values have been written to file FUN" << endl; + population->printObjectivesToFile("FUN"); - delete population; - delete algorithm; + delete population; + delete algorithm; } // main diff --git a/src/main/gGA_main.cpp b/src/main/gGA_main.cpp index 2d36712..8742de1 100644 --- a/src/main/gGA_main.cpp +++ b/src/main/gGA_main.cpp @@ -29,78 +29,82 @@ #include #include -int main(int argc, char ** argv) { - - clock_t t_ini, t_fin; - - Problem * problem ; // The problem to solve - Algorithm * algorithm ; // The algorithm to use - Operator * crossover ; // Crossover operator - Operator * mutation ; // Mutation operator - Operator * selection ; // Selection operator - - if (argc>=2) { - problem = ProblemFactory::getProblem(argc, argv); - cout << "Selected problem: " << problem->getName() << endl; - } else { - cout << "No problem selected." << endl; - cout << "Default problem will be used: Sphere" << endl; - problem = ProblemFactory::getProblem(const_cast("Sphere")); - } - - algorithm = new gGA(problem); - - // Algorithm parameters - int populationSizeValue = 100; - int maxEvaluationsValue = 250000; - algorithm->setInputParameter("populationSize",&populationSizeValue); - algorithm->setInputParameter("maxEvaluations",&maxEvaluationsValue); - - // Mutation and Crossover for Real codification - map parameters; - double crossoverProbability = 0.9; - double distributionIndexValue1 = 20.0; - parameters["probability"] = &crossoverProbability ; - parameters["distributionIndex"] = &distributionIndexValue1 ; - crossover = new SBXCrossover(parameters); - - parameters.clear(); - double mutationProbability = 1.0/problem->getNumberOfVariables(); - double distributionIndexValue2 = 20.0; - parameters["probability"] = &mutationProbability; - parameters["distributionIndex"] = &distributionIndexValue2 ; - mutation = new PolynomialMutation(parameters); - - // Selection Operator - parameters.clear(); - selection = new BinaryTournament2(parameters) ; - - // Add the operators to the algorithm - algorithm->addOperator("crossover",crossover); - algorithm->addOperator("mutation",mutation); - algorithm->addOperator("selection",selection); - - // Add the indicator object to the algorithm - //algorithm->setInputParameter("indicators", indicators) ; - - // Execute the Algorithm - t_ini = clock(); - SolutionSet * population = algorithm->execute(); - t_fin = clock(); - double secs = (double) (t_fin - t_ini); - secs = secs / CLOCKS_PER_SEC; - - // Result messages - cout << "Total execution time: " << secs << "s" << endl; - cout << "Variables values have been written to file VAR" << endl; - population->printVariablesToFile("VAR"); - cout << "Objectives values have been written to file FUN" << endl; - population->printObjectivesToFile("FUN"); - - delete crossover; - delete mutation; - delete selection; - delete population; - delete algorithm; +int main(int argc, char ** argv) +{ + + clock_t t_ini, t_fin; + + Problem * problem ; // The problem to solve + Algorithm * algorithm ; // The algorithm to use + Operator * crossover ; // Crossover operator + Operator * mutation ; // Mutation operator + Operator * selection ; // Selection operator + + if (argc>=2) + { + problem = ProblemFactory::getProblem(argc, argv); + cout << "Selected problem: " << problem->getName() << endl; + } + else + { + cout << "No problem selected." << endl; + cout << "Default problem will be used: Sphere" << endl; + problem = ProblemFactory::getProblem(const_cast("Sphere")); + } + + algorithm = new gGA(problem); + + // Algorithm parameters + int populationSizeValue = 100; + int maxEvaluationsValue = 250000; + algorithm->setInputParameter("populationSize",&populationSizeValue); + algorithm->setInputParameter("maxEvaluations",&maxEvaluationsValue); + + // Mutation and Crossover for Real codification + map parameters; + double crossoverProbability = 0.9; + double distributionIndexValue1 = 20.0; + parameters["probability"] = &crossoverProbability ; + parameters["distributionIndex"] = &distributionIndexValue1 ; + crossover = new SBXCrossover(parameters); + + parameters.clear(); + double mutationProbability = 1.0/problem->getNumberOfVariables(); + double distributionIndexValue2 = 20.0; + parameters["probability"] = &mutationProbability; + parameters["distributionIndex"] = &distributionIndexValue2 ; + mutation = new PolynomialMutation(parameters); + + // Selection Operator + parameters.clear(); + selection = new BinaryTournament2(parameters) ; + + // Add the operators to the algorithm + algorithm->addOperator("crossover",crossover); + algorithm->addOperator("mutation",mutation); + algorithm->addOperator("selection",selection); + + // Add the indicator object to the algorithm + //algorithm->setInputParameter("indicators", indicators) ; + + // Execute the Algorithm + t_ini = clock(); + SolutionSet * population = algorithm->execute(); + t_fin = clock(); + double secs = (double) (t_fin - t_ini); + secs = secs / CLOCKS_PER_SEC; + + // Result messages + cout << "Total execution time: " << secs << "s" << endl; + cout << "Variables values have been written to file VAR" << endl; + population->printVariablesToFile("VAR"); + cout << "Objectives values have been written to file FUN" << endl; + population->printObjectivesToFile("FUN"); + + delete crossover; + delete mutation; + delete selection; + delete population; + delete algorithm; } // main diff --git a/src/main/gGAbin_main.cpp b/src/main/gGAbin_main.cpp index 7e9e0e2..b3951a8 100644 --- a/src/main/gGAbin_main.cpp +++ b/src/main/gGAbin_main.cpp @@ -30,90 +30,94 @@ #include #include -int main(int argc, char ** argv) { - - clock_t t_ini, t_fin; - - Problem * problem ; // The problem to solve - Algorithm * algorithm ; // The algorithm to use - Operator * crossover ; // Crossover operator - Operator * mutation ; // Mutation operator - Operator * selection ; // Selection operator - - if (argc>=2) { - problem = ProblemFactory::getProblem(argc, argv); - cout << "Selected problem: " << problem->getName() << endl; - } else { - - cout << "No problem selected." << endl; - cout << "Default problem will be used: OneMax" << endl; - - char ** argv = new char*[2]; - argv[0] = new char[3]; - strcpy(argv[0], "400"); - argv[1] = new char[1]; - strcpy(argv[1], "2"); - char * problemName = new char[6]; - strcpy(problemName, "OneMax"); - - problem = ProblemFactory::getProblem(problemName, 2, argv); - - delete argv[0]; - delete argv[1]; - delete [] argv; - delete problemName; - - } - - algorithm = new gGA(problem); - - // Algorithm parameters - int populationSize = 100; - int maxEvaluations = 25000; - algorithm->setInputParameter("populationSize",&populationSize); - algorithm->setInputParameter("maxEvaluations",&maxEvaluations); - - map parameters; - - // Mutation operator - parameters.clear(); - double mutationProbability = 1.0/problem->getNumberOfBits(); - parameters["probability"] = &mutationProbability; - mutation = new BitFlipMutation(parameters); - - // Crossover operator - parameters.clear(); - double crossoverProbability = 0.9; - parameters["probability"] = &crossoverProbability; - crossover = new SinglePointCrossover(parameters); - - // Selection Operator - parameters.clear(); - selection = new BinaryTournament2(parameters) ; - - // Add the operators to the algorithm - algorithm->addOperator("crossover",crossover); - algorithm->addOperator("mutation",mutation); - algorithm->addOperator("selection",selection); - - // Execute the Algorithm - t_ini = clock(); - SolutionSet * population = algorithm->execute(); - t_fin = clock(); - double secs = (double) (t_fin - t_ini); - secs = secs / CLOCKS_PER_SEC; - - // Result messages - cout << "Total execution time: " << secs << "s" << endl; - cout << "Variables values have been written to file VAR" << endl; - population->printVariablesToFile("VAR"); - cout << "Objectives values have been written to file FUN" << endl; - population->printObjectivesToFile("FUN"); - - delete selection; - delete mutation; - delete crossover; - delete population; - delete algorithm; +int main(int argc, char ** argv) +{ + + clock_t t_ini, t_fin; + + Problem * problem ; // The problem to solve + Algorithm * algorithm ; // The algorithm to use + Operator * crossover ; // Crossover operator + Operator * mutation ; // Mutation operator + Operator * selection ; // Selection operator + + if (argc>=2) + { + problem = ProblemFactory::getProblem(argc, argv); + cout << "Selected problem: " << problem->getName() << endl; + } + else + { + + cout << "No problem selected." << endl; + cout << "Default problem will be used: OneMax" << endl; + + char ** argv = new char*[2]; + argv[0] = new char[3]; + strcpy(argv[0], "400"); + argv[1] = new char[1]; + strcpy(argv[1], "2"); + char * problemName = new char[7]; + strcpy(problemName, "OneMax"); + + problem = ProblemFactory::getProblem(problemName, 2, argv); + + delete argv[0]; + delete argv[1]; + delete [] argv; + delete [] problemName; + + } + + algorithm = new gGA(problem); + + // Algorithm parameters + int populationSize = 100; + int maxEvaluations = 25000; + algorithm->setInputParameter("populationSize",&populationSize); + algorithm->setInputParameter("maxEvaluations",&maxEvaluations); + + map parameters; + + // Mutation operator + parameters.clear(); + double mutationProbability = 1.0/problem->getNumberOfBits(); + parameters["probability"] = &mutationProbability; + mutation = new BitFlipMutation(parameters); + + // Crossover operator + parameters.clear(); + double crossoverProbability = 0.9; + parameters["probability"] = &crossoverProbability; + crossover = new SinglePointCrossover(parameters); + + // Selection Operator + parameters.clear(); + selection = new BinaryTournament2(parameters) ; + + // Add the operators to the algorithm + algorithm->addOperator("crossover",crossover); + algorithm->addOperator("mutation",mutation); + algorithm->addOperator("selection",selection); + + // Execute the Algorithm + t_ini = clock(); + SolutionSet * population = algorithm->execute(); + t_fin = clock(); + double secs = (double) (t_fin - t_ini); + secs = secs / CLOCKS_PER_SEC; + + // Result messages + cout << "Total execution time: " << secs << "s" << endl; + cout << "Variables values have been written to file VAR" << endl; + population->printVariablesToFile("VAR"); + cout << "Objectives values have been written to file FUN" << endl; + population->printObjectivesToFile("FUN"); + + delete selection; + delete mutation; + delete crossover; + delete population; + delete algorithm; } // main diff --git a/src/main/ssGA_main.cpp b/src/main/ssGA_main.cpp index fc90c23..4a3d180 100644 --- a/src/main/ssGA_main.cpp +++ b/src/main/ssGA_main.cpp @@ -2,6 +2,7 @@ // // Author: // Esteban López-Camacho +// Sérgio Vieira // // Copyright (c) 2011 Antonio J. Nebro, Juan J. Durillo // @@ -30,77 +31,81 @@ #include #include -int main(int argc, char ** argv) { - - clock_t t_ini, t_fin; - - Problem * problem ; // The problem to solve - Algorithm * algorithm ; // The algorithm to use - Operator * crossover ; // Crossover operator - Operator * mutation ; // Mutation operator - Operator * selection ; // Selection operator - - if (argc>=2) { - problem = ProblemFactory::getProblem(argc, argv); - } else { - cout << "No problem selected." << endl; - cout << "Default problem will be used: Sphere" << endl; - problem = ProblemFactory::getProblem(const_cast("Sphere")); - } - - algorithm = new ssGA(problem); // Steady-state GA - - // Algorithm parameters - int populationSize = 100; - int maxEvaluations = 250000; - algorithm->setInputParameter("populationSize",&populationSize); - algorithm->setInputParameter("maxEvaluations",&maxEvaluations); - - // Mutation and Crossover for Real codification - map parameters; - double crossoverProbability = 0.9; - double distributionIndex1 = 20.0; - parameters["probability"] = &crossoverProbability ; - parameters["distributionIndex"] = &distributionIndex1 ; - crossover = new SBXCrossover(parameters); - - parameters.clear(); - double mutationProbability = 1.0/problem->getNumberOfVariables(); - double distributionIndex2 = 20.0; - parameters["probability"] = &mutationProbability; - parameters["distributionIndex"] = &distributionIndex2 ; - mutation = new PolynomialMutation(parameters); - - // Selection Operator - parameters.clear(); - selection = new BinaryTournament(parameters) ; - - // Add the operators to the algorithm - algorithm->addOperator("crossover",crossover); - algorithm->addOperator("mutation",mutation); - algorithm->addOperator("selection",selection); - - // Add the indicator object to the algorithm - //algorithm->setInputParameter("indicators", indicators) ; - - // Execute the Algorithm - t_ini = clock(); - SolutionSet * population = algorithm->execute(); - t_fin = clock(); - double secs = (double) (t_fin - t_ini); - secs = secs / CLOCKS_PER_SEC; - - // Result messages - cout << "Total execution time: " << secs << "s" << endl; - cout << "Variables values have been written to file VAR" << endl; - population->printVariablesToFile("VAR"); - cout << "Objectives values have been written to file FUN" << endl; - population->printObjectivesToFile("FUN"); - - delete crossover; - delete mutation; - delete selection; - delete population; - delete algorithm; +int main(int argc, char ** argv) +{ + + clock_t t_ini, t_fin; + + Problem * problem ; // The problem to solve + Algorithm * algorithm ; // The algorithm to use + Operator * crossover ; // Crossover operator + Operator * mutation ; // Mutation operator + Operator * selection ; // Selection operator + + if (argc>=2) + { + problem = ProblemFactory::getProblem(argc, argv); + } + else + { + cout << "No problem selected." << endl; + cout << "Default problem will be used: Sphere" << endl; + problem = ProblemFactory::getProblem(const_cast("Sphere")); + } + + algorithm = new ssGA(problem); // Steady-state GA + + // Algorithm parameters + int populationSize = 100; + int maxEvaluations = 250000; + algorithm->setInputParameter("populationSize",&populationSize); + algorithm->setInputParameter("maxEvaluations",&maxEvaluations); + + // Mutation and Crossover for Real codification + map parameters; + double crossoverProbability = 0.9; + double distributionIndex1 = 20.0; + parameters["probability"] = &crossoverProbability ; + parameters["distributionIndex"] = &distributionIndex1 ; + crossover = new SBXCrossover(parameters); + + parameters.clear(); + double mutationProbability = 1.0/problem->getNumberOfVariables(); + double distributionIndex2 = 20.0; + parameters["probability"] = &mutationProbability; + parameters["distributionIndex"] = &distributionIndex2 ; + mutation = new PolynomialMutation(parameters); + + // Selection Operator + parameters.clear(); + selection = new BinaryTournament(parameters) ; + + // Add the operators to the algorithm + algorithm->addOperator("crossover",crossover); + algorithm->addOperator("mutation",mutation); + algorithm->addOperator("selection",selection); + + // Add the indicator object to the algorithm + //algorithm->setInputParameter("indicators", indicators) ; + + // Execute the Algorithm + t_ini = clock(); + SolutionSet * population = algorithm->execute(); + t_fin = clock(); + double secs = (double) (t_fin - t_ini); + secs = secs / CLOCKS_PER_SEC; + + // Result messages + cout << "Total execution time: " << secs << "s" << endl; + cout << "Variables values have been written to file VAR" << endl; + population->printVariablesToFile("VAR"); + cout << "Objectives values have been written to file FUN" << endl; + population->printObjectivesToFile("FUN"); + + delete crossover; + delete mutation; + delete selection; + delete population; + delete algorithm; } // main diff --git a/src/main/ssNSGAII_main.cpp b/src/main/ssNSGAII_main.cpp index 40e0d38..63f5bbd 100644 --- a/src/main/ssNSGAII_main.cpp +++ b/src/main/ssNSGAII_main.cpp @@ -2,6 +2,7 @@ // // Author: // Esteban López-Camacho +// Sérgio Vieira // // Copyright (c) 2011 Antonio J. Nebro, Juan J. Durillo // @@ -41,83 +42,87 @@ * Genetic Algorithms" 5th International Conference, EMO 2009, pp: 183-197. * April 2009) */ -int main(int argc, char ** argv) { - - clock_t t_ini, t_fin; - - Problem * problem ; // The problem to solve - Algorithm * algorithm ; // The algorithm to use - Operator * crossover ; // Crossover operator - Operator * mutation ; // Mutation operator - Operator * selection ; // Selection operator - - if (argc>=2) { - problem = ProblemFactory::getProblem(argc, argv); - cout << "Selected problem: " << problem->getName() << endl; - } else { - cout << "No problem selected." << endl; - cout << "Default problem will be used: Fonseca" << endl; - problem = ProblemFactory::getProblem(const_cast("Fonseca")); - } - - //TODO: Quality Indicators - //QualityIndicator indicators ; // Object to get quality indicators - //indicators = null ; - - algorithm = new ssNSGAII(problem); - - // Algorithm parameters - int populationSize = 100; - int maxEvaluations = 25000; - algorithm->setInputParameter("populationSize",&populationSize); - algorithm->setInputParameter("maxEvaluations",&maxEvaluations); - - // Mutation and Crossover for Real codification - map parameters; - - double crossoverProbability = 0.9; - double crossoverDistributionIndex = 20.0; - parameters["probability"] = &crossoverProbability; - parameters["distributionIndex"] = &crossoverDistributionIndex; - crossover = new SBXCrossover(parameters); - - parameters.clear(); - double mutationProbability = 1.0/problem->getNumberOfVariables(); - double mutationDistributionIndex = 20.0; - parameters["probability"] = &mutationProbability; - parameters["distributionIndex"] = &mutationDistributionIndex; - mutation = new PolynomialMutation(parameters); - - // Selection Operator - parameters.clear(); - selection = new BinaryTournament2(parameters); - - // Add the operators to the algorithm - algorithm->addOperator("crossover",crossover); - algorithm->addOperator("mutation",mutation); - algorithm->addOperator("selection",selection); - - // Add the indicator object to the algorithm - //algorithm->setInputParameter("indicators", indicators) ; - - // Execute the Algorithm - t_ini = clock(); - SolutionSet * population = algorithm->execute(); - t_fin = clock(); - double secs = (double) (t_fin - t_ini); - secs = secs / CLOCKS_PER_SEC; - - // Result messages - cout << "Total execution time: " << secs << "s" << endl; - cout << "Variables values have been written to file VAR" << endl; - population->printVariablesToFile("VAR"); - cout << "Objectives values have been written to file FUN" << endl; - population->printObjectivesToFile("FUN"); - - delete selection; - delete mutation; - delete crossover; - delete population; - delete algorithm; +int main(int argc, char ** argv) +{ + + clock_t t_ini, t_fin; + + Problem * problem ; // The problem to solve + Algorithm * algorithm ; // The algorithm to use + Operator * crossover ; // Crossover operator + Operator * mutation ; // Mutation operator + Operator * selection ; // Selection operator + + if (argc>=2) + { + problem = ProblemFactory::getProblem(argc, argv); + cout << "Selected problem: " << problem->getName() << endl; + } + else + { + cout << "No problem selected." << endl; + cout << "Default problem will be used: Fonseca" << endl; + problem = ProblemFactory::getProblem(const_cast("Fonseca")); + } + + //TODO: Quality Indicators + //QualityIndicator indicators ; // Object to get quality indicators + //indicators = null ; + + algorithm = new ssNSGAII(problem); + + // Algorithm parameters + int populationSize = 100; + int maxEvaluations = 25000; + algorithm->setInputParameter("populationSize",&populationSize); + algorithm->setInputParameter("maxEvaluations",&maxEvaluations); + + // Mutation and Crossover for Real codification + map parameters; + + double crossoverProbability = 0.9; + double crossoverDistributionIndex = 20.0; + parameters["probability"] = &crossoverProbability; + parameters["distributionIndex"] = &crossoverDistributionIndex; + crossover = new SBXCrossover(parameters); + + parameters.clear(); + double mutationProbability = 1.0/problem->getNumberOfVariables(); + double mutationDistributionIndex = 20.0; + parameters["probability"] = &mutationProbability; + parameters["distributionIndex"] = &mutationDistributionIndex; + mutation = new PolynomialMutation(parameters); + + // Selection Operator + parameters.clear(); + selection = new BinaryTournament2(parameters); + + // Add the operators to the algorithm + algorithm->addOperator("crossover",crossover); + algorithm->addOperator("mutation",mutation); + algorithm->addOperator("selection",selection); + + // Add the indicator object to the algorithm + //algorithm->setInputParameter("indicators", indicators) ; + + // Execute the Algorithm + t_ini = clock(); + SolutionSet * population = algorithm->execute(); + t_fin = clock(); + double secs = (double) (t_fin - t_ini); + secs = secs / CLOCKS_PER_SEC; + + // Result messages + cout << "Total execution time: " << secs << "s" << endl; + cout << "Variables values have been written to file VAR" << endl; + population->printVariablesToFile("VAR"); + cout << "Objectives values have been written to file FUN" << endl; + population->printObjectivesToFile("FUN"); + + delete selection; + delete mutation; + delete crossover; + delete population; + delete algorithm; } // main diff --git a/src/metaheuristics/CMakeLists.txt b/src/metaheuristics/CMakeLists.txt new file mode 100644 index 0000000..1f8a9fe --- /dev/null +++ b/src/metaheuristics/CMakeLists.txt @@ -0,0 +1,9 @@ +add_subdirectory(gde3) +add_subdirectory(mochc) +add_subdirectory(moead) +add_subdirectory(nsgaII) +add_subdirectory(omopso) +add_subdirectory(paes) +add_subdirectory(singleObjective) +add_subdirectory(smpso) +add_subdirectory(smsemoa) \ No newline at end of file diff --git a/src/metaheuristics/gde3/CMakeLists.txt b/src/metaheuristics/gde3/CMakeLists.txt new file mode 100644 index 0000000..294ec59 --- /dev/null +++ b/src/metaheuristics/gde3/CMakeLists.txt @@ -0,0 +1,3 @@ +file(GLOB SOURCES "*.cpp" "*.h") +ListToString(SOURCES ";" ${SOURCES}) +LIST_APPEND("${SOURCES}") \ No newline at end of file diff --git a/src/metaheuristics/gde3/GDE3.cpp b/src/metaheuristics/gde3/GDE3.cpp index 9e97dd7..b99063a 100644 --- a/src/metaheuristics/gde3/GDE3.cpp +++ b/src/metaheuristics/gde3/GDE3.cpp @@ -2,6 +2,7 @@ // // Author: // Esteban López-Camacho +// Sérgio Vieira // // Copyright (c) 2011 Antonio J. Nebro, Juan J. Durillo // @@ -31,7 +32,8 @@ * Constructor * @param problem Problem to solve */ -GDE3::GDE3(Problem *problem) : Algorithm(problem) { +GDE3::GDE3(Problem *problem) : Algorithm(problem) +{ } // GDE3 @@ -40,161 +42,176 @@ GDE3::GDE3(Problem *problem) : Algorithm(problem) { * @return a SolutionSet that is a set of non dominated solutions * as a result of the algorithm execution */ -SolutionSet * GDE3::execute() { - - int populationSize; - int maxIterations; - int evaluations; - int iterations; - - SolutionSet * population; - SolutionSet * offspringPopulation; - - Distance * distance; - Comparator * dominance; - - Operator * crossoverOperator; - Operator * selectionOperator; - - distance = new Distance(); - dominance = new DominanceComparator(); - - Solution ** parent; - - //Read the parameters - populationSize = *(int *) getInputParameter("populationSize"); - maxIterations = *(int *) getInputParameter("maxIterations"); - - //Initialize the variables - population = new SolutionSet(populationSize); - evaluations = 0; - iterations = 0; - - //Read the operators - crossoverOperator = operators_["crossover"]; - selectionOperator = operators_["selection"]; - - // Create the initial solutionSet - Solution * newSolution; - for (int i = 0; i < populationSize; i++) { - newSolution = new Solution(problem_); - problem_->evaluate(newSolution); - problem_->evaluateConstraints(newSolution); - evaluations++; - population->add(newSolution); - } //for - - // Generations ... - while (iterations < maxIterations) { - // Create the offSpring solutionSet - offspringPopulation = new SolutionSet(populationSize * 2); - - for (int i = 0; i < populationSize; i++){ - // Obtain parents. Two parameters are required: the population and the - // index of the current individual - void ** object1 = new void*[2]; - object1[0] = population; - object1[1] = &i; - parent = (Solution **) (selectionOperator->execute(object1)); - delete[] object1; - - Solution * child ; - // Crossover. Two parameters are required: the current individual and the - // array of parents - void ** object2 = new void*[2]; - object2[0] = population->get(i); - object2[1] = parent; - child = (Solution *) (crossoverOperator->execute(object2)); - delete[] object2; - delete[] parent; - - problem_->evaluate(child) ; - problem_->evaluateConstraints(child); - evaluations++ ; - - // Dominance test - int result ; - result = dominance->compare(population->get(i), child) ; - if (result == -1) { // Solution i dominates child - offspringPopulation->add(new Solution(population->get(i))); - delete child; - } // if - else if (result == 1) { // child dominates - offspringPopulation->add(child) ; - } // else if - else { // the two solutions are non-dominated - offspringPopulation->add(child) ; - offspringPopulation->add(new Solution(population->get(i))); - } // else - } // for - - // Ranking the offspring population - Ranking * ranking = new Ranking(offspringPopulation); - - int remain = populationSize; - int index = 0; - SolutionSet * front = NULL; - for (int i = 0; i < populationSize; i++) { - delete population->get(i); - } - population->clear(); - - // Obtain the next front - front = ranking->getSubfront(index); - - while ((remain > 0) && (remain >= front->size())){ - //Assign crowding distance to individuals - distance->crowdingDistanceAssignment(front,problem_->getNumberOfObjectives()); - //Add the individuals of this front - for (int k = 0; k < front->size(); k++ ) { - population->add(new Solution(front->get(k))); - } // for - - //Decrement remain - remain = remain - front->size(); - - //Obtain the next front - index++; - if (remain > 0) { +SolutionSet * GDE3::execute() +{ + + int populationSize; + int maxIterations; + int evaluations; + int iterations; + + SolutionSet * population; + SolutionSet * offspringPopulation; + + Distance * distance; + Comparator * dominance; + + Operator * crossoverOperator; + Operator * selectionOperator; + + distance = snew Distance(); + dominance = snew DominanceComparator(); + + Solution ** parent; + + //Read the parameters + populationSize = *(int *) getInputParameter("populationSize"); + maxIterations = *(int *) getInputParameter("maxIterations"); + + //Initialize the variables + population = snew SolutionSet(populationSize); + evaluations = 0; + iterations = 0; + + //Read the operators + crossoverOperator = operators_["crossover"]; + selectionOperator = operators_["selection"]; + + // Create the initial solutionSet + Solution * newSolution; + for (int i = 0; i < populationSize; i++) + { + newSolution = snew Solution(problem_); + problem_->evaluate(newSolution); + problem_->evaluateConstraints(newSolution); + evaluations++; + population->add(newSolution); + } //for + + // Generations ... + while (iterations < maxIterations) + { + // Create the offSpring solutionSet + offspringPopulation = snew SolutionSet(populationSize * 2); + + for (int i = 0; i < populationSize; i++) + { + // Obtain parents. Two parameters are required: the population and the + // index of the current individual + void ** object1 = snew void*[2]; + object1[0] = population; + object1[1] = &i; + parent = (Solution **) (selectionOperator->execute(object1)); + delete[] object1; + + Solution * child ; + // Crossover. Two parameters are required: the current individual and the + // array of parents + void ** object2 = snew void*[2]; + object2[0] = population->get(i); + object2[1] = parent; + child = (Solution *) (crossoverOperator->execute(object2)); + delete[] object2; + delete[] parent; + + problem_->evaluate(child) ; + problem_->evaluateConstraints(child); + evaluations++ ; + + // Dominance test + int result ; + result = dominance->compare(population->get(i), child) ; + if (result == -1) // Solution i dominates child + { + offspringPopulation->add(snew Solution(population->get(i))); + delete child; + } // if + else if (result == 1) // child dominates + { + offspringPopulation->add(child) ; + } // else if + else // the two solutions are non-dominated + { + offspringPopulation->add(child) ; + offspringPopulation->add(snew Solution(population->get(i))); + } // else + } // for + + // Ranking the offspring population + Ranking * ranking = snew Ranking(offspringPopulation); + + int remain = populationSize; + int index = 0; + SolutionSet * front = nullptr; + for (int i = 0; i < populationSize; i++) + { + delete population->get(i); + } + population->clear(); + + // Obtain the next front front = ranking->getSubfront(index); - } // if + + while ((remain > 0) && (remain >= front->size())) + { + //Assign crowding distance to individuals + distance->crowdingDistanceAssignment(front,problem_->getNumberOfObjectives()); + //Add the individuals of this front + for (int k = 0; k < front->size(); k++ ) + { + population->add(snew Solution(front->get(k))); + } // for + + //Decrement remain + remain = remain - front->size(); + + //Obtain the next front + index++; + if (remain > 0) + { + front = ranking->getSubfront(index); + } // if + } // while + + // remain is less than front(index).size, insert only the best one + if (remain > 0) // front contains individuals to insert + { + while (front->size() > remain) + { + distance->crowdingDistanceAssignment(front,problem_->getNumberOfObjectives()); + Comparator * crowdingComparator = snew CrowdingComparator(); + int indexWorst = front->indexWorst(crowdingComparator); + delete crowdingComparator; + delete front->get(indexWorst); + front->remove(indexWorst); + } + for (int k = 0; k < front->size(); k++) + { + population->add(snew Solution(front->get(k))); + } + + remain = 0; + } // if + + delete ranking; + delete offspringPopulation; + + iterations ++ ; } // while - // remain is less than front(index).size, insert only the best one - if (remain > 0) { // front contains individuals to insert - while (front->size() > remain) { - distance->crowdingDistanceAssignment(front,problem_->getNumberOfObjectives()); - Comparator * crowdingComparator = new CrowdingComparator(); - int indexWorst = front->indexWorst(crowdingComparator); - delete crowdingComparator; - delete front->get(indexWorst); - front->remove(indexWorst); - } - for (int k = 0; k < front->size(); k++) { - population->add(new Solution(front->get(k))); - } - - remain = 0; - } // if + delete dominance; + delete distance; + // Return the first non-dominated front + Ranking * ranking = snew Ranking(population); + SolutionSet * result = snew SolutionSet(ranking->getSubfront(0)->size()); + for (int i=0; igetSubfront(0)->size(); i++) + { + result->add(snew Solution(ranking->getSubfront(0)->get(i))); + } delete ranking; - delete offspringPopulation; - - iterations ++ ; - } // while - - delete dominance; - delete distance; - - // Return the first non-dominated front - Ranking * ranking = new Ranking(population); - SolutionSet * result = new SolutionSet(ranking->getSubfront(0)->size()); - for (int i=0;igetSubfront(0)->size();i++) { - result->add(new Solution(ranking->getSubfront(0)->get(i))); - } - delete ranking; - delete population; + delete population; - return result; + return result; } // execute diff --git a/src/metaheuristics/gde3/GDE3.h b/src/metaheuristics/gde3/GDE3.h index f1526c8..d379d1b 100644 --- a/src/metaheuristics/gde3/GDE3.h +++ b/src/metaheuristics/gde3/GDE3.h @@ -2,6 +2,7 @@ // // Author: // Esteban López-Camacho +// Sérgio Vieira // // Copyright (c) 2011 Antonio J. Nebro, Juan J. Durillo // @@ -33,14 +34,15 @@ * @brief This class implements the GDE3 algorithm. **/ -class GDE3 : public Algorithm { +class GDE3 : public Algorithm +{ private: - int populationSize_; - int maxEvaluations_; - //QualityIndicator *indicators_; + int populationSize_; + int maxEvaluations_; + //QualityIndicator *indicators_; public: - GDE3(Problem * problem); - SolutionSet * execute(); + GDE3(Problem * problem); + SolutionSet * execute(); }; #endif /* __GDE3__ */ diff --git a/src/metaheuristics/mochc/CMakeLists.txt b/src/metaheuristics/mochc/CMakeLists.txt new file mode 100644 index 0000000..294ec59 --- /dev/null +++ b/src/metaheuristics/mochc/CMakeLists.txt @@ -0,0 +1,3 @@ +file(GLOB SOURCES "*.cpp" "*.h") +ListToString(SOURCES ";" ${SOURCES}) +LIST_APPEND("${SOURCES}") \ No newline at end of file diff --git a/src/metaheuristics/mochc/MOCHC.cpp b/src/metaheuristics/mochc/MOCHC.cpp index 64a0f09..2851ed5 100644 --- a/src/metaheuristics/mochc/MOCHC.cpp +++ b/src/metaheuristics/mochc/MOCHC.cpp @@ -20,231 +20,258 @@ // #include -bool MOCHC::equalsIndividuals(Solution & s1, Solution & s2) { - - for (int var = 0; var < s1.getNumberOfVariables(); var++) { - Binary *b1, *b2; - b1 = (Binary *)s1.getDecisionVariables()[var]; - b2 = (Binary *)s2.getDecisionVariables()[var]; - bool found = true; - for (int bit = 0; bit < b1->getNumberOfBits(); bit++) { - if (b1->getIth(bit)!=b2->getIth(bit)) { - return false; - } - } - } - - return true; +bool MOCHC::equalsIndividuals(Solution & s1, Solution & s2) +{ + + for (int var = 0; var < s1.getNumberOfVariables(); var++) + { + Binary *b1, *b2; + b1 = (Binary *)s1.getDecisionVariables()[var]; + b2 = (Binary *)s2.getDecisionVariables()[var]; + bool found = true; + for (int bit = 0; bit < b1->getNumberOfBits(); bit++) + { + if (b1->getIth(bit)!=b2->getIth(bit)) + { + return false; + } + } + } + + return true; } -bool MOCHC::exist(Solution & s1, SolutionSet & set2) { - for (int i = 0; i < set2.size(); i++) { - if (equalsIndividuals(s1,*set2.get(i))) - return true; - } - return false; +bool MOCHC::exist(Solution & s1, SolutionSet & set2) +{ + for (int i = 0; i < set2.size(); i++) + { + if (equalsIndividuals(s1,*set2.get(i))) + return true; + } + return false; } -bool MOCHC::equals(SolutionSet & set1, SolutionSet & set2) { +bool MOCHC::equals(SolutionSet & set1, SolutionSet & set2) +{ - if (set1.size() != set2.size()) - return false; + if (set1.size() != set2.size()) + return false; - for (int i = 0; i < set1.size(); i++) { - if (!exist(*set1.get(i),set2)) - return false; - } - return true; + for (int i = 0; i < set1.size(); i++) + { + if (!exist(*set1.get(i),set2)) + return false; + } + return true; } // returns the equal -int MOCHC::hammingDistance(Solution & sol1, Solution & sol2) { - int distance = 0; - for (int i = 0; i < problem_->getNumberOfVariables(); i++) { - Binary *varFrom1, *varFrom2; - varFrom1 = (Binary *)sol1.getDecisionVariables()[i]; - varFrom2 = (Binary *)sol2.getDecisionVariables()[i]; - distance += varFrom1->hammingDistance(varFrom2); - } - return distance; +int MOCHC::hammingDistance(Solution & sol1, Solution & sol2) +{ + int distance = 0; + for (int i = 0; i < problem_->getNumberOfVariables(); i++) + { + Binary *varFrom1, *varFrom2; + varFrom1 = (Binary *)sol1.getDecisionVariables()[i]; + varFrom2 = (Binary *)sol2.getDecisionVariables()[i]; + distance += varFrom1->hammingDistance(varFrom2); + } + return distance; } -SolutionSet *MOCHC::rankingAndCrowdingSelection(SolutionSet * pop, int size) { +SolutionSet *MOCHC::rankingAndCrowdingSelection(SolutionSet * pop, int size) +{ - SolutionSet *result = new SolutionSet(size); + SolutionSet *result = snew SolutionSet(size); // Ranking the union - Ranking * ranking = new Ranking(pop); - Distance * distance = new Distance(); + Ranking * ranking = snew Ranking(pop); + Distance * distance = snew Distance(); int remain = size; int index = 0; - SolutionSet * front = NULL; + SolutionSet * front = nullptr; // Obtain the next front front = ranking->getSubfront(index); - while ((remain > 0) && (remain >= front->size())) { - //Assign crowding distance to individuals - distance->crowdingDistanceAssignment(front, problem_->getNumberOfObjectives()); + while ((remain > 0) && (remain >= front->size())) + { + //Assign crowding distance to individuals + distance->crowdingDistanceAssignment(front, problem_->getNumberOfObjectives()); - //Add the individuals of this front - for (int k = 0; k < front->size(); k++) { - result->add(new Solution(front->get(k))); - } // for + //Add the individuals of this front + for (int k = 0; k < front->size(); k++) + { + result->add(snew Solution(front->get(k))); + } // for - //Decrement remain - remain = remain - front->size(); + //Decrement remain + remain = remain - front->size(); + + //Obtain the next front + index++; + if (remain > 0) + { + front = ranking->getSubfront(index); + } // if - //Obtain the next front - index++; - if (remain > 0) { - front = ranking->getSubfront(index); - } // if - } // while // Remain is less than front(index).size, insert only the best one - if (remain > 0) { // front contains individuals to insert - distance->crowdingDistanceAssignment(front, problem_->getNumberOfObjectives()); - Comparator * c = new CrowdingComparator(); - front->sort(c); - delete c; - for (int k = 0; k < remain; k++) { - result->add(new Solution(front->get(k))); - } // for - - remain = 0; + if (remain > 0) // front contains individuals to insert + { + distance->crowdingDistanceAssignment(front, problem_->getNumberOfObjectives()); + Comparator * c = snew CrowdingComparator(); + front->sort(c); + delete c; + for (int k = 0; k < remain; k++) + { + result->add(snew Solution(front->get(k))); + } // for + + remain = 0; } // if delete ranking; delete distance; - return result; + return result; } -SolutionSet *MOCHC::execute() { - - int populationSize; - int iterations; - int maxEvaluations; - int convergenceValue; - int minimumDistance; - int evaluations; - - double preservedPopulation; - double initialConvergenceCount; - bool condition = false; - SolutionSet *solutionSet, *offSpringPopulation, *newPopulation; - - Comparator * crowdingComparator = new CrowdingComparator(); - - SolutionSet * population; - SolutionSet * offspringPopulation; - SolutionSet * unionSolution; - - Operator * cataclysmicMutation; - Operator * crossover; - Operator * parentSelection; - - - //Read the parameters - populationSize = *(int *) getInputParameter("populationSize"); - maxEvaluations = *(int *) getInputParameter("maxEvaluations"); - convergenceValue = *(int *) getInputParameter("convergenceValue"); - initialConvergenceCount = *(double *)getInputParameter("initialConvergenceCount"); - preservedPopulation = *(double *)getInputParameter("preservedPopulation"); - - - //Read the operators - cataclysmicMutation = operators_["mutation"]; - crossover = operators_["crossover"]; - parentSelection = operators_["parentSelection"]; - - iterations = 0; - evaluations = 0; - - // calculating the maximum problem sizes .... - Solution * sol = new Solution(problem_); - int size = 0; - for (int var = 0; var < problem_->getNumberOfVariables(); var++) { - Binary *binaryVar; +SolutionSet *MOCHC::execute() +{ + + int populationSize; + int iterations; + int maxEvaluations; + int convergenceValue; + int minimumDistance; + int evaluations; + + double preservedPopulation; + double initialConvergenceCount; + bool condition = false; + SolutionSet *solutionSet, *offSpringPopulation, *newPopulation; + + Comparator * crowdingComparator = snew CrowdingComparator(); + + SolutionSet * population; + SolutionSet * offspringPopulation; + SolutionSet * unionSolution; + + Operator * cataclysmicMutation; + Operator * crossover; + Operator * parentSelection; + + + //Read the parameters + populationSize = *(int *) getInputParameter("populationSize"); + maxEvaluations = *(int *) getInputParameter("maxEvaluations"); + convergenceValue = *(int *) getInputParameter("convergenceValue"); + initialConvergenceCount = *(double *)getInputParameter("initialConvergenceCount"); + preservedPopulation = *(double *)getInputParameter("preservedPopulation"); + + + //Read the operators + cataclysmicMutation = operators_["mutation"]; + crossover = operators_["crossover"]; + parentSelection = operators_["parentSelection"]; + + iterations = 0; + evaluations = 0; + + // calculating the maximum problem sizes .... + Solution * sol = snew Solution(problem_); + int size = 0; + for (int var = 0; var < problem_->getNumberOfVariables(); var++) + { + Binary *binaryVar; binaryVar = (Binary *)sol->getDecisionVariables()[var]; - size += binaryVar->getNumberOfBits(); - } - minimumDistance = (int) std::floor(initialConvergenceCount*size); - std::cout << minimumDistance << std::endl; - std::cout << convergenceValue << std::endl; - - // Create the initial solutionSet - Solution * newSolution; - population = new SolutionSet(populationSize); - for (int i = 0; i < populationSize; i++) { - newSolution = new Solution(problem_); - problem_->evaluate(newSolution); - problem_->evaluateConstraints(newSolution); - evaluations++; - population->add(newSolution); - } //for - - - while (!condition) { - offSpringPopulation = new SolutionSet(populationSize); - Solution **parents = new Solution*[2]; - - for (int i = 0; i < population->size()/2; i++) { - parents[0] = (Solution *) (parentSelection->execute(population)); - parents[1] = (Solution *) (parentSelection->execute(population)); - - if (hammingDistance(*parents[0],*parents[1])>= minimumDistance) { - Solution ** offSpring = (Solution **) (crossover->execute(parents)); - problem_->evaluate(offSpring[0]); - problem_->evaluateConstraints(offSpring[0]); - problem_->evaluate(offSpring[1]); - problem_->evaluateConstraints(offSpring[1]); - evaluations+=2; - offSpringPopulation->add(offSpring[0]); - offSpringPopulation->add(offSpring[1]); - } - } - SolutionSet *join = population->join(offSpringPopulation); - delete offSpringPopulation; - - newPopulation = rankingAndCrowdingSelection(join,populationSize); - delete join; - if (equals(*population,*newPopulation)) { - std::cout << "populations are equals" << std::endl; - minimumDistance--; - } - - if (minimumDistance <= -convergenceValue) { - minimumDistance = (int) (1.0/size * (1-1.0/size) * size); - int preserve = (int) std::floor(preservedPopulation*populationSize); - newPopulation->clear(); //do the new in c++ really hurts me(juanjo) - population->sort(crowdingComparator); - for (int i = 0; i < preserve; i++) { - newPopulation->add(new Solution(population->get(i))); - } - for (int i = preserve; i < populationSize; i++) { - Solution * solution = new Solution(population->get(i)); - cataclysmicMutation->execute(solution); - problem_->evaluate(solution); - problem_->evaluateConstraints(solution); - newPopulation->add(solution); - } - - } - - iterations++; - delete population; - population = newPopulation; - if (evaluations >= maxEvaluations) { - condition = true; - } - } - - return population; + size += binaryVar->getNumberOfBits(); + } + minimumDistance = (int) std::floor(initialConvergenceCount*size); + std::cout << minimumDistance << std::endl; + std::cout << convergenceValue << std::endl; + + // Create the initial solutionSet + Solution * newSolution; + population = snew SolutionSet(populationSize); + for (int i = 0; i < populationSize; i++) + { + newSolution = snew Solution(problem_); + problem_->evaluate(newSolution); + problem_->evaluateConstraints(newSolution); + evaluations++; + population->add(newSolution); + } //for + + + while (!condition) + { + offSpringPopulation = snew SolutionSet(populationSize); + Solution **parents = snew Solution*[2]; + + for (int i = 0; i < population->size()/2; i++) + { + parents[0] = (Solution *) (parentSelection->execute(population)); + parents[1] = (Solution *) (parentSelection->execute(population)); + + if (hammingDistance(*parents[0],*parents[1])>= minimumDistance) + { + Solution ** offSpring = (Solution **) (crossover->execute(parents)); + problem_->evaluate(offSpring[0]); + problem_->evaluateConstraints(offSpring[0]); + problem_->evaluate(offSpring[1]); + problem_->evaluateConstraints(offSpring[1]); + evaluations+=2; + offSpringPopulation->add(offSpring[0]); + offSpringPopulation->add(offSpring[1]); + } + } + SolutionSet *join = population->join(offSpringPopulation); + delete offSpringPopulation; + + newPopulation = rankingAndCrowdingSelection(join,populationSize); + delete join; + if (equals(*population,*newPopulation)) + { + std::cout << "populations are equals" << std::endl; + minimumDistance--; + } + + if (minimumDistance <= -convergenceValue) + { + minimumDistance = (int) (1.0/size * (1-1.0/size) * size); + int preserve = (int) std::floor(preservedPopulation*populationSize); + newPopulation->clear(); //do the new in c++ really hurts me(juanjo) + population->sort(crowdingComparator); + for (int i = 0; i < preserve; i++) + { + newPopulation->add(snew Solution(population->get(i))); + } + for (int i = preserve; i < populationSize; i++) + { + Solution * solution = snew Solution(population->get(i)); + cataclysmicMutation->execute(solution); + problem_->evaluate(solution); + problem_->evaluateConstraints(solution); + newPopulation->add(solution); + } + + } + + iterations++; + delete population; + population = newPopulation; + if (evaluations >= maxEvaluations) + { + condition = true; + } + } + + return population; } diff --git a/src/metaheuristics/mochc/MOCHC.h b/src/metaheuristics/mochc/MOCHC.h index e1d5f13..adcffe4 100644 --- a/src/metaheuristics/mochc/MOCHC.h +++ b/src/metaheuristics/mochc/MOCHC.h @@ -31,21 +31,22 @@ #include #include #include -// Juanjo: I am following the same sintax as in the other algorithms. +// Juanjo: I am following the same sintax as in the other algorithms. // however, I would never ever program like this in C++ // I would recommend to use something as MOCHC(Problem &) -class MOCHC : public Algorithm { +class MOCHC : public Algorithm +{ - bool equalsIndividuals(Solution &s1, Solution & s2); - bool exist(Solution &s1, SolutionSet &set2); - bool equals(SolutionSet& set1, SolutionSet& set2); - int hammingDistance(Solution &sol1, Solution& sol2); - SolutionSet *rankingAndCrowdingSelection(SolutionSet *sol,int size); + bool equalsIndividuals(Solution &s1, Solution & s2); + bool exist(Solution &s1, SolutionSet &set2); + bool equals(SolutionSet& set1, SolutionSet& set2); + int hammingDistance(Solution &sol1, Solution& sol2); + SolutionSet *rankingAndCrowdingSelection(SolutionSet *sol,int size); public: - MOCHC(Problem * problem) : Algorithm(problem){}; - SolutionSet *execute(); + MOCHC(Problem * problem) : Algorithm(problem) {}; + SolutionSet *execute(); }; diff --git a/src/metaheuristics/moead/CMakeLists.txt b/src/metaheuristics/moead/CMakeLists.txt new file mode 100644 index 0000000..294ec59 --- /dev/null +++ b/src/metaheuristics/moead/CMakeLists.txt @@ -0,0 +1,3 @@ +file(GLOB SOURCES "*.cpp" "*.h") +ListToString(SOURCES ";" ${SOURCES}) +LIST_APPEND("${SOURCES}") \ No newline at end of file diff --git a/src/metaheuristics/moead/MOEAD.cpp b/src/metaheuristics/moead/MOEAD.cpp index f38144e..9a3ef3c 100644 --- a/src/metaheuristics/moead/MOEAD.cpp +++ b/src/metaheuristics/moead/MOEAD.cpp @@ -2,6 +2,7 @@ // // Author: // Esteban López-Camacho +// Sérgio Vieira // // Copyright (c) 2011 Antonio J. Nebro, Juan J. Durillo // @@ -31,288 +32,322 @@ * Constructor * @param problem Problem to solve */ -MOEAD::MOEAD(Problem *problem) : Algorithm(problem) { - functionType_ = "_TCHE1"; +MOEAD::MOEAD(Problem *problem) : Algorithm(problem) +{ + functionType_ = "_TCHE1"; } // MOEAD -SolutionSet * MOEAD::execute() { - int maxEvaluations; - - evaluations_ = 0; - maxEvaluations = *(int *) getInputParameter("maxEvaluations"); - populationSize_ = *(int *) getInputParameter("populationSize"); - dataDirectory_ = * (string *) getInputParameter("dataDirectory"); - - population_ = new SolutionSet(populationSize_); - //indArray_ = new Solution*[problem_->getNumberOfObjectives()]; - - T_ = 20; - delta_ = 0.9; - nr_ = 2; -/* - T_ = * (int *) (0.1 * populationSize_); - delta_ = 0.9; - nr_ = * (int *) (0.01 * populationSize_); -*/ - neighborhood_ = new int*[populationSize_]; - - z_ = new double[problem_->getNumberOfObjectives()]; - //lambda_ = new Vector(problem_->getNumberOfObjectives()) ; - lambda_ = new double*[populationSize_]; - - crossover_ = operators_["crossover"]; // default: DE crossover - mutation_ = operators_["mutation"]; // default: polynomial mutation - - // STEP 1. Initialization - // STEP 1.1. Compute euclidean distances between weight vectors and find T - initUniformWeight(); - //for (int i = 0; i < 300; i++) - // cout << lambda_[i][0] << " " << lambda_[i][1] << endl ; - - initNeighborhood(); - - // STEP 1.2. Initialize population - initPopulation(); - - // STEP 1.3. Initialize z_ - initIdealPoint(); - - // STEP 2. Update - do { - int * permutation = new int[populationSize_]; - UtilsMOEAD::randomPermutation(permutation, populationSize_); - for (int i = 0; i < populationSize_; i++) { - int n = permutation[i]; // or int n = i; - //int n = i ; // or int n = i; - int type; - double rnd = PseudoRandom::randDouble(); - - // STEP 2.1. Mating selection based on probability - if (rnd < delta_) // if (rnd < realb) - { - type = 1; // neighborhood - } else { - type = 2; // whole population - } - vector p; - matingSelection(p, n, 2, type); - - // STEP 2.2. Reproduction - Solution * child; - Solution ** parents = new Solution*[3]; - - parents[0] = population_->get(p[0]); - parents[1] = population_->get(p[1]); - parents[2] = population_->get(n); - - // Apply DE crossover - void ** object = new void*[2]; - object[0] = population_->get(n); - object[1] = parents; - child = (Solution *) (crossover_->execute(object)); - delete[] object; - delete[] parents; - - // Apply mutation - mutation_->execute(child); - - // Evaluation - problem_->evaluate(child); - - evaluations_++; - - // STEP 2.3. Repair. Not necessary - - // STEP 2.4. Update z_ - updateReference(child); - - // STEP 2.5. Update of solutions - updateProblem(child, n, type); - } // for - - delete[] permutation; - - } while (evaluations_ < maxEvaluations); - - // Free memory - deleteParams(); - - return population_; +SolutionSet * MOEAD::execute() +{ + int maxEvaluations; + + evaluations_ = 0; + maxEvaluations = *(int *) getInputParameter("maxEvaluations"); + populationSize_ = *(int *) getInputParameter("populationSize"); + dataDirectory_ = * (std::string *) getInputParameter("dataDirectory"); + + population_ = snew SolutionSet(populationSize_); + //indArray_ = new Solution*[problem_->getNumberOfObjectives()]; + + T_ = 20; + delta_ = 0.9; + nr_ = 2; + /* + T_ = * (int *) (0.1 * populationSize_); + delta_ = 0.9; + nr_ = * (int *) (0.01 * populationSize_); + */ + neighborhood_ = snew int*[populationSize_]; + + z_ = snew double[problem_->getNumberOfObjectives()]; + //lambda_ = new Vector(problem_->getNumberOfObjectives()) ; + lambda_ = snew double*[populationSize_]; + + crossover_ = operators_["crossover"]; // default: DE crossover + mutation_ = operators_["mutation"]; // default: polynomial mutation + + // STEP 1. Initialization + // STEP 1.1. Compute euclidean distances between weight vectors and find T + initUniformWeight(); + //for (int i = 0; i < 300; i++) + // std::cout << lambda_[i][0] << " " << lambda_[i][1] << std::endl ; + + initNeighborhood(); + + // STEP 1.2. Initialize population + initPopulation(); + + // STEP 1.3. Initialize z_ + initIdealPoint(); + + // STEP 2. Update + do + { + int * permutation = snew int[populationSize_]; + UtilsMOEAD::randomPermutation(permutation, populationSize_); + for (int i = 0; i < populationSize_; i++) + { + int n = permutation[i]; // or int n = i; + //int n = i ; // or int n = i; + int type; + double rnd = PseudoRandom::randDouble(); + + // STEP 2.1. Mating selection based on probability + if (rnd < delta_) // if (rnd < realb) + { + type = 1; // neighborhood + } + else + { + type = 2; // whole population + } + VectorOfInteger p; + matingSelection(p, n, 2, type); + + // STEP 2.2. Reproduction + Solution * child; + Solution ** parents = snew Solution*[3]; + + parents[0] = population_->get(p[0]); + parents[1] = population_->get(p[1]); + parents[2] = population_->get(n); + + // Apply DE crossover + void ** object = snew void*[2]; + object[0] = population_->get(n); + object[1] = parents; + child = (Solution *) (crossover_->execute(object)); + delete[] object; + delete[] parents; + + // Apply mutation + mutation_->execute(child); + + // Evaluation + problem_->evaluate(child); + + evaluations_++; + + // STEP 2.3. Repair. Not necessary + + // STEP 2.4. Update z_ + updateReference(child); + + // STEP 2.5. Update of solutions + updateProblem(child, n, type); + } // for + + delete[] permutation; + + } + while (evaluations_ < maxEvaluations); + + // Free memory + deleteParams(); + + return population_; } // execute /** * initUniformWeight */ -void MOEAD::initUniformWeight() { - if ((problem_->getNumberOfObjectives() == 2) && (populationSize_ <= 300)) { - for (int n = 0; n < populationSize_; n++) { - lambda_[n] = new double[problem_->getNumberOfObjectives()]; - double a = 1.0 * n / (populationSize_ - 1); - lambda_[n][0] = a; - lambda_[n][1] = 1 - a; - } // for - } // if - else { - ostringstream os; - os << dataDirectory_ + "/" << "W" << problem_->getNumberOfObjectives() << "D_" - << populationSize_ << ".dat"; - string dataFileName; - dataFileName = os.str(); - - // Open the file - std::ifstream in(dataFileName.c_str()); - if( !in ) { - cout << "initUniformWeight: failed when reading from file: : " << - dataFileName << endl; - exit(-1); +void MOEAD::initUniformWeight() +{ + if ((problem_->getNumberOfObjectives() == 2) && (populationSize_ <= 300)) + { + for (int n = 0; n < populationSize_; n++) + { + lambda_[n] = snew double[problem_->getNumberOfObjectives()]; + double a = 1.0 * n / (populationSize_ - 1); + lambda_[n][0] = a; + lambda_[n][1] = 1 - a; + } // for } // if + else + { + ostringstream os; + os << dataDirectory_ + "/" << "W" << problem_->getNumberOfObjectives() << "D_" + << populationSize_ << ".dat"; + std::string dataFileName; + dataFileName = os.str(); - //int numberOfObjectives = 0; - int i = 0; - int j = 0; - string aux; - while (getline(in, aux)) { - istringstream iss(aux); - j = 0; - // TODO: Check if number of tokens per line is equal to number of - // objectives - lambda_[i] = new double[problem_->getNumberOfObjectives()]; - while (iss) { - string token; - iss >> token; - if (token.compare("")!=0) { - double value = atof(token.c_str()); - lambda_[i][j] = value; - //cout << "lambda[" << i << "," << j << "] = " << value << endl; - j++; + // Open the file + std::ifstream in(dataFileName.c_str()); + if( !in ) + { + std::cout << "initUniformWeight: failed when reading from file: : " << + dataFileName << std::endl; + exit(-1); } // if - } // while - i++; - } // while - in.close(); - } // else + + //int numberOfObjectives = 0; + int i = 0; + int j = 0; + std::string aux; + while (getline(in, aux)) + { + istringstream iss(aux); + j = 0; + // TODO: Check if number of tokens per line is equal to number of + // objectives + lambda_[i] = snew double[problem_->getNumberOfObjectives()]; + while (iss) + { + std::string token; + iss >> token; + if (token.compare("")!=0) + { + double value = atof(token.c_str()); + lambda_[i][j] = value; + //std::cout << "lambda[" << i << "," << j << "] = " << value << std::endl; + j++; + } // if + } // while + i++; + } // while + in.close(); + } // else } // initUniformWeight /** * initNeighborhood */ -void MOEAD::initNeighborhood() { - double * x = new double[populationSize_]; - int * idx = new int[populationSize_]; - - for (int i = 0; i < populationSize_; i++) { - // calculate the distances based on weight vectors - for (int j = 0; j < populationSize_; j++) { - x[j] = UtilsMOEAD::distVector(lambda_[i], lambda_[j], - problem_->getNumberOfObjectives()); - //x[j] = dist_vector(population[i].namda,population[j].namda); - idx[j] = j; - // cout << "x[" << j << "]: " << x[j] << ". idx[" << j << "]: " << - // idx[j] << endl ; +void MOEAD::initNeighborhood() +{ + double * x = snew double[populationSize_]; + int * idx = snew int[populationSize_]; + + for (int i = 0; i < populationSize_; i++) + { + // calculate the distances based on weight vectors + for (int j = 0; j < populationSize_; j++) + { + x[j] = UtilsMOEAD::distVector(lambda_[i], lambda_[j], + problem_->getNumberOfObjectives()); + //x[j] = dist_vector(population[i].namda,population[j].namda); + idx[j] = j; + // std::cout << "x[" << j << "]: " << x[j] << ". idx[" << j << "]: " << + // idx[j] << std::endl ; + } // for + + // find 'niche' nearest neighboring subproblems + UtilsMOEAD::minFastSort(x, idx, populationSize_, T_); + //minfastsort(x,idx,population.size(),niche); + + neighborhood_[i] = snew int[T_]; + for (int k = 0; k < T_; k++) + { + neighborhood_[i][k] = idx[k]; + //std::cout << "neg[ << i << "," << k << "]: " << neighborhood_[i][k] << std::endl; + } } // for - - // find 'niche' nearest neighboring subproblems - UtilsMOEAD::minFastSort(x, idx, populationSize_, T_); - //minfastsort(x,idx,population.size(),niche); - - neighborhood_[i] = new int[T_]; - for (int k = 0; k < T_; k++) { - neighborhood_[i][k] = idx[k]; - //cout << "neg[ << i << "," << k << "]: " << neighborhood_[i][k] << endl; - } - } // for - - delete[] x; - delete[] idx; - + + delete[] x; + delete[] idx; + } // initNeighborhood /** * initPopulation */ -void MOEAD::initPopulation() { - for (int i = 0; i < populationSize_; i++) { - Solution * newSolution = new Solution(problem_); - - problem_->evaluate(newSolution); - evaluations_++; - population_->add(newSolution); - } // for +void MOEAD::initPopulation() +{ + for (int i = 0; i < populationSize_; i++) + { + Solution * newSolution = snew Solution(problem_); + + problem_->evaluate(newSolution); + evaluations_++; + population_->add(newSolution); + } // for } // initPopulation /** * initIdealPoint */ -void MOEAD::initIdealPoint() { - for (int i = 0; i < problem_->getNumberOfObjectives(); i++) { - z_[i] = 1.0e+30; - //indArray_[i] = new Solution(problem_); - //problem_->evaluate(indArray_[i]); - //evaluations_++; - } // for - - for (int i = 0; i < populationSize_; i++) { - updateReference(population_->get(i)); - } // for +void MOEAD::initIdealPoint() +{ + for (int i = 0; i < problem_->getNumberOfObjectives(); i++) + { + z_[i] = 1.0e+30; + //indArray_[i] = new Solution(problem_); + //problem_->evaluate(indArray_[i]); + //evaluations_++; + } // for + + for (int i = 0; i < populationSize_; i++) + { + updateReference(population_->get(i)); + } // for } // initIdealPoint /** * matingSelection */ -void MOEAD::matingSelection(vector &list, int cid, int size, int type) { - - // list : the set of the indexes of selected mating parents - // cid : the id of current subproblem - // size : the number of selected mating parents - // type : 1 - neighborhood; otherwise - whole population - int ss; - int r; - int p; - - //ss = neighborhood_[cid].length; - ss = T_; - while (list.size() < size) { - if (type == 1) { - r = PseudoRandom::randInt(0, ss - 1); - p = neighborhood_[cid][r]; - //p = population[cid].table[r]; - } else { - p = PseudoRandom::randInt(0, populationSize_ - 1); - } - bool flag = true; - for (int i = 0; i < list.size(); i++) { - if (list[i] == p) // p is in the list - { - flag = false; - break; - } - } - - //if (flag) list.push_back(p); - if (flag) { - list.push_back(p); +void MOEAD::matingSelection(VectorOfInteger &list, int cid, int size, int type) +{ + + // list : the set of the indexes of selected mating parents + // cid : the id of current subproblem + // size : the number of selected mating parents + // type : 1 - neighborhood; otherwise - whole population + int ss; + int r; + int p; + + //ss = neighborhood_[cid].length; + ss = T_; + while (list.size() < size) + { + if (type == 1) + { + r = PseudoRandom::randInt(0, ss - 1); + p = neighborhood_[cid][r]; + //p = population[cid].table[r]; + } + else + { + p = PseudoRandom::randInt(0, populationSize_ - 1); + } + bool flag = true; + for (int i = 0; i < list.size(); i++) + { + if (list[i] == p) // p is in the list + { + flag = false; + break; + } + } + + //if (flag) list.push_back(p); + if (flag) + { + list.push_back(p); + } } - } } // matingSelection /** - * + * * @param individual */ -void MOEAD::updateReference(Solution * individual) { - for (int n = 0; n < problem_->getNumberOfObjectives(); n++) { - if (individual->getObjective(n) < z_[n]) { - z_[n] = individual->getObjective(n); - //indArray_[n] = individual; +void MOEAD::updateReference(Solution * individual) +{ + for (int n = 0; n < problem_->getNumberOfObjectives(); n++) + { + if (individual->getObjective(n) < z_[n]) + { + z_[n] = individual->getObjective(n); + //indArray_[n] = individual; + } } - } } // updateReference @@ -321,104 +356,125 @@ void MOEAD::updateReference(Solution * individual) { * @param id * @param type */ -void MOEAD::updateProblem(Solution * indiv, int id, int type) { - // indiv: child solution - // id: the id of current subproblem - // type: update solutions in neighborhood (1) or whole population (otherwise) - int size; - int time; - - time = 0; - - if (type == 1) { - //size = neighborhood_[id].length; - size = T_; - } else { - //size = population_.size(); - size = populationSize_; - } - int * perm = new int[size]; - - UtilsMOEAD::randomPermutation(perm, size); - - for (int i = 0; i < size; i++) { - - int k; - - if (type == 1) { - k = neighborhood_[id][perm[i]]; - } else { - k = perm[i]; // calculate the values of objective function regarding - // the current subproblem +void MOEAD::updateProblem(Solution * indiv, int id, int type) +{ + // indiv: child solution + // id: the id of current subproblem + // type: update solutions in neighborhood (1) or whole population (otherwise) + int size; + int time; + + time = 0; + + if (type == 1) + { + //size = neighborhood_[id].length; + size = T_; } - - double f1, f2; - - f1 = fitnessFunction(population_->get(k), lambda_[k]); - f2 = fitnessFunction(indiv, lambda_[k]); - - if (f2 < f1) { - delete population_->get(k); - population_->replace(k, new Solution(indiv)); - //population[k].indiv = indiv; - time++; + else + { + //size = population_.size(); + size = populationSize_; } - // the maximal number of solutions updated is not allowed to exceed 'limit' - if (time >= nr_) { - delete indiv; - delete[] perm; - return; + int * perm = snew int[size]; + + UtilsMOEAD::randomPermutation(perm, size); + + for (int i = 0; i < size; i++) + { + + int k; + + if (type == 1) + { + k = neighborhood_[id][perm[i]]; + } + else + { + k = perm[i]; // calculate the values of objective function regarding + // the current subproblem + } + + double f1, f2; + + f1 = fitnessFunction(population_->get(k), lambda_[k]); + f2 = fitnessFunction(indiv, lambda_[k]); + + if (f2 < f1) + { + delete population_->get(k); + population_->replace(k, snew Solution(indiv)); + //population[k].indiv = indiv; + time++; + } + // the maximal number of solutions updated is not allowed to exceed 'limit' + if (time >= nr_) + { + delete indiv; + delete[] perm; + return; + } } - } - delete indiv; - delete[] perm; - + delete indiv; + delete[] perm; + } // updateProblem /** * fitnessFunction */ -double MOEAD::fitnessFunction(Solution * individual, double * lambda) { - double fitness; - fitness = 0.0; - - if (functionType_.compare("_TCHE1")==0) { - double maxFun = -1.0e+30; - - for (int n = 0; n < problem_->getNumberOfObjectives(); n++) { - double diff = fabs(individual->getObjective(n) - z_[n]); - - double feval; - if (lambda[n] == 0) { - feval = 0.0001 * diff; - } else { - feval = diff * lambda[n]; - } - if (feval > maxFun) { - maxFun = feval; - } - } // for - - fitness = maxFun; - } // if - else { - cout << "MOEAD.fitnessFunction: unknown type " << functionType_ << endl; - exit (EXIT_FAILURE); - } - return fitness; +double MOEAD::fitnessFunction(Solution * individual, double * lambda) +{ + double fitness; + fitness = 0.0; + + if (functionType_.compare("_TCHE1")==0) + { + double maxFun = -1.0e+30; + + for (int n = 0; n < problem_->getNumberOfObjectives(); n++) + { + double diff = fabs(individual->getObjective(n) - z_[n]); + + double feval; + if (lambda[n] == 0) + { + feval = 0.0001 * diff; + } + else + { + feval = diff * lambda[n]; + } + if (feval > maxFun) + { + maxFun = feval; + } + } // for + + fitness = maxFun; + } // if + else + { + std::cout << "MOEAD.fitnessFunction: unknown type " << functionType_ << std::endl; + exit (EXIT_FAILURE); + } + return fitness; } // fitnessEvaluation -void MOEAD::deleteParams() { - delete[] z_; - for (int n = 0; n < populationSize_; n++) { - delete[] lambda_[n]; - } // for - delete[] lambda_; - for (int i = 0; i < populationSize_; i++) { - delete[] neighborhood_[i]; - } - delete[] neighborhood_; +void MOEAD::deleteParams() +{ + delete[] z_; + for (int n = 0; n < populationSize_; n++) + { + delete[] lambda_[n]; + } // for + delete[] lambda_; + for (int i = 0; i < populationSize_; i++) + { + delete[] neighborhood_[i]; + } + delete[] neighborhood_; } //deleteParams diff --git a/src/metaheuristics/moead/MOEAD.h b/src/metaheuristics/moead/MOEAD.h index a3ddce7..e09826d 100644 --- a/src/metaheuristics/moead/MOEAD.h +++ b/src/metaheuristics/moead/MOEAD.h @@ -2,6 +2,7 @@ // // Author: // Esteban López-Camacho +// Sérgio Vieira // // Copyright (c) 2011 Antonio J. Nebro, Juan J. Durillo // @@ -32,66 +33,67 @@ * This class implements the MOEA/D algorithm. */ -class MOEAD : public Algorithm { - +class MOEAD : public Algorithm +{ + private: - /** - * Stores the population size - */ - int populationSize_; - /** - * Stores the population - */ - SolutionSet * population_; - /** - * Z vector (ideal point) - */ - double * z_; - /** - * Lambda vectors - */ - double ** lambda_; - /** - * T: neighbour size - */ - int T_; - /** - * Neighborhood - */ - int ** neighborhood_; - /** - * delta: probability that parent solutions are selected from neighbourhood - */ - double delta_; - /** - * nr: maximal number of solutions replaced by each child solution - */ - int nr_; - Solution ** indArray_; - string functionType_; - int evaluations_; - /** - * Operators - */ - Operator * crossover_; - Operator * mutation_; + /** + * Stores the population size + */ + int populationSize_; + /** + * Stores the population + */ + SolutionSet * population_; + /** + * Z vector (ideal point) + */ + double * z_; + /** + * Lambda vectors + */ + double ** lambda_; + /** + * T: neighbour size + */ + int T_; + /** + * Neighborhood + */ + int ** neighborhood_; + /** + * delta: probability that parent solutions are selected from neighbourhood + */ + double delta_; + /** + * nr: maximal number of solutions replaced by each child solution + */ + int nr_; + Solution ** indArray_; + std::string functionType_; + int evaluations_; + /** + * Operators + */ + Operator * crossover_; + Operator * mutation_; + + std::string dataDirectory_; - string dataDirectory_; - - void initUniformWeight(); - void initNeighborhood(); - void initPopulation(); - void initIdealPoint(); - void matingSelection(vector &list, int cid, int size, int type); - void updateReference(Solution * individual); - void updateProblem(Solution * indiv, int id, int type); - double fitnessFunction(Solution * individual, double * lambda); - void deleteParams(); + void initUniformWeight(); + void initNeighborhood(); + void initPopulation(); + void initIdealPoint(); + void matingSelection(VectorOfInteger &list, int cid, int size, int type); + void updateReference(Solution * individual); + void updateProblem(Solution * indiv, int id, int type); + double fitnessFunction(Solution * individual, double * lambda); + void deleteParams(); public: - MOEAD(Problem * problem); - SolutionSet * execute(); + MOEAD(Problem * problem); + SolutionSet * execute(); }; #endif /* __MOEAD__ */ diff --git a/src/metaheuristics/moead/UtilsMOEAD.cpp b/src/metaheuristics/moead/UtilsMOEAD.cpp index bce0408..d900950 100644 --- a/src/metaheuristics/moead/UtilsMOEAD.cpp +++ b/src/metaheuristics/moead/UtilsMOEAD.cpp @@ -2,6 +2,7 @@ // // Author: // Esteban López-Camacho +// Sérgio Vieira // // Copyright (c) 2011 Antonio J. Nebro, Juan J. Durillo // @@ -19,69 +20,84 @@ // along with this program. If not, see . #include +#include "JMetalHeader.h" /** * Utilities methods to used by MOEA/D */ -double UtilsMOEAD::distVector(double * vector1, double * vector2, int dim) { - //int dim = vector1.size(); - double sum = 0; - for (int n = 0; n < dim; n++) { - sum += (vector1[n] - vector2[n]) * (vector1[n] - vector2[n]); - } - return sqrt(sum); +double UtilsMOEAD::distVector(double * vector1, double * vector2, int dim) +{ + //int dim = vector1.size(); + double sum = 0; + for (int n = 0; n < dim; n++) + { + sum += (vector1[n] - vector2[n]) * (vector1[n] - vector2[n]); + } + return sqrt(sum); } // distVector -void UtilsMOEAD::minFastSort(double * x, int * idx, int n, int m) { - - for (int i = 0; i < m; i++) { - for (int j = i + 1; j < n; j++) { - if (x[i] > x[j]) { - double temp = x[i]; - x[i] = x[j]; - x[j] = temp; - int id = idx[i]; - idx[i] = idx[j]; - idx[j] = id; - } // if - } - } // for - +void UtilsMOEAD::minFastSort(double * x, int * idx, int n, int m) +{ + + for (int i = 0; i < m; i++) + { + for (int j = i + 1; j < n; j++) + { + if (x[i] > x[j]) + { + double temp = x[i]; + x[i] = x[j]; + x[j] = temp; + int id = idx[i]; + idx[i] = idx[j]; + idx[j] = id; + } // if + } + } // for + } // minFastSort -void UtilsMOEAD::randomPermutation(int * perm, int size) { - int * index = new int[size]; - bool * flag = new bool[size]; - - for (int n = 0; n < size; n++) { - index[n] = n; - flag[n] = true; - } - - int num = 0; - while (num < size) { - int start = PseudoRandom::randInt(0, size - 1); - //int start = int(size*nd_uni(&rnd_uni_init)); - while (true) { - if (flag[start]) { - perm[num] = index[start]; - flag[start] = false; - num++; - break; - } - if (start == (size - 1)) { - start = 0; - } else { - start++; - } +void UtilsMOEAD::randomPermutation(int * perm, int size) +{ + int * index = snew int[size]; + bool * flag = new bool[size]; + + for (int n = 0; n < size; n++) + { + index[n] = n; + flag[n] = true; } - } // while - - delete[] index; - delete[] flag; - + + int num = 0; + while (num < size) + { + int start = PseudoRandom::randInt(0, size - 1); + //int start = int(size*nd_uni(&rnd_uni_init)); + while (true) + { + if (flag[start]) + { + perm[num] = index[start]; + flag[start] = false; + num++; + break; + } + if (start == (size - 1)) + { + start = 0; + } + else + { + start++; + } + } + } // while + + delete[] index; + delete[] flag; + } // randomPermutation diff --git a/src/metaheuristics/moead/UtilsMOEAD.h b/src/metaheuristics/moead/UtilsMOEAD.h index e14cd8b..b56fd67 100644 --- a/src/metaheuristics/moead/UtilsMOEAD.h +++ b/src/metaheuristics/moead/UtilsMOEAD.h @@ -2,6 +2,7 @@ // // Author: // Esteban López-Camacho +// Sérgio Vieira // // Copyright (c) 2011 Antonio J. Nebro, Juan J. Durillo // @@ -36,13 +37,14 @@ using namespace std; */ -class UtilsMOEAD { - +class UtilsMOEAD +{ + public: - static double distVector(double * vector1, double * vector2, int dim); - static void minFastSort(double * x, int * idx, int n, int m); - static void randomPermutation(int * perm, int size); - + static double distVector(double * vector1, double * vector2, int dim); + static void minFastSort(double * x, int * idx, int n, int m); + static void randomPermutation(int * perm, int size); + }; diff --git a/src/metaheuristics/nsgaII/CMakeLists.txt b/src/metaheuristics/nsgaII/CMakeLists.txt new file mode 100644 index 0000000..294ec59 --- /dev/null +++ b/src/metaheuristics/nsgaII/CMakeLists.txt @@ -0,0 +1,3 @@ +file(GLOB SOURCES "*.cpp" "*.h") +ListToString(SOURCES ";" ${SOURCES}) +LIST_APPEND("${SOURCES}") \ No newline at end of file diff --git a/src/metaheuristics/nsgaII/NSGAII.cpp b/src/metaheuristics/nsgaII/NSGAII.cpp index 31251d1..972446b 100644 --- a/src/metaheuristics/nsgaII/NSGAII.cpp +++ b/src/metaheuristics/nsgaII/NSGAII.cpp @@ -2,6 +2,7 @@ // // Author: // Esteban López-Camacho +// Sérgio Vieira // // Copyright (c) 2011 Antonio J. Nebro, Juan J. Durillo // @@ -31,7 +32,8 @@ * Constructor * @param problem Problem to solve */ -NSGAII::NSGAII(Problem *problem) : Algorithm(problem) { +NSGAII::NSGAII(Problem *problem) : Algorithm(problem) +{ } // NSGAII @@ -40,165 +42,177 @@ NSGAII::NSGAII(Problem *problem) : Algorithm(problem) { * @return a SolutionSet that is a set of non dominated solutions * as a result of the algorithm execution */ -SolutionSet * NSGAII::execute() { +SolutionSet * NSGAII::execute() +{ - int populationSize; - int maxEvaluations; - int evaluations; + int populationSize; + int maxEvaluations; + int evaluations; // QualityIndicator * indicators; // QualityIndicator object - int requiredEvaluations; // Use in the example of use of the - // indicators object (see below) + int requiredEvaluations; // Use in the example of use of the + // indicators object (see below) - SolutionSet * population; - SolutionSet * offspringPopulation; - SolutionSet * unionSolution; + SolutionSet * population; + SolutionSet * offspringPopulation; + SolutionSet * unionSolution; - Operator * mutationOperator; - Operator * crossoverOperator; - Operator * selectionOperator; + Operator * mutationOperator; + Operator * crossoverOperator; + Operator * selectionOperator; - Distance * distance = new Distance(); + Distance * distance = new Distance(); - //Read the parameters - populationSize = *(int *) getInputParameter("populationSize"); - maxEvaluations = *(int *) getInputParameter("maxEvaluations"); + //Read the parameters + populationSize = *(int *) getInputParameter("populationSize"); + maxEvaluations = *(int *) getInputParameter("maxEvaluations"); // indicators = (QualityIndicator *) getInputParameter("indicators"); - //Initialize the variables - population = new SolutionSet(populationSize); - evaluations = 0; - - requiredEvaluations = 0; - - //Read the operators - mutationOperator = operators_["mutation"]; - crossoverOperator = operators_["crossover"]; - selectionOperator = operators_["selection"]; - - // Create the initial solutionSet - Solution * newSolution; - for (int i = 0; i < populationSize; i++) { - newSolution = new Solution(problem_); - problem_->evaluate(newSolution); - problem_->evaluateConstraints(newSolution); - evaluations++; - population->add(newSolution); - } //for - - // Generations - while (evaluations < maxEvaluations) { - - // Create the offSpring solutionSet - offspringPopulation = new SolutionSet(populationSize); - Solution ** parents = new Solution*[2]; - - for (int i = 0; i < (populationSize / 2); i++) { - if (evaluations < maxEvaluations) { - //obtain parents - parents[0] = (Solution *) (selectionOperator->execute(population)); - parents[1] = (Solution *) (selectionOperator->execute(population)); - - Solution ** offSpring = (Solution **) (crossoverOperator->execute(parents)); - - mutationOperator->execute(offSpring[0]); - mutationOperator->execute(offSpring[1]); - - problem_->evaluate(offSpring[0]); - problem_->evaluateConstraints(offSpring[0]); - problem_->evaluate(offSpring[1]); - problem_->evaluateConstraints(offSpring[1]); - offspringPopulation->add(offSpring[0]); - offspringPopulation->add(offSpring[1]); - evaluations += 2; - delete[] offSpring; - - } // if - } // for - - delete[] parents; - - // Create the solutionSet union of solutionSet and offSpring - unionSolution = population->join(offspringPopulation); - delete offspringPopulation; - - // Ranking the union - Ranking * ranking = new Ranking(unionSolution); - - int remain = populationSize; - int index = 0; - SolutionSet * front = NULL; - for (int i=0;isize();i++) { - delete population->get(i); - } - population->clear(); - - // Obtain the next front - front = ranking->getSubfront(index); - - while ((remain > 0) && (remain >= front->size())) { - //Assign crowding distance to individuals - distance->crowdingDistanceAssignment(front, problem_->getNumberOfObjectives()); - - //Add the individuals of this front - for (int k = 0; k < front->size(); k++) { - population->add(new Solution(front->get(k))); - } // for - - //Decrement remain - remain = remain - front->size(); - - //Obtain the next front - index++; - if (remain > 0) { + //Initialize the variables + population = new SolutionSet(populationSize); + evaluations = 0; + + requiredEvaluations = 0; + + //Read the operators + mutationOperator = operators_["mutation"]; + crossoverOperator = operators_["crossover"]; + selectionOperator = operators_["selection"]; + + // Create the initial solutionSet + Solution * newSolution; + for (int i = 0; i < populationSize; i++) + { + newSolution = new Solution(problem_); + problem_->evaluate(newSolution); + problem_->evaluateConstraints(newSolution); + evaluations++; + population->add(newSolution); + } //for + + // Generations + while (evaluations < maxEvaluations) + { + + // Create the offSpring solutionSet + offspringPopulation = new SolutionSet(populationSize); + Solution ** parents = new Solution*[2]; + + for (int i = 0; i < (populationSize / 2); i++) + { + if (evaluations < maxEvaluations) + { + //obtain parents + parents[0] = (Solution *) (selectionOperator->execute(population)); + parents[1] = (Solution *) (selectionOperator->execute(population)); + + Solution ** offSpring = (Solution **) (crossoverOperator->execute(parents)); + + mutationOperator->execute(offSpring[0]); + mutationOperator->execute(offSpring[1]); + + problem_->evaluate(offSpring[0]); + problem_->evaluateConstraints(offSpring[0]); + problem_->evaluate(offSpring[1]); + problem_->evaluateConstraints(offSpring[1]); + offspringPopulation->add(offSpring[0]); + offspringPopulation->add(offSpring[1]); + evaluations += 2; + delete[] offSpring; + + } // if + } // for + + delete[] parents; + + // Create the solutionSet union of solutionSet and offSpring + unionSolution = population->join(offspringPopulation); + delete offspringPopulation; + + // Ranking the union + Ranking * ranking = new Ranking(unionSolution); + + int remain = populationSize; + int index = 0; + SolutionSet * front = nullptr; + for (int i=0; isize(); i++) + { + delete population->get(i); + } + population->clear(); + + // Obtain the next front front = ranking->getSubfront(index); - } // if - - } // while - // Remain is less than front(index).size, insert only the best one - if (remain > 0) { // front contains individuals to insert - distance->crowdingDistanceAssignment(front, problem_->getNumberOfObjectives()); - Comparator * c = new CrowdingComparator(); - front->sort(c); - delete c; - for (int k = 0; k < remain; k++) { - population->add(new Solution(front->get(k))); - } // for - - remain = 0; - } // if - - delete ranking; - delete unionSolution; - - // This piece of code shows how to use the indicator object into the code - // of NSGA-II. In particular, it finds the number of evaluations required - // by the algorithm to obtain a Pareto front with a hypervolume higher - // than the hypervolume of the true Pareto front. -// if ((indicators != NULL) && (requiredEvaluations == 0)) { + while ((remain > 0) && (remain >= front->size())) + { + //Assign crowding distance to individuals + distance->crowdingDistanceAssignment(front, problem_->getNumberOfObjectives()); + + //Add the individuals of this front + for (int k = 0; k < front->size(); k++) + { + population->add(new Solution(front->get(k))); + } // for + + //Decrement remain + remain = remain - front->size(); + + //Obtain the next front + index++; + if (remain > 0) + { + front = ranking->getSubfront(index); + } // if + + } // while + + // Remain is less than front(index).size, insert only the best one + if (remain > 0) // front contains individuals to insert + { + distance->crowdingDistanceAssignment(front, problem_->getNumberOfObjectives()); + Comparator * c = new CrowdingComparator(); + front->sort(c); + delete c; + for (int k = 0; k < remain; k++) + { + population->add(new Solution(front->get(k))); + } // for + + remain = 0; + } // if + + delete ranking; + delete unionSolution; + + // This piece of code shows how to use the indicator object into the code + // of NSGA-II. In particular, it finds the number of evaluations required + // by the algorithm to obtain a Pareto front with a hypervolume higher + // than the hypervolume of the true Pareto front. +// if ((indicators != nullptr) && (requiredEvaluations == 0)) { // double HV = indicators->getHypervolume(population); // if (HV >= (0.98 * indicators->getTrueParetoFrontHypervolume())) { // requiredEvaluations = evaluations; // } // if // } // if - } // while + } // while - delete distance; + delete distance; - // Return as output parameter the required evaluations + // Return as output parameter the required evaluations // setOutputParameter("evaluations", &requiredEvaluations); - // Return the first non-dominated front - Ranking * ranking = new Ranking(population); - SolutionSet * result = new SolutionSet(ranking->getSubfront(0)->size()); - for (int i=0;igetSubfront(0)->size();i++) { - result->add(new Solution(ranking->getSubfront(0)->get(i))); - } - delete ranking; - delete population; + // Return the first non-dominated front + Ranking * ranking = new Ranking(population); + SolutionSet * result = new SolutionSet(ranking->getSubfront(0)->size()); + for (int i=0; igetSubfront(0)->size(); i++) + { + result->add(new Solution(ranking->getSubfront(0)->get(i))); + } + delete ranking; + delete population; - return result; + return result; } // execute diff --git a/src/metaheuristics/nsgaII/NSGAII.h b/src/metaheuristics/nsgaII/NSGAII.h index 81f2bef..cff502e 100644 --- a/src/metaheuristics/nsgaII/NSGAII.h +++ b/src/metaheuristics/nsgaII/NSGAII.h @@ -2,6 +2,7 @@ // // Author: // Esteban López-Camacho +// Sérgio Vieira // // Copyright (c) 2011 Antonio J. Nebro, Juan J. Durillo // @@ -34,11 +35,12 @@ * @brief This class implements the NSGA-II algorithm **/ -class NSGAII : public Algorithm { +class NSGAII : public Algorithm +{ public: - NSGAII(Problem * problem); - SolutionSet * execute(); + NSGAII(Problem * problem); + SolutionSet * execute(); }; diff --git a/src/metaheuristics/nsgaII/ssNSGAII.cpp b/src/metaheuristics/nsgaII/ssNSGAII.cpp index 393e6bd..9604911 100644 --- a/src/metaheuristics/nsgaII/ssNSGAII.cpp +++ b/src/metaheuristics/nsgaII/ssNSGAII.cpp @@ -2,6 +2,7 @@ // // Author: // Esteban López-Camacho +// Sérgio Vieira // // Copyright (c) 2011 Antonio J. Nebro, Juan J. Durillo // @@ -31,7 +32,8 @@ * Constructor * @param problem Problem to solve */ -ssNSGAII::ssNSGAII(Problem *problem) : Algorithm(problem) { +ssNSGAII::ssNSGAII(Problem *problem) : Algorithm(problem) +{ } // ssNSGAII @@ -40,139 +42,148 @@ ssNSGAII::ssNSGAII(Problem *problem) : Algorithm(problem) { * @return a SolutionSet that is a set of non dominated solutions * as a result of the algorithm execution */ -SolutionSet * ssNSGAII::execute() { - - int populationSize; - int maxEvaluations; - int evaluations; - - // TODO: QualityIndicator indicators; // QualityIndicator object - int requiredEvaluations; // Use in the example of use of the - // indicators object (see below) - - SolutionSet * population; - SolutionSet * offspringPopulation; - SolutionSet * unionSolution; - - Operator * mutationOperator; - Operator * crossoverOperator; - Operator * selectionOperator; - - Distance * distance = new Distance(); - - //Read the parameters - populationSize = *(int *) getInputParameter("populationSize"); - maxEvaluations = *(int *) getInputParameter("maxEvaluations"); - // TODO: indicators = (QualityIndicator) getInputParameter("indicators"); - - //Initialize the variables - population = new SolutionSet(populationSize); - evaluations = 0; - - requiredEvaluations = 0; - - //Read the operators - mutationOperator = operators_["mutation"]; - crossoverOperator = operators_["crossover"]; - selectionOperator = operators_["selection"]; - - // Create the initial solutionSet - Solution * newSolution; - for (int i = 0; i < populationSize; i++) { - newSolution = new Solution(problem_); - problem_->evaluate(newSolution); - problem_->evaluateConstraints(newSolution); - evaluations++; - population->add(newSolution); - } //for - - // Generations - while (evaluations < maxEvaluations) { - - // Create the offSpring solutionSet - offspringPopulation = new SolutionSet(populationSize); - Solution ** parents = new Solution*[2]; - - //obtain parents - parents[0] = (Solution *) (selectionOperator->execute(population)); - parents[1] = (Solution *) (selectionOperator->execute(population)); - - // crossover - Solution ** offSpring = (Solution **) (crossoverOperator->execute(parents)); - - // mutation - mutationOperator->execute(offSpring[0]); - - // evaluation - problem_->evaluate(offSpring[0]); - problem_->evaluateConstraints(offSpring[0]); - - // insert child into the offspring population - offspringPopulation->add(offSpring[0]); - - evaluations ++; - delete offSpring[1]; - delete[] offSpring; - delete[] parents; - - // Create the solutionSet union of solutionSet and offSpring - unionSolution = population->join(offspringPopulation); - delete offspringPopulation; - - // Ranking the union - Ranking * ranking = new Ranking(unionSolution); - - int remain = populationSize; - int index = 0; - SolutionSet * front = NULL; - for (int i=0;isize();i++) { - delete population->get(i); - } - population->clear(); - - // Obtain the next front - front = ranking->getSubfront(index); - - while ((remain > 0) && (remain >= front->size())) { - //Assign crowding distance to individuals - distance->crowdingDistanceAssignment(front, problem_->getNumberOfObjectives()); - //Add the individuals of this front - for (int k = 0; k < front->size(); k++) { - population->add(new Solution(front->get(k))); - } // for - - //Decrement remain - remain = remain - front->size(); - - //Obtain the next front - index++; - if (remain > 0) { +SolutionSet * ssNSGAII::execute() +{ + + int populationSize; + int maxEvaluations; + int evaluations; + + // TODO: QualityIndicator indicators; // QualityIndicator object + int requiredEvaluations; // Use in the example of use of the + // indicators object (see below) + + SolutionSet * population; + SolutionSet * offspringPopulation; + SolutionSet * unionSolution; + + Operator * mutationOperator; + Operator * crossoverOperator; + Operator * selectionOperator; + + Distance * distance = new Distance(); + + //Read the parameters + populationSize = *(int *) getInputParameter("populationSize"); + maxEvaluations = *(int *) getInputParameter("maxEvaluations"); + // TODO: indicators = (QualityIndicator) getInputParameter("indicators"); + + //Initialize the variables + population = new SolutionSet(populationSize); + evaluations = 0; + + requiredEvaluations = 0; + + //Read the operators + mutationOperator = operators_["mutation"]; + crossoverOperator = operators_["crossover"]; + selectionOperator = operators_["selection"]; + + // Create the initial solutionSet + Solution * newSolution; + for (int i = 0; i < populationSize; i++) + { + newSolution = new Solution(problem_); + problem_->evaluate(newSolution); + problem_->evaluateConstraints(newSolution); + evaluations++; + population->add(newSolution); + } //for + + // Generations + while (evaluations < maxEvaluations) + { + + // Create the offSpring solutionSet + offspringPopulation = new SolutionSet(populationSize); + Solution ** parents = new Solution*[2]; + + //obtain parents + parents[0] = (Solution *) (selectionOperator->execute(population)); + parents[1] = (Solution *) (selectionOperator->execute(population)); + + // crossover + Solution ** offSpring = (Solution **) (crossoverOperator->execute(parents)); + + // mutation + mutationOperator->execute(offSpring[0]); + + // evaluation + problem_->evaluate(offSpring[0]); + problem_->evaluateConstraints(offSpring[0]); + + // insert child into the offspring population + offspringPopulation->add(offSpring[0]); + + evaluations ++; + delete offSpring[1]; + delete[] offSpring; + delete[] parents; + + // Create the solutionSet union of solutionSet and offSpring + unionSolution = population->join(offspringPopulation); + delete offspringPopulation; + + // Ranking the union + Ranking * ranking = new Ranking(unionSolution); + + int remain = populationSize; + int index = 0; + SolutionSet * front = nullptr; + for (int i=0; isize(); i++) + { + delete population->get(i); + } + population->clear(); + + // Obtain the next front front = ranking->getSubfront(index); - } // if - } // while - - // Remain is less than front(index).size, insert only the best one - if (remain > 0) { // front contains individuals to insert - distance->crowdingDistanceAssignment(front, problem_->getNumberOfObjectives()); - Comparator * c = new CrowdingComparator(); - front->sort(c); - delete c; - for (int k = 0; k < remain; k++) { - population->add(new Solution(front->get(k))); - } // for - remain = 0; - } // if - - delete ranking; - delete unionSolution; - - // This piece of code shows how to use the indicator object into the code - // of NSGA-II. In particular, it finds the number of evaluations required - // by the algorithm to obtain a Pareto front with a hypervolume higher - // than the hypervolume of the true Pareto front. + while ((remain > 0) && (remain >= front->size())) + { + //Assign crowding distance to individuals + distance->crowdingDistanceAssignment(front, problem_->getNumberOfObjectives()); + //Add the individuals of this front + for (int k = 0; k < front->size(); k++) + { + population->add(new Solution(front->get(k))); + } // for + + //Decrement remain + remain = remain - front->size(); + + //Obtain the next front + index++; + if (remain > 0) + { + front = ranking->getSubfront(index); + } // if + } // while + + // Remain is less than front(index).size, insert only the best one + if (remain > 0) // front contains individuals to insert + { + distance->crowdingDistanceAssignment(front, problem_->getNumberOfObjectives()); + Comparator * c = new CrowdingComparator(); + front->sort(c); + delete c; + for (int k = 0; k < remain; k++) + { + population->add(new Solution(front->get(k))); + } // for + + remain = 0; + } // if + + delete ranking; + delete unionSolution; + + // This piece of code shows how to use the indicator object into the code + // of NSGA-II. In particular, it finds the number of evaluations required + // by the algorithm to obtain a Pareto front with a hypervolume higher + // than the hypervolume of the true Pareto front. // TODO: -// if ((indicators != NULL) && +// if ((indicators != nullptr) && // (requiredEvaluations == 0)) { // double HV = indicators.getHypervolume(population); // if (HV >= (0.98 * indicators.getTrueParetoFrontHypervolume())) { @@ -180,23 +191,24 @@ SolutionSet * ssNSGAII::execute() { // } // if // } // if - } // while + } // while - delete distance; + delete distance; - // Return as output parameter the required evaluations - // TODO: - //setOutputParameter("evaluations", requiredEvaluations); + // Return as output parameter the required evaluations + // TODO: + //setOutputParameter("evaluations", requiredEvaluations); - // Return the first non-dominated front - Ranking * ranking = new Ranking(population); - SolutionSet * result = new SolutionSet(ranking->getSubfront(0)->size()); - for (int i=0;igetSubfront(0)->size();i++) { - result->add(new Solution(ranking->getSubfront(0)->get(i))); - } - delete ranking; - delete population; + // Return the first non-dominated front + Ranking * ranking = new Ranking(population); + SolutionSet * result = new SolutionSet(ranking->getSubfront(0)->size()); + for (int i=0; igetSubfront(0)->size(); i++) + { + result->add(new Solution(ranking->getSubfront(0)->get(i))); + } + delete ranking; + delete population; - return result; + return result; } // execute diff --git a/src/metaheuristics/nsgaII/ssNSGAII.h b/src/metaheuristics/nsgaII/ssNSGAII.h index ac53855..d56f8ea 100644 --- a/src/metaheuristics/nsgaII/ssNSGAII.h +++ b/src/metaheuristics/nsgaII/ssNSGAII.h @@ -2,6 +2,7 @@ // // Author: // Esteban López-Camacho +// Sérgio Vieira // // Copyright (c) 2011 Antonio J. Nebro, Juan J. Durillo // @@ -34,16 +35,17 @@ * @brief This class implements a steady-state version of NSGA-II. **/ -class ssNSGAII : public Algorithm { +class ssNSGAII : public Algorithm +{ private: - int populationSize_; - int maxEvaluations_; - //QualityIndicator *indicators_; + int populationSize_; + int maxEvaluations_; + //QualityIndicator *indicators_; public: - ssNSGAII(Problem * problem); - SolutionSet * execute(); + ssNSGAII(Problem * problem); + SolutionSet * execute(); }; diff --git a/src/metaheuristics/omopso/CMakeLists.txt b/src/metaheuristics/omopso/CMakeLists.txt new file mode 100644 index 0000000..294ec59 --- /dev/null +++ b/src/metaheuristics/omopso/CMakeLists.txt @@ -0,0 +1,3 @@ +file(GLOB SOURCES "*.cpp" "*.h") +ListToString(SOURCES ";" ${SOURCES}) +LIST_APPEND("${SOURCES}") \ No newline at end of file diff --git a/src/metaheuristics/omopso/OMOPSO.cpp b/src/metaheuristics/omopso/OMOPSO.cpp index b98ab39..ecaf1a5 100644 --- a/src/metaheuristics/omopso/OMOPSO.cpp +++ b/src/metaheuristics/omopso/OMOPSO.cpp @@ -2,6 +2,7 @@ // // Author: // Esteban López-Camacho +// Sérgio Vieira // // Copyright (c) 2014 Antonio J. Nebro // @@ -31,36 +32,38 @@ * Constructor * @param problem Problem to solve */ -OMOPSO::OMOPSO(Problem *problem) : Algorithm(problem) { +OMOPSO::OMOPSO(Problem *problem) : Algorithm(problem) +{ } // OMOPSO /** * Initialize all parameter of the algorithm */ -void OMOPSO::initParams() { - - particlesSize = *(int *) getInputParameter("swarmSize"); - archiveSize = *(int *) getInputParameter("archiveSize"); - maxIterations = *(int *) getInputParameter("maxIterations"); +void OMOPSO::initParams() +{ - iteration = 0; + particlesSize = *(int *) getInputParameter("swarmSize"); + archiveSize = *(int *) getInputParameter("archiveSize"); + maxIterations = *(int *) getInputParameter("maxIterations"); - particles = new SolutionSet(particlesSize); - best = new Solution*[particlesSize]; - leaders = new CrowdingArchive(archiveSize,problem_->getNumberOfObjectives()); - eArchive = new NonDominatedSolutionList(new EpsilonDominanceComparator(eta)); + iteration = 0; - uniformMutation = operators_["uniformMutation"] ; - nonUniformMutation = operators_["nonUniformMutation"] ; + particles = new SolutionSet(particlesSize); + best = new Solution*[particlesSize]; + leaders = new CrowdingArchive(archiveSize,problem_->getNumberOfObjectives()); + eArchive = new NonDominatedSolutionList(new EpsilonDominanceComparator(eta)); - // Create the dominator for equadless and dominance - dominance = new DominanceComparator(); - crowdingDistanceComparator = new CrowdingDistanceComparator(); - distance = new Distance(); + uniformMutation = operators_["uniformMutation"] ; + nonUniformMutation = operators_["nonUniformMutation"] ; - // Create the speed_ vector - speed = new double*[particlesSize]; + // Create the dominator for equadless and dominance + dominance = new DominanceComparator(); + crowdingDistanceComparator = new CrowdingDistanceComparator(); + distance = new Distance(); + + // Create the speed_ vector + speed = snew double*[particlesSize]; } // initParams @@ -68,72 +71,81 @@ void OMOPSO::initParams() { /** * Free all the memory reserved by the algorithm */ -void OMOPSO::deleteParams() { - - for (int i = 0; i < particlesSize; i++) { - delete [] speed[i]; - } - delete [] speed; - delete dominance; - delete crowdingDistanceComparator; - delete distance; - delete particles; - for (int i = 0; i < particlesSize; i++) { - delete best[i]; - } - delete [] best; - delete leaders; - delete eArchive; - +void OMOPSO::deleteParams() +{ + + for (int i = 0; i < particlesSize; i++) + { + delete [] speed[i]; + } + delete [] speed; + delete dominance; + delete crowdingDistanceComparator; + delete distance; + delete particles; + for (int i = 0; i < particlesSize; i++) + { + delete best[i]; + } + delete [] best; + delete leaders; + delete eArchive; + } // deleteParams /** * Update the speed of each particle */ -void OMOPSO::computeSpeed() { - - double r1, r2, W, C1, C2; - XReal *bestGlobal; - - for (int i = 0; i < particlesSize; i++) { - XReal *particle = new XReal(particles->get(i)); - XReal *bestParticle = new XReal(best[i]); - - //Select a global best for calculate the speed of particle i, bestGlobal - Solution *one, *two; - int pos1 = PseudoRandom::randInt(0,leaders->size()-1); - int pos2 = PseudoRandom::randInt(0,leaders->size()-1); - one = leaders->get(pos1); - two = leaders->get(pos2); - - if (crowdingDistanceComparator->compare(one,two) < 1) { - bestGlobal = new XReal(one); - } else { - bestGlobal = new XReal(two); - } +void OMOPSO::computeSpeed() +{ + + double r1, r2, W, C1, C2; + XReal *bestGlobal; + + for (int i = 0; i < particlesSize; i++) + { + XReal *particle = new XReal(particles->get(i)); + XReal *bestParticle = new XReal(best[i]); + + //Select a global best for calculate the speed of particle i, bestGlobal + Solution *one, *two; + int pos1 = PseudoRandom::randInt(0,leaders->size()-1); + int pos2 = PseudoRandom::randInt(0,leaders->size()-1); + one = leaders->get(pos1); + two = leaders->get(pos2); + + if (crowdingDistanceComparator->compare(one,two) < 1) + { + bestGlobal = new XReal(one); + } + else + { + bestGlobal = new XReal(two); + } - //Params for velocity equation - r1 = PseudoRandom::randDouble(); - r2 = PseudoRandom::randDouble(); - C1 = PseudoRandom::randDouble(1.5,2.0); - C2 = PseudoRandom::randDouble(1.5,2.0); - W = PseudoRandom::randDouble(0.1,0.5); - - for (int var = 0; var < particle->getNumberOfDecisionVariables(); var++) { - //Computing the velocity of this particle - speed[i][var] = W * speed[i][var] + - C1 * r1 * (bestParticle->getValue(var) - - particle->getValue(var)) + - C2 * r2 * (bestGlobal->getValue(var) - - particle->getValue(var)); - } + //Params for velocity equation + r1 = PseudoRandom::randDouble(); + r2 = PseudoRandom::randDouble(); + C1 = PseudoRandom::randDouble(1.5,2.0); + C2 = PseudoRandom::randDouble(1.5,2.0); + W = PseudoRandom::randDouble(0.1,0.5); + + for (int var = 0; var < particle->getNumberOfDecisionVariables(); var++) + { + //Computing the velocity of this particle + speed[i][var] = W * speed[i][var] + + C1 * r1 * (bestParticle->getValue(var) - + particle->getValue(var)) + + C2 * r2 * (bestGlobal->getValue(var) - + particle->getValue(var)); + } - delete bestGlobal; - delete particle; - delete bestParticle; + delete bestGlobal; + delete particle; + delete bestParticle; - } + } } // computeSpeed @@ -141,25 +153,37 @@ void OMOPSO::computeSpeed() { /** * Update the position of each particle */ -void OMOPSO::computeNewPositions() { - - for (int i = 0; i < particlesSize; i++) { - XReal * particle = new XReal(particles->get(i)); - //particle.move(speed_[i]); - for (int var = 0; var < particle->getNumberOfDecisionVariables(); var++) { - particle->setValue(var, particle->getValue(var) + speed[i][var]); - - if (particle->getValue(var) < problem_->getLowerLimit(var)) { - particle->setValue(var, problem_->getLowerLimit(var)); - speed[i][var] = speed[i][var] * -1.0; - } - if (particle->getValue(var) > problem_->getUpperLimit(var)){ - particle->setValue(var, problem_->getUpperLimit(var)); - speed[i][var] = speed[i][var] * -1.0; - } +void OMOPSO::computeNewPositions() +{ + + for (int i = 0; i < particlesSize; i++) + { + XReal * particle = new XReal(particles->get(i)); + //particle.move(speed_[i]); + for (int var = 0; var < particle->getNumberOfDecisionVariables(); var++) + { + double oldPosition = particle->getValue(var); + double newPosition = oldPosition + speed[i][var]; + particle->setValue(var, newPosition); + if (particle->getValue(var) < problem_->getLowerLimit(var)) + { + particle->setValue(var, problem_->getLowerLimit(var)); + double diff = ((oldPosition - problem_->getLowerLimit(var))) * PseudoRandom::randDouble(); + newPosition = problem_->getLowerLimit(var) + diff; + particle->setValue(var, newPosition); + speed[i][var] = speed[i][var] * -1.0; + } + if (particle->getValue(var) > problem_->getUpperLimit(var)) + { + //particle->setValue(var, problem_->getUpperLimit(var)); + double diff = ((problem_->getUpperLimit(var) - oldPosition)) * PseudoRandom::randDouble(); + newPosition = problem_->getUpperLimit(var) - diff; + particle->setValue(var, newPosition); + speed[i][var] = speed[i][var] * -1.0; + } + } + delete particle; } - delete particle; - } } // computeNewPositions @@ -167,19 +191,25 @@ void OMOPSO::computeNewPositions() { /** * Apply a mutation operator to some particles in the swarm */ -void OMOPSO::mopsoMutation(int actualIteration, int totalIterations) { - // There are three groups of particles_, the ones that are mutated with - // a non-uniform mutation operator, the ones that are mutated with a - // uniform mutation and the one that no are mutated - nonUniformMutation->setParameter("currentIteration", &actualIteration); - - for (int i = 0; i < particles->size();i++) { - if (i % 3 == 0) { //particles_ mutated with a non-uniform mutation - nonUniformMutation->execute(particles->get(i)); - } else if (i % 3 == 1) { //particles_ mutated with a uniform mutation operator - uniformMutation->execute(particles->get(i)); - } else {} //particles_ without mutation - } +void OMOPSO::mopsoMutation(int actualIteration, int totalIterations) +{ + // There are three groups of particles_, the ones that are mutated with + // a non-uniform mutation operator, the ones that are mutated with a + // uniform mutation and the one that no are mutated + nonUniformMutation->setParameter("currentIteration", &actualIteration); + + for (int i = 0; i < particles->size(); i++) + { + if (i % 3 == 0) //particles_ mutated with a non-uniform mutation + { + nonUniformMutation->execute(particles->get(i)); + } + else if (i % 3 == 1) //particles_ mutated with a uniform mutation operator + { + uniformMutation->execute(particles->get(i)); + } + else {} //particles_ without mutation + } } // mopsoMutation @@ -188,104 +218,124 @@ void OMOPSO::mopsoMutation(int actualIteration, int totalIterations) { * @return a SolutionSet that is a set of non dominated solutions * as a result of the algorithm execution */ -SolutionSet *OMOPSO::execute() { - - initParams(); - - //->Step 1 (and 3) Create the initial population and evaluate - for (int i = 0; i < particlesSize; i++){ - Solution *particle = new Solution(problem_); - problem_->evaluate(particle); - problem_->evaluateConstraints(particle); - particles->add(particle); - } - - //-> Step2. Initialize the speed of each particle to 0 - for (int i = 0; i < particlesSize; i++) { - speed[i] = new double[problem_->getNumberOfVariables()]; - for (int j = 0; j < problem_->getNumberOfVariables(); j++) { - speed[i][j] = 0.0; - } - } - - // Step4 and 5 - for (int i = 0; i < particles->size(); i++){ - Solution *particle = new Solution(particles->get(i)); - if (leaders->add(particle)){ - Solution *particle2 = new Solution(particle); - if (eArchive->add(particle2) == false) { - delete particle2; - } - } else { - delete particle; +SolutionSet *OMOPSO::execute() +{ + + initParams(); + + //->Step 1 (and 3) Create the initial population and evaluate + for (int i = 0; i < particlesSize; i++) + { + Solution *particle = new Solution(problem_); + problem_->evaluate(particle); + problem_->evaluateConstraints(particle); + particles->add(particle); } - } - - //-> Step 6. Initialize the memory of each particle - for (int i = 0; i < particles->size(); i++){ - Solution *particle = new Solution(particles->get(i)); - best[i] = particle; - } - - //Crowding the leaders_ - distance->crowdingDistanceAssignment(leaders, problem_->getNumberOfObjectives()); - - //-> Step 7. Iterations .. - while (iteration < maxIterations) { - - //Compute the speed_ - computeSpeed(); - - //Compute the new positions for the particles_ - computeNewPositions(); - - //Mutate the particles_ - mopsoMutation(iteration,maxIterations); - - //Evaluate the new particles in new positions - for (int i = 0; i < particles->size(); i++){ - Solution *particle = particles->get(i); - problem_->evaluate(particle); - problem_->evaluateConstraints(particle); + + //-> Step2. Initialize the speed of each particle to 0 + for (int i = 0; i < particlesSize; i++) + { + speed[i] = snew double[problem_->getNumberOfVariables()]; + for (int j = 0; j < problem_->getNumberOfVariables(); j++) + { + speed[i][j] = 0.0; + } } - //Update the archive - for (int i = 0; i < particles->size(); i++) { - Solution *particle = new Solution(particles->get(i)); - if (leaders->add(particle)) { - Solution *particle2 = new Solution(particle); - if (eArchive->add(particle2) == false) { - delete particle2; + // Step4 and 5 + for (int i = 0; i < particles->size(); i++) + { + Solution *particle = new Solution(particles->get(i)); + if (leaders->add(particle)) + { + Solution *particle2 = new Solution(particle); + if (eArchive->add(particle2) == false) + { + delete particle2; + } + } + else + { + delete particle; } - } else { - delete particle; - } } - //Update the memory of this particle - for (int i = 0; i < particles->size(); i++) { - int flag = dominance->compare(particles->get(i), best[i]); - if (flag != 1) { // the new particle is best_ than the older remembered + //-> Step 6. Initialize the memory of each particle + for (int i = 0; i < particles->size(); i++) + { Solution *particle = new Solution(particles->get(i)); - delete best[i]; best[i] = particle; - } } - - //Assign crowding distance to the leaders_ - distance->crowdingDistanceAssignment(leaders, - problem_->getNumberOfObjectives()); - iteration++; - } - - // Build the solution set result - SolutionSet *result = new SolutionSet(leaders->size()); - for (int i=0;isize();i++) { - result->add(new Solution(leaders->get(i))); - } - - // Free memory - deleteParams(); - - return result; + + //Crowding the leaders_ + distance->crowdingDistanceAssignment(leaders, problem_->getNumberOfObjectives()); + + //-> Step 7. Iterations .. + while (iteration < maxIterations) + { + + //Compute the speed_ + computeSpeed(); + + //Compute the new positions for the particles_ + computeNewPositions(); + + //Mutate the particles_ + mopsoMutation(iteration,maxIterations); + + //Evaluate the new particles in new positions + for (int i = 0; i < particles->size(); i++) + { + Solution *particle = particles->get(i); + problem_->evaluate(particle); + problem_->evaluateConstraints(particle); + } + + //Update the archive + for (int i = 0; i < particles->size(); i++) + { + Solution *particle = new Solution(particles->get(i)); + if (leaders->add(particle)) + { + Solution *particle2 = new Solution(particle); + if (eArchive->add(particle2) == false) + { + delete particle2; + } + } + else + { + delete particle; + } + } + + //Update the memory of this particle + for (int i = 0; i < particles->size(); i++) + { + int flag = dominance->compare(particles->get(i), best[i]); + if (flag != 1) // the new particle is best_ than the older remembered + { + Solution *particle = new Solution(particles->get(i)); + delete best[i]; + best[i] = particle; + } + } + + //Assign crowding distance to the leaders_ + distance->crowdingDistanceAssignment(leaders, + problem_->getNumberOfObjectives()); + iteration++; + } + + // Build the solution set result + SolutionSet *result = new SolutionSet(leaders->size()); + for (int i=0; isize(); i++) + { + result->add(new Solution(leaders->get(i))); + } + + // Free memory + deleteParams(); + + return result; } // execute diff --git a/src/metaheuristics/omopso/OMOPSO.h b/src/metaheuristics/omopso/OMOPSO.h index 493a538..ab6acd8 100644 --- a/src/metaheuristics/omopso/OMOPSO.h +++ b/src/metaheuristics/omopso/OMOPSO.h @@ -2,6 +2,7 @@ // // Author: // Esteban López-Camacho +// Sérgio Vieira // // Copyright (c) 2014 Antonio J. Nebro // @@ -34,130 +35,131 @@ /** * This class implements an asynchronous version of OMOPSO algorithm */ -class OMOPSO : public Algorithm { - +class OMOPSO : public Algorithm +{ + private: - - /** - * Stores the number of particles used - */ - int particlesSize; - - /** - * Stores the maximum size for the archive - */ - int archiveSize; - - /** - * Stores the maximum number of iteration_ - */ - int maxIterations; - - /** - * Stores the current number of iteration_ - */ - int iteration; - - /** - * Stores the perturbation used by the non-uniform mutation - */ - double perturbation; - - /** - * Stores the particles - */ - SolutionSet *particles; - - /** - * Stores the best solutions founds so far for each particles - */ - Solution **best; - - /** - * Stores the leaders - */ - CrowdingArchive *leaders; - - /** - * Stores the epsilon-archive - */ - NonDominatedSolutionList *eArchive; - - /** - * Stores the speed of each particle - */ - double **speed; - - /** - * Stores a comparator for checking dominance - */ - Comparator *dominance; - - /** - * Stores a comparator for crowding checking - */ - Comparator *crowdingDistanceComparator; - - /** - * Stores a Distance object - */ - Distance *distance; - - /** - * Stores a operator for uniform mutations - */ - Operator *uniformMutation; - - /** - * Stores a operator for non uniform mutations - */ - Operator *nonUniformMutation; - - /** - * eta_ value - */ - double eta = 0.0075; - - /** - * Initialize all parameter of the algorithm - */ - void initParams(); - - /** - * Free all the memory reserved by the algorithm - */ - void deleteParams(); - - /** - * Update the speed of each particle - */ - void computeSpeed(); - - /** - * Update the position of each particle - */ - void computeNewPositions(); - - /** - * Apply a mutation operator to some particles in the swarm - */ - void mopsoMutation(int actualIteration, int totalIterations); - + + /** + * Stores the number of particles used + */ + int particlesSize; + + /** + * Stores the maximum size for the archive + */ + int archiveSize; + + /** + * Stores the maximum number of iteration_ + */ + int maxIterations; + + /** + * Stores the current number of iteration_ + */ + int iteration; + + /** + * Stores the perturbation used by the non-uniform mutation + */ + double perturbation; + + /** + * Stores the particles + */ + SolutionSet *particles; + + /** + * Stores the best solutions founds so far for each particles + */ + Solution **best; + + /** + * Stores the leaders + */ + CrowdingArchive *leaders; + + /** + * Stores the epsilon-archive + */ + NonDominatedSolutionList *eArchive; + + /** + * Stores the speed of each particle + */ + double **speed; + + /** + * Stores a comparator for checking dominance + */ + Comparator *dominance; + + /** + * Stores a comparator for crowding checking + */ + Comparator *crowdingDistanceComparator; + + /** + * Stores a Distance object + */ + Distance *distance; + + /** + * Stores a operator for uniform mutations + */ + Operator *uniformMutation; + + /** + * Stores a operator for non uniform mutations + */ + Operator *nonUniformMutation; + + /** + * eta_ value + */ + double eta = 0.0075; + + /** + * Initialize all parameter of the algorithm + */ + void initParams(); + + /** + * Free all the memory reserved by the algorithm + */ + void deleteParams(); + + /** + * Update the speed of each particle + */ + void computeSpeed(); + + /** + * Update the position of each particle + */ + void computeNewPositions(); + + /** + * Apply a mutation operator to some particles in the swarm + */ + void mopsoMutation(int actualIteration, int totalIterations); + public: - - /** - * Constructor - * @param problem Problem to solve - */ - OMOPSO(Problem *problem); - - /** - * Runs of the SMPSO algorithm. - * @return a SolutionSet that is a set of non dominated solutions - * as a result of the algorithm execution - */ - SolutionSet *execute(); - + + /** + * Constructor + * @param problem Problem to solve + */ + OMOPSO(Problem *problem); + + /** + * Runs of the SMPSO algorithm. + * @return a SolutionSet that is a set of non dominated solutions + * as a result of the algorithm execution + */ + SolutionSet *execute(); + }; #endif /* OMOPSO_H_ */ diff --git a/src/metaheuristics/paes/CMakeLists.txt b/src/metaheuristics/paes/CMakeLists.txt new file mode 100644 index 0000000..294ec59 --- /dev/null +++ b/src/metaheuristics/paes/CMakeLists.txt @@ -0,0 +1,3 @@ +file(GLOB SOURCES "*.cpp" "*.h") +ListToString(SOURCES ";" ${SOURCES}) +LIST_APPEND("${SOURCES}") \ No newline at end of file diff --git a/src/metaheuristics/paes/paes.cpp b/src/metaheuristics/paes/paes.cpp index 8517171..7444b24 100644 --- a/src/metaheuristics/paes/paes.cpp +++ b/src/metaheuristics/paes/paes.cpp @@ -21,12 +21,12 @@ #include - /** - * Create a new PAES instance for resolve a problem - * @param problem Problem to solve - */ +/** + * Create a new PAES instance for resolve a problem + * @param problem Problem to solve + */ -paes::paes(Problem * problem) : Algorithm(problem){ } +paes::paes(Problem * problem) : Algorithm(problem) { } /** * Tests two solutions to determine which one becomes be the guide of PAES @@ -36,34 +36,39 @@ paes::paes(Problem * problem) : Algorithm(problem){ } */ Solution * paes::test(Solution * solution, Solution * mutatedSolution, - AdaptiveGridArchive * archive){ + AdaptiveGridArchive * archive) +{ int originalLocation = archive->getGrid()->location(solution); int mutatedLocation = archive->getGrid()->location(mutatedSolution); - if (originalLocation == -1) { - return new Solution(mutatedSolution); + if (originalLocation == -1) + { + return new Solution(mutatedSolution); } - if (mutatedLocation == -1) { - return new Solution(solution); + if (mutatedLocation == -1) + { + return new Solution(solution); } if (archive->getGrid()->getLocationDensity(mutatedLocation) < - archive->getGrid()->getLocationDensity(originalLocation)) { - return new Solution(mutatedSolution); + archive->getGrid()->getLocationDensity(originalLocation)) + { + return new Solution(mutatedSolution); } return new Solution(solution); - } // test +} // test - /** - * Runs of the Paes algorithm. - * @return a SolutionSet that is a set of non dominated solutions - * as a result of the algorithm execution - */ +/** +* Runs of the Paes algorithm. +* @return a SolutionSet that is a set of non dominated solutions +* as a result of the algorithm execution +*/ -SolutionSet * paes::execute() { +SolutionSet * paes::execute() +{ int bisections, archiveSize, maxEvaluations, evaluations; AdaptiveGridArchive * archive; @@ -94,32 +99,38 @@ SolutionSet * paes::execute() { archive->add(new Solution(solution),evaluations ); //Iterations.... - do { - // Create the mutate one - Solution * mutatedIndividual = new Solution(solution); - mutationOperator->execute(mutatedIndividual); - - problem_->evaluate(mutatedIndividual); - problem_->evaluateConstraints(mutatedIndividual); - evaluations++; - //<- - - // Check dominance - int flag = dominance->compare(solution,mutatedIndividual); - - if (flag == 1) { //If mutate solution dominate - solution = new Solution(mutatedIndividual); - archive->add(mutatedIndividual,evaluations ); - } else if (flag == 0) { //If none dominate the other - if (archive->add(mutatedIndividual,evaluations )) { - solution = test(solution,mutatedIndividual,archive); + do + { + // Create the mutate one + Solution * mutatedIndividual = new Solution(solution); + mutationOperator->execute(mutatedIndividual); + + problem_->evaluate(mutatedIndividual); + problem_->evaluateConstraints(mutatedIndividual); + evaluations++; + //<- + + // Check dominance + int flag = dominance->compare(solution,mutatedIndividual); + + if (flag == 1) //If mutate solution dominate + { + solution = new Solution(mutatedIndividual); + archive->add(mutatedIndividual,evaluations ); + } + else if (flag == 0) //If none dominate the other + { + if (archive->add(mutatedIndividual,evaluations )) + { + solution = test(solution,mutatedIndividual,archive); + } } - } - } while (evaluations < maxEvaluations); + } + while (evaluations < maxEvaluations); //Return the population of non-dominated solution return archive; - } // execute +} // execute diff --git a/src/metaheuristics/paes/paes.h b/src/metaheuristics/paes/paes.h index b675b04..10fe7bd 100644 --- a/src/metaheuristics/paes/paes.h +++ b/src/metaheuristics/paes/paes.h @@ -27,12 +27,13 @@ #include #include -class paes : public Algorithm { +class paes : public Algorithm +{ public: - paes(Problem * problem); - Solution * test(Solution * solution,Solution * mutatedSolution, - AdaptiveGridArchive * archive); + paes(Problem * problem); + Solution * test(Solution * solution,Solution * mutatedSolution, + AdaptiveGridArchive * archive); SolutionSet * execute(); }; diff --git a/src/metaheuristics/singleObjective/CMakeLists.txt b/src/metaheuristics/singleObjective/CMakeLists.txt new file mode 100644 index 0000000..17ef0be --- /dev/null +++ b/src/metaheuristics/singleObjective/CMakeLists.txt @@ -0,0 +1,4 @@ +add_subdirectory(cmaes) +add_subdirectory(differentialEvolution) +add_subdirectory(geneticAlgorithm) +add_subdirectory(particleSwarmOptimization) \ No newline at end of file diff --git a/src/metaheuristics/singleObjective/cmaes/CMAES.cpp b/src/metaheuristics/singleObjective/cmaes/CMAES.cpp index b0ab8c6..7d6e0e2 100644 --- a/src/metaheuristics/singleObjective/cmaes/CMAES.cpp +++ b/src/metaheuristics/singleObjective/cmaes/CMAES.cpp @@ -2,6 +2,7 @@ // // Author: // Esteban López-Camacho +// Sérgio Vieira // // Copyright (c) 2011 Antonio J. Nebro, Juan J. Durillo // @@ -31,461 +32,527 @@ * Constructor * @param problem Problem to solve */ -CMAES::CMAES(Problem *problem) : Algorithm(problem) { - bestSolutionEver = NULL; +CMAES::CMAES(Problem *problem) : Algorithm(problem) +{ + bestSolutionEver = nullptr; } // CMAES -SolutionSet * CMAES::execute() { - - - //Read the parameters - populationSize = *(int *) getInputParameter("populationSize"); - maxEvaluations = *(int *) getInputParameter("maxEvaluations"); - - //Initialize the variables - counteval = 0; - - Comparator * comparator = new ObjectiveComparator(0); - - init(); - - // iteration loop - while (counteval < maxEvaluations) { - - // --- core iteration step --- - population_ = samplePopulation(); // get a new population of solutions - - for(int i = 0; i < populationSize; i++) { - if (!isFeasible(population_->get(i))) { - //cout << "RESAMPLING!" << endl; - population_->replace(i, resampleSingle(i)); - } - problem_->evaluate(population_->get(i)); +SolutionSet * CMAES::execute() +{ + + + //Read the parameters + populationSize = *(int *) getInputParameter("populationSize"); + maxEvaluations = *(int *) getInputParameter("maxEvaluations"); + + //Initialize the variables + counteval = 0; + + Comparator * comparator = snew ObjectiveComparator(0); + + init(); + + // iteration loop + while (counteval < maxEvaluations) + { + + // --- core iteration step --- + population_ = samplePopulation(); // get a new population of solutions + + for(int i = 0; i < populationSize; i++) + { + if (!isFeasible(population_->get(i))) + { + //std::cout << "RESAMPLING!" << std::endl; + population_->replace(i, resampleSingle(i)); + } + problem_->evaluate(population_->get(i)); + } + counteval += populationSize; + + storeBest(comparator); + //std::cout << counteval << ": " << bestSolutionEver->getObjective(0) << std::endl; + updateDistribution(); + + delete population_; + } - counteval += populationSize; - - storeBest(comparator); - //cout << counteval << ": " << bestSolutionEver->getObjective(0) << endl; - updateDistribution(); - - delete population_; - - } - - deleteParams(); - - delete comparator ; - - SolutionSet * resultPopulation = new SolutionSet(1) ; - resultPopulation->add(bestSolutionEver) ; - - return resultPopulation ; - + + deleteParams(); + + delete comparator ; + + SolutionSet * resultPopulation = snew SolutionSet(1) ; + resultPopulation->add(bestSolutionEver) ; + + return resultPopulation ; + } // execute -void CMAES::init() { - - /*User defined input parameters */ - - // number of objective variables/problem dimension - int N = problem_->getNumberOfVariables(); - - // objective variables initial point - default_random_engine generator; - xmean = new double[N]; - for (int i = 0; i < N; i++) { - double stddev = (problem_->getUpperLimit(i) - problem_->getLowerLimit(i)) /2; - double mean = problem_->getLowerLimit(i) + stddev; - normal_distribution distribution(mean,stddev/2); - xmean[i] = distribution(generator); - //xmean[i] = PseudoRandom::randDouble(0, 1); - } - - // coordinate wise standard deviation (step size) - sigma = 0.3; - //sigma = 1; - - /* Strategy parameter setting: Selection */ - - // population size, offspring number - int lambda = populationSize; - //lambda = 4+Math.floor(3*Math.log(N)); - - // number of parents/points for recombination - mu = (int) floor(lambda/2); - - // muXone array for weighted recombination - weights = new double[mu]; - double sum = 0; - for (int i=0; igetNumberOfVariables(); + + // objective variables initial point + default_random_engine generator; + xmean = snew double[N]; + for (int i = 0; i < N; i++) + { + double stddev = (problem_->getUpperLimit(i) - problem_->getLowerLimit(i)) /2; + double mean = problem_->getLowerLimit(i) + stddev; + normal_distribution distribution(mean,stddev/2); + xmean[i] = distribution(generator); + //xmean[i] = PseudoRandom::randDouble(0, 1); } - for (int j = 0; j < i; j++) { - C[i][j] = 0; + + // coordinate wise standard deviation (step size) + sigma = 0.3; + //sigma = 1; + + /* Strategy parameter setting: Selection */ + + // population size, offspring number + int lambda = populationSize; + //lambda = 4+Math.floor(3*Math.log(N)); + + // number of parents/points for recombination + mu = (int) floor(lambda/2); + + // muXone array for weighted recombination + weights = snew double[mu]; + double sum = 0; + for (int i=0; i distribution(0.0,1.0); - - int N = problem_->getNumberOfVariables(); - double * artmp = new double[N]; - double sum; - - for (int iNk = 0; iNk < populationSize; iNk++) { - - for (int i = 0; i < N; i++) { - //artmp[i] = diagD[i] * PseudoRandom::randDouble(-2, 2); - artmp[i] = diagD[i] * distribution(generator); + // evolution paths for C and sigma + pc = snew double[N]; + ps = snew double[N]; + + // B defines the coordinate system + B = snew double*[N]; + // covariance matrix C + C = snew double*[N]; + for (int i = 0; i < N; i++) + { + B[i] = snew double[N]; + C[i] = snew double[N]; + } + + // C^-1/2 + invsqrtC = snew double*[N]; + for (int i = 0; i < N; i++) + { + invsqrtC[i] = snew double[N]; + pc[i] = 0; + ps[i] = 0; + diagD[i] = 1; + for (int j = 0; j < N; j++) + { + B[i][j] = 0; + invsqrtC[i][j] = 0; + } + for (int j = 0; j < i; j++) + { + C[i][j] = 0; + } + B[i][i] = 1; + C[i][i] = diagD[i] * diagD[i]; + invsqrtC[i][i] = 1; } - for (int i = 0; i < N; i++) { - sum = 0.0; - for (int j = 0; j < N; j++) { - sum += B[i][j] * artmp[j]; - } - arx[iNk][i] = xmean[i] + sigma * sum; + + // track update of B and D + eigeneval = 0; + + chiN = sqrt(N) * ( 1 - 1/(4*N) + 1/(21*N*N) ); + + /* non-settable parameters */ + + xold = snew double[N]; + arx = snew double*[lambda]; + for (int i = 0; i < lambda; i++) + { + arx[i] = snew double[N]; } - } - - delete [] artmp; - - return genoPhenoTransformation(arx); - + +} // init + + +SolutionSet * CMAES::samplePopulation() +{ + + default_random_engine generator; + normal_distribution distribution(0.0,1.0); + + int N = problem_->getNumberOfVariables(); + double * artmp = snew double[N]; + double sum; + + for (int iNk = 0; iNk < populationSize; iNk++) + { + + for (int i = 0; i < N; i++) + { + //artmp[i] = diagD[i] * PseudoRandom::randDouble(-2, 2); + artmp[i] = diagD[i] * distribution(generator); + } + for (int i = 0; i < N; i++) + { + sum = 0.0; + for (int j = 0; j < N; j++) + { + sum += B[i][j] * artmp[j]; + } + arx[iNk][i] = xmean[i] + sigma * sum; + } + } + + delete [] artmp; + + return genoPhenoTransformation(arx); + } // samplePopulation -SolutionSet * CMAES::genoPhenoTransformation(double ** popx) { +SolutionSet * CMAES::genoPhenoTransformation(double ** popx) +{ - SolutionSet * population_ = new SolutionSet(populationSize); - for (int i = 0; i < populationSize; i++) { - Solution * solution = new Solution(problem_); - for (int j = 0; j < problem_->getNumberOfVariables(); j++) { - solution->getDecisionVariables()[j]->setValue(popx[i][j]); + SolutionSet * population_ = snew SolutionSet(populationSize); + for (int i = 0; i < populationSize; i++) + { + Solution * solution = snew Solution(problem_); + for (int j = 0; j < problem_->getNumberOfVariables(); j++) + { + solution->getDecisionVariables()[j]->setValue(popx[i][j]); + } + population_->add(solution); } - population_->add(solution); - } - return population_; + return population_; } // genoPhenoTransformation -bool CMAES::isFeasible(Solution * solution) { +bool CMAES::isFeasible(Solution * solution) +{ - bool res = true; - Variable ** x = solution->getDecisionVariables(); + bool res = true; + Variable ** x = solution->getDecisionVariables(); - for (int i = 0; i < problem_->getNumberOfVariables(); i++) { - double value = x[i]->getValue(); - if ((value < problem_->getLowerLimit(i)) || (value > problem_->getUpperLimit(i))) { - res = false; + for (int i = 0; i < problem_->getNumberOfVariables(); i++) + { + double value = x[i]->getValue(); + if ((value < problem_->getLowerLimit(i)) || (value > problem_->getUpperLimit(i))) + { + res = false; + } } - } - return res; + return res; } // isFeasible -Solution * CMAES::resampleSingle(int iNk) { +Solution * CMAES::resampleSingle(int iNk) +{ - for (int i = 0; i < problem_->getNumberOfVariables(); i++) { - if (arx[iNk][i] > problem_->getUpperLimit(i)) { - arx[iNk][i] = problem_->getUpperLimit(i); - } else if (arx[iNk][i] < problem_->getLowerLimit(i)) { - arx[iNk][i] = problem_->getLowerLimit(i); + for (int i = 0; i < problem_->getNumberOfVariables(); i++) + { + if (arx[iNk][i] > problem_->getUpperLimit(i)) + { + arx[iNk][i] = problem_->getUpperLimit(i); + } + else if (arx[iNk][i] < problem_->getLowerLimit(i)) + { + arx[iNk][i] = problem_->getLowerLimit(i); + } } - } - return genoPhenoTransformation(arx[iNk]); + return genoPhenoTransformation(arx[iNk]); } // resampleSingle -Solution * CMAES::genoPhenoTransformation(double * x) { +Solution * CMAES::genoPhenoTransformation(double * x) +{ - Solution * solution = new Solution(problem_); - for (int i = 0; i < problem_->getNumberOfVariables(); i++) { - solution->getDecisionVariables()[i]->setValue(x[i]); - } - return solution; + Solution * solution = snew Solution(problem_); + for (int i = 0; i < problem_->getNumberOfVariables(); i++) + { + solution->getDecisionVariables()[i]->setValue(x[i]); + } + return solution; } // genoPhenoTransformation -void CMAES::storeBest(Comparator * comparator) { +void CMAES::storeBest(Comparator * comparator) +{ - Solution * bestInPopulation = new Solution(population_->best(comparator)); - if ((bestSolutionEver == NULL) || - (bestSolutionEver->getObjective(0) - > bestInPopulation->getObjective(0))) { - if (bestSolutionEver != NULL) { - delete bestSolutionEver; + Solution * bestInPopulation = snew Solution(population_->best(comparator)); + if ((bestSolutionEver == nullptr) || + (bestSolutionEver->getObjective(0) + > bestInPopulation->getObjective(0))) + { + if (bestSolutionEver != nullptr) + { + delete bestSolutionEver; + } + bestSolutionEver = bestInPopulation; + } + else + { + delete bestInPopulation; } - bestSolutionEver = bestInPopulation; - } else { - delete bestInPopulation; - } } // storeBest - - -void CMAES::updateDistribution() { - - int N = problem_->getNumberOfVariables(); - int lambda = populationSize; - - double * arfitness = new double[lambda]; - int * arindex = new int[lambda]; - - /* Sort by fitness and compute weighted mean into xmean */ - - //minimization - for (int i = 0; i < lambda; i++) { - arfitness[i] = population_->get(i)->getObjective(0); - arindex[i] = i; - } - UtilsCMAES::minFastSort(arfitness, arindex, lambda); - - // calculate xmean and BDz~N(0,C) - for (int i = 0; i < N; i++) { - xold[i] = xmean[i]; - xmean[i] = 0.; - for (int iNk = 0; iNk < mu; iNk++) { - xmean[i] += weights[iNk] * arx[arindex[iNk]][i]; + + +void CMAES::updateDistribution() +{ + + int N = problem_->getNumberOfVariables(); + int lambda = populationSize; + + double * arfitness = snew double[lambda]; + int * arindex = snew int[lambda]; + + /* Sort by fitness and compute weighted mean into xmean */ + + //minimization + for (int i = 0; i < lambda; i++) + { + arfitness[i] = population_->get(i)->getObjective(0); + arindex[i] = i; } - //BDz[i] = sqrt(sp->getMueff()) * (xmean[i] - xold[i]) / sigma; - } - - /* Cumulation: Update evolution paths */ - - double * artmp = new double[N]; - for (int i = 0; i < N; i++) { - artmp[i] = 0; - //double value = (xmean[i] - xold[i]) / sigma; - for (int j = 0; j < N; j++) { - //artmp[i] += invsqrtC[i][j] * value; - artmp[i] += invsqrtC[i][j] * (xmean[j] - xold[j]) / sigma; + UtilsCMAES::minFastSort(arfitness, arindex, lambda); + + // calculate xmean and BDz~N(0,C) + for (int i = 0; i < N; i++) + { + xold[i] = xmean[i]; + xmean[i] = 0.; + for (int iNk = 0; iNk < mu; iNk++) + { + xmean[i] += weights[iNk] * arx[arindex[iNk]][i]; + } + //BDz[i] = sqrt(sp->getMueff()) * (xmean[i] - xold[i]) / sigma; } - } - // cumulation for sigma (ps) - for (int i = 0; i < N; i++) { - ps[i] = (1. - cs) * ps[i] - + sqrt(cs * (2. - cs) * mueff) - * artmp[i]; - } - - // calculate norm(ps)^2 - double psxps = 0.0; - for (int i = 0; i < N; i++) { - psxps += ps[i] * ps[i]; - } - - // cumulation for covariance matrix (pc) - int hsig = 0; - if ((sqrt(psxps) / sqrt(1. - pow(1. - cs, 2. * counteval/lambda)) / chiN) - < (1.4 + 2. / (N + 1.))) { - hsig = 1; - } - for (int i = 0; i < N; i++) { - pc[i] = (1. - cc) * pc[i] - + hsig * sqrt(cc * (2. - cc) * mueff) * (xmean[i] - xold[i]) / sigma; - } - - /* Adapt covariance matrix C */ - - for (int i = 0; i < N; i++) { - for (int j = 0; j <= i; j++) { - C[i][j] = (1 - c1 -cmu) - * C[i][j] - + c1 - * (pc[i] * pc[j] + (1 - hsig) * cc - * (2. - cc) * C[i][j]); - for (int k = 0; k < mu; k++) { - /* - * additional rank mu - * update - */ - C[i][j] += cmu - * weights[k] - * (arx[arindex[k]][i] - xold[i]) - * (arx[arindex[k]][j] - xold[j]) / sigma - / sigma; - } + + /* Cumulation: Update evolution paths */ + + double * artmp = snew double[N]; + for (int i = 0; i < N; i++) + { + artmp[i] = 0; + //double value = (xmean[i] - xold[i]) / sigma; + for (int j = 0; j < N; j++) + { + //artmp[i] += invsqrtC[i][j] * value; + artmp[i] += invsqrtC[i][j] * (xmean[j] - xold[j]) / sigma; + } } - } - - /* Adapt step size sigma */ - - sigma *= exp((cs/damps) * (sqrt(psxps)/chiN - 1)); - - /* Decomposition of C into B*diag(D.^2)*B' (diagonalization) */ - - if (counteval - eigeneval > lambda /(c1+cmu)/N/10) { // to achieve O(N^2) - - eigeneval = counteval; - - // enforce symmetry - for (int i = 0; i < N; i++) { - for (int j = 0; j <= i; j++) { - B[i][j] = B[j][i] = C[i][j]; - } + // cumulation for sigma (ps) + for (int i = 0; i < N; i++) + { + ps[i] = (1. - cs) * ps[i] + + sqrt(cs * (2. - cs) * mueff) + * artmp[i]; } - - // eigen decomposition, B==normalized eigenvectors - double * offdiag = new double[N]; - UtilsCMAES::tred2(N, B, diagD, offdiag); - UtilsCMAES::tql2(N, diagD, offdiag, B); - if (UtilsCMAES::checkEigenSystem(N, C, diagD, B) > 0) { // for debugging - counteval = maxEvaluations; + + // calculate norm(ps)^2 + double psxps = 0.0; + for (int i = 0; i < N; i++) + { + psxps += ps[i] * ps[i]; } - - for (int i = 0; i < N; i++) { - if (diagD[i] < 0) { // numerical problem? - cerr << "CMAES::updateDistribution(): WARNING - an eigenvalue has become negative." << endl; - counteval = maxEvaluations; - //throw new JMException("Exception in CMAES.execute(): an eigenvalue has become negative.") ; - } - diagD[i] = sqrt(diagD[i]); + + // cumulation for covariance matrix (pc) + int hsig = 0; + if ((sqrt(psxps) / sqrt(1. - pow(1. - cs, 2. * counteval/lambda)) / chiN) + < (1.4 + 2. / (N + 1.))) + { + hsig = 1; } - // diagD is a vector of standard deviations now - - //invsqrtC = B * diag(D.^-1) * B'; - double ** artmp2 = new double*[N]; - for (int i = 0; i < N; i++) { - artmp2[i] = new double[N]; - //double value = (xmean[i] - xold[i]) / sigma; - for (int j = 0; j < N; j++) { - artmp2[i][j] = B[i][j] * (1/diagD[j]); - } + for (int i = 0; i < N; i++) + { + pc[i] = (1. - cc) * pc[i] + + hsig * sqrt(cc * (2. - cc) * mueff) * (xmean[i] - xold[i]) / sigma; } - for (int i = 0; i < N; i++) { - //double value = (xmean[i] - xold[i]) / sigma; - for (int j = 0; j < N; j++) { - invsqrtC[i][j] = 0.0; - for (int k = 0; k < N; k++) { - invsqrtC[i][j] += artmp2[i][k] * B[j][k]; + + /* Adapt covariance matrix C */ + + for (int i = 0; i < N; i++) + { + for (int j = 0; j <= i; j++) + { + C[i][j] = (1 - c1 -cmu) + * C[i][j] + + c1 + * (pc[i] * pc[j] + (1 - hsig) * cc + * (2. - cc) * C[i][j]); + for (int k = 0; k < mu; k++) + { + /* + * additional rank mu + * update + */ + C[i][j] += cmu + * weights[k] + * (arx[arindex[k]][i] - xold[i]) + * (arx[arindex[k]][j] - xold[j]) / sigma + / sigma; + } } - } } - - for (int i = 0; i < N; i++) { - delete [] artmp2[i]; + + /* Adapt step size sigma */ + + sigma *= exp((cs/damps) * (sqrt(psxps)/chiN - 1)); + + /* Decomposition of C into B*diag(D.^2)*B' (diagonalization) */ + + if (counteval - eigeneval > lambda /(c1+cmu)/N/10) // to achieve O(N^2) + { + + eigeneval = counteval; + + // enforce symmetry + for (int i = 0; i < N; i++) + { + for (int j = 0; j <= i; j++) + { + B[i][j] = B[j][i] = C[i][j]; + } + } + + // eigen decomposition, B==normalized eigenvectors + double * offdiag = snew double[N]; + UtilsCMAES::tred2(N, B, diagD, offdiag); + UtilsCMAES::tql2(N, diagD, offdiag, B); + if (UtilsCMAES::checkEigenSystem(N, C, diagD, B) > 0) // for debugging + { + counteval = maxEvaluations; + } + + for (int i = 0; i < N; i++) + { + if (diagD[i] < 0) // numerical problem? + { + cerr << "CMAES::updateDistribution(): WARNING - an eigenvalue has become negative." << std::endl; + counteval = maxEvaluations; + //throw new JMException("Exception in CMAES.execute(): an eigenvalue has become negative.") ; + } + diagD[i] = sqrt(diagD[i]); + } + // diagD is a vector of standard deviations now + + //invsqrtC = B * diag(D.^-1) * B'; + double ** artmp2 = snew double*[N]; + for (int i = 0; i < N; i++) + { + artmp2[i] = snew double[N]; + //double value = (xmean[i] - xold[i]) / sigma; + for (int j = 0; j < N; j++) + { + artmp2[i][j] = B[i][j] * (1/diagD[j]); + } + } + for (int i = 0; i < N; i++) + { + //double value = (xmean[i] - xold[i]) / sigma; + for (int j = 0; j < N; j++) + { + invsqrtC[i][j] = 0.0; + for (int k = 0; k < N; k++) + { + invsqrtC[i][j] += artmp2[i][k] * B[j][k]; + } + } + } + + for (int i = 0; i < N; i++) + { + delete [] artmp2[i]; + } + delete [] offdiag; + delete [] artmp2; + } - delete [] offdiag; - delete [] artmp2; - } - - delete [] arfitness; - delete [] arindex; - delete [] artmp; + delete [] arfitness; + delete [] arindex; + delete [] artmp; } // updateDistribution() -void CMAES::deleteParams() { - int N = problem_->getNumberOfVariables(); - int lambda = populationSize; - delete [] xmean; - delete [] weights; - delete [] diagD; - delete [] pc; - delete [] ps; - for (int i = 0; i < N; i++) { - delete [] B[i]; - delete [] C[i]; - delete [] invsqrtC[i]; - } - delete [] B; - delete [] C; - delete [] invsqrtC; - delete [] xold; - for (int i = 0; i < lambda; i++) { - delete [] arx[i]; - } - delete [] arx; +void CMAES::deleteParams() +{ + int N = problem_->getNumberOfVariables(); + int lambda = populationSize; + delete [] xmean; + delete [] weights; + delete [] diagD; + delete [] pc; + delete [] ps; + for (int i = 0; i < N; i++) + { + delete [] B[i]; + delete [] C[i]; + delete [] invsqrtC[i]; + } + delete [] B; + delete [] C; + delete [] invsqrtC; + delete [] xold; + for (int i = 0; i < lambda; i++) + { + delete [] arx[i]; + } + delete [] arx; } // freeMemory diff --git a/src/metaheuristics/singleObjective/cmaes/CMAES.h b/src/metaheuristics/singleObjective/cmaes/CMAES.h index 7e007c8..2150a7c 100644 --- a/src/metaheuristics/singleObjective/cmaes/CMAES.h +++ b/src/metaheuristics/singleObjective/cmaes/CMAES.h @@ -2,6 +2,7 @@ // // Author: // Esteban López-Camacho +// Sérgio Vieira // // Copyright (c) 2011 Antonio J. Nebro, Juan J. Durillo // @@ -37,30 +38,31 @@ * This class implements the CMA-ES algorithm. */ -class CMAES : public Algorithm { +class CMAES : public Algorithm +{ + +private: - private: - /** * Stores the population size */ int populationSize; - + int counteval; int maxEvaluations; - + double sigma; - + double * xmean; double * xold; - + /* * Strategy parameter setting: Selection */ int mu; double * weights; double mueff; - + /* * Strategy parameter setting: Adaptation */ @@ -69,7 +71,7 @@ class CMAES : public Algorithm { double c1; double cmu; double damps; - + /* * Dynamic (internal) strategy parameters and constants */ @@ -81,11 +83,11 @@ class CMAES : public Algorithm { double ** invsqrtC; int eigeneval; double chiN; - + double ** arx; SolutionSet * population_; Solution * bestSolutionEver; - + void init(); SolutionSet * samplePopulation(); SolutionSet * genoPhenoTransformation(double ** popx); @@ -95,8 +97,8 @@ class CMAES : public Algorithm { void storeBest(Comparator * comparator); void updateDistribution(); void deleteParams(); - - public: + +public: CMAES(Problem * problem); SolutionSet * execute(); diff --git a/src/metaheuristics/singleObjective/cmaes/CMakeLists.txt b/src/metaheuristics/singleObjective/cmaes/CMakeLists.txt new file mode 100644 index 0000000..7122541 --- /dev/null +++ b/src/metaheuristics/singleObjective/cmaes/CMakeLists.txt @@ -0,0 +1,4 @@ +file(GLOB SOURCES "*.cpp" "*.h") +ListToString(SOURCES ";" ${SOURCES}) +LIST_APPEND("${SOURCES}") +add_subdirectory(utils) \ No newline at end of file diff --git a/src/metaheuristics/singleObjective/cmaes/utils/CMakeLists.txt b/src/metaheuristics/singleObjective/cmaes/utils/CMakeLists.txt new file mode 100644 index 0000000..294ec59 --- /dev/null +++ b/src/metaheuristics/singleObjective/cmaes/utils/CMakeLists.txt @@ -0,0 +1,3 @@ +file(GLOB SOURCES "*.cpp" "*.h") +ListToString(SOURCES ";" ${SOURCES}) +LIST_APPEND("${SOURCES}") \ No newline at end of file diff --git a/src/metaheuristics/singleObjective/cmaes/utils/UtilsCMAES.cpp b/src/metaheuristics/singleObjective/cmaes/utils/UtilsCMAES.cpp index 70610e8..b40215a 100644 --- a/src/metaheuristics/singleObjective/cmaes/utils/UtilsCMAES.cpp +++ b/src/metaheuristics/singleObjective/cmaes/utils/UtilsCMAES.cpp @@ -2,6 +2,7 @@ // // Author: // Esteban López-Camacho +// Sérgio Vieira // // Copyright (c) 2011 Antonio J. Nebro, Juan J. Durillo // @@ -30,119 +31,144 @@ /** * Symmetric Householder reduction to tridiagonal form, taken from JAMA package. */ -void UtilsCMAES::tred2 (int n, double ** V, double * d, double * e) { +void UtilsCMAES::tred2 (int n, double ** V, double * d, double * e) +{ - // This is derived from the Algol procedures tred2 by - // Bowdler, Martin, Reinsch, and Wilkinson, Handbook for - // Auto. Comp., Vol.ii-Linear Algebra, and the corresponding - // Fortran subroutine in EISPACK. + // This is derived from the Algol procedures tred2 by + // Bowdler, Martin, Reinsch, and Wilkinson, Handbook for + // Auto. Comp., Vol.ii-Linear Algebra, and the corresponding + // Fortran subroutine in EISPACK. - for (int j = 0; j < n; j++) { - d[j] = V[n-1][j]; - } + for (int j = 0; j < n; j++) + { + d[j] = V[n-1][j]; + } - // Householder reduction to tridiagonal form. + // Householder reduction to tridiagonal form. - for (int i = n-1; i > 0; i--) { + for (int i = n-1; i > 0; i--) + { - // Scale to avoid under/overflow. + // Scale to avoid under/overflow. - double scale = 0.0; - double h = 0.0; - for (int k = 0; k < i; k++) { - scale = scale + fabs(d[k]); - } - if (scale == 0.0) { - e[i] = d[i-1]; - for (int j = 0; j < i; j++) { - d[j] = V[i-1][j]; - V[i][j] = 0.0; - V[j][i] = 0.0; - } - } else { - - // Generate Householder vector. - - for (int k = 0; k < i; k++) { - d[k] /= scale; - h += d[k] * d[k]; - } - double f = d[i-1]; - double g = sqrt(h); - if (f > 0) { - g = -g; - } - e[i] = scale * g; - h = h - f * g; - d[i-1] = f - g; - for (int j = 0; j < i; j++) { - e[j] = 0.0; - } - - // Apply similarity transformation to remaining columns. - - for (int j = 0; j < i; j++) { - f = d[j]; - V[j][i] = f; - g = e[j] + V[j][j] * f; - for (int k = j+1; k <= i-1; k++) { - g += V[k][j] * d[k]; - e[k] += V[k][j] * f; + double scale = 0.0; + double h = 0.0; + for (int k = 0; k < i; k++) + { + scale = scale + fabs(d[k]); + } + if (scale == 0.0) + { + e[i] = d[i-1]; + for (int j = 0; j < i; j++) + { + d[j] = V[i-1][j]; + V[i][j] = 0.0; + V[j][i] = 0.0; + } } - e[j] = g; - } - f = 0.0; - for (int j = 0; j < i; j++) { - e[j] /= h; - f += e[j] * d[j]; - } - double hh = f / (h + h); - for (int j = 0; j < i; j++) { - e[j] -= hh * d[j]; - } - for (int j = 0; j < i; j++) { - f = d[j]; - g = e[j]; - for (int k = j; k <= i-1; k++) { - V[k][j] -= (f * e[k] + g * d[k]); + else + { + + // Generate Householder vector. + + for (int k = 0; k < i; k++) + { + d[k] /= scale; + h += d[k] * d[k]; + } + double f = d[i-1]; + double g = sqrt(h); + if (f > 0) + { + g = -g; + } + e[i] = scale * g; + h = h - f * g; + d[i-1] = f - g; + for (int j = 0; j < i; j++) + { + e[j] = 0.0; + } + + // Apply similarity transformation to remaining columns. + + for (int j = 0; j < i; j++) + { + f = d[j]; + V[j][i] = f; + g = e[j] + V[j][j] * f; + for (int k = j+1; k <= i-1; k++) + { + g += V[k][j] * d[k]; + e[k] += V[k][j] * f; + } + e[j] = g; + } + f = 0.0; + for (int j = 0; j < i; j++) + { + e[j] /= h; + f += e[j] * d[j]; + } + double hh = f / (h + h); + for (int j = 0; j < i; j++) + { + e[j] -= hh * d[j]; + } + for (int j = 0; j < i; j++) + { + f = d[j]; + g = e[j]; + for (int k = j; k <= i-1; k++) + { + V[k][j] -= (f * e[k] + g * d[k]); + } + d[j] = V[i-1][j]; + V[i][j] = 0.0; + } } - d[j] = V[i-1][j]; - V[i][j] = 0.0; - } + d[i] = h; } - d[i] = h; - } - - // Accumulate transformations. - - for (int i = 0; i < n-1; i++) { - V[n-1][i] = V[i][i]; - V[i][i] = 1.0; - double h = d[i+1]; - if (h != 0.0) { - for (int k = 0; k <= i; k++) { - d[k] = V[k][i+1] / h; - } - for (int j = 0; j <= i; j++) { - double g = 0.0; - for (int k = 0; k <= i; k++) { - g += V[k][i+1] * V[k][j]; + + // Accumulate transformations. + + for (int i = 0; i < n-1; i++) + { + V[n-1][i] = V[i][i]; + V[i][i] = 1.0; + double h = d[i+1]; + if (h != 0.0) + { + for (int k = 0; k <= i; k++) + { + d[k] = V[k][i+1] / h; + } + for (int j = 0; j <= i; j++) + { + double g = 0.0; + for (int k = 0; k <= i; k++) + { + g += V[k][i+1] * V[k][j]; + } + for (int k = 0; k <= i; k++) + { + V[k][j] -= g * d[k]; + } + } } - for (int k = 0; k <= i; k++) { - V[k][j] -= g * d[k]; + for (int k = 0; k <= i; k++) + { + V[k][i+1] = 0.0; } - } } - for (int k = 0; k <= i; k++) { - V[k][i+1] = 0.0; + for (int j = 0; j < n; j++) + { + d[j] = V[n-1][j]; + V[n-1][j] = 0.0; } - } - for (int j = 0; j < n; j++) { - d[j] = V[n-1][j]; - V[n-1][j] = 0.0; - } - V[n-1][n-1] = 1.0; - e[0] = 0.0; + V[n-1][n-1] = 1.0; + e[0] = 0.0; } // tred2 @@ -150,207 +176,240 @@ void UtilsCMAES::tred2 (int n, double ** V, double * d, double * e) { /** * Symmetric tridiagonal QL algorithm, taken from JAMA package. */ -void UtilsCMAES::tql2 (int n, double * d, double * e, double ** V) { - - // This is derived from the Algol procedures tql2, by - // Bowdler, Martin, Reinsch, and Wilkinson, Handbook for - // Auto. Comp., Vol.ii-Linear Algebra, and the corresponding - // Fortran subroutine in EISPACK. - - for (int i = 1; i < n; i++) { - e[i-1] = e[i]; - } - e[n-1] = 0.0; - - double f = 0.0; - double tst1 = 0.0; - double eps = pow(2.0,-52.0); - for (int l = 0; l < n; l++) { - - // Find small subdiagonal element - - tst1 = fmax(tst1,fabs(d[l]) + fabs(e[l])); - int m = l; - while (m < n) { - if (fabs(e[m]) <= eps*tst1) { - break; - } - m++; - } - - // If m == l, d[l] is an eigenvalue, - // otherwise, iterate. +void UtilsCMAES::tql2 (int n, double * d, double * e, double ** V) +{ - if (m > l) { - int iter = 0; - do { - iter = iter + 1; // (Could check iteration count here.) + // This is derived from the Algol procedures tql2, by + // Bowdler, Martin, Reinsch, and Wilkinson, Handbook for + // Auto. Comp., Vol.ii-Linear Algebra, and the corresponding + // Fortran subroutine in EISPACK. - // Compute implicit shift + for (int i = 1; i < n; i++) + { + e[i-1] = e[i]; + } + e[n-1] = 0.0; + + double f = 0.0; + double tst1 = 0.0; + double eps = pow(2.0,-52.0); + for (int l = 0; l < n; l++) + { + + // Find small subdiagonal element + + tst1 = fmax(tst1,fabs(d[l]) + fabs(e[l])); + int m = l; + while (m < n) + { + if (fabs(e[m]) <= eps*tst1) + { + break; + } + m++; + } - double g = d[l]; - double p = (d[l+1] - g) / (2.0 * e[l]); - double r = hypot(p,1.0); - if (p < 0) { - r = -r; + // If m == l, d[l] is an eigenvalue, + // otherwise, iterate. + + if (m > l) + { + int iter = 0; + do + { + iter = iter + 1; // (Could check iteration count here.) + + // Compute implicit shift + + double g = d[l]; + double p = (d[l+1] - g) / (2.0 * e[l]); + double r = hypot(p,1.0); + if (p < 0) + { + r = -r; + } + d[l] = e[l] / (p + r); + d[l+1] = e[l] * (p + r); + double dl1 = d[l+1]; + double h = g - d[l]; + for (int i = l+2; i < n; i++) + { + d[i] -= h; + } + f = f + h; + + // Implicit QL transformation. + + p = d[m]; + double c = 1.0; + double c2 = c; + double c3 = c; + double el1 = e[l+1]; + double s = 0.0; + double s2 = 0.0; + for (int i = m-1; i >= l; i--) + { + c3 = c2; + c2 = c; + s2 = s; + g = c * e[i]; + h = c * p; + r = hypot(p,e[i]); + e[i+1] = s * r; + s = e[i] / r; + c = p / r; + p = c * d[i] - s * g; + d[i+1] = h + s * (c * g + s * d[i]); + + // Accumulate transformation. + + for (int k = 0; k < n; k++) + { + h = V[k][i+1]; + V[k][i+1] = s * V[k][i] + c * h; + V[k][i] = c * V[k][i] - s * h; + } + } + p = -s * s2 * c3 * el1 * e[l] / dl1; + e[l] = s * p; + d[l] = c * p; + + // Check for convergence. + + } + while (fabs(e[l]) > eps*tst1); } - d[l] = e[l] / (p + r); - d[l+1] = e[l] * (p + r); - double dl1 = d[l+1]; - double h = g - d[l]; - for (int i = l+2; i < n; i++) { - d[i] -= h; + d[l] = d[l] + f; + e[l] = 0.0; + } + + // Sort eigenvalues and corresponding vectors. + + for (int i = 0; i < n-1; i++) + { + int k = i; + double p = d[i]; + for (int j = i+1; j < n; j++) + { + if (d[j] < p) // NH find smallest k>i + { + k = j; + p = d[j]; + } } - f = f + h; - - // Implicit QL transformation. - - p = d[m]; - double c = 1.0; - double c2 = c; - double c3 = c; - double el1 = e[l+1]; - double s = 0.0; - double s2 = 0.0; - for (int i = m-1; i >= l; i--) { - c3 = c2; - c2 = c; - s2 = s; - g = c * e[i]; - h = c * p; - r = hypot(p,e[i]); - e[i+1] = s * r; - s = e[i] / r; - c = p / r; - p = c * d[i] - s * g; - d[i+1] = h + s * (c * g + s * d[i]); - - // Accumulate transformation. - - for (int k = 0; k < n; k++) { - h = V[k][i+1]; - V[k][i+1] = s * V[k][i] + c * h; - V[k][i] = c * V[k][i] - s * h; - } + if (k != i) + { + d[k] = d[i]; // swap k and i + d[i] = p; + for (int j = 0; j < n; j++) + { + p = V[j][i]; + V[j][i] = V[j][k]; + V[j][k] = p; + } } - p = -s * s2 * c3 * el1 * e[l] / dl1; - e[l] = s * p; - d[l] = c * p; - - // Check for convergence. - - } while (fabs(e[l]) > eps*tst1); - } - d[l] = d[l] + f; - e[l] = 0.0; - } - - // Sort eigenvalues and corresponding vectors. - - for (int i = 0; i < n-1; i++) { - int k = i; - double p = d[i]; - for (int j = i+1; j < n; j++) { - if (d[j] < p) { // NH find smallest k>i - k = j; - p = d[j]; - } - } - if (k != i) { - d[k] = d[i]; // swap k and i - d[i] = p; - for (int j = 0; j < n; j++) { - p = V[j][i]; - V[j][i] = V[j][k]; - V[j][k] = p; - } } - } } // tql2 /** * exhaustive test of the output of the eigendecomposition * needs O(n^3) operations - * + * * produces error * returns number of detected inaccuracies */ -int UtilsCMAES::checkEigenSystem (int N, double ** C, double * diag, double ** Q) { - - /* compute Q diag Q^T and Q Q^T to check */ - int i, j, k, res = 0; - double cc, dd; - string s; - - for (i=0; i < N; ++i) - for (j=0; j < N; ++j) { - for (cc=0.,dd=0., k=0; k < N; ++k) { - cc += diag[k] * Q[i][k] * Q[j][k]; - dd += Q[i][k] * Q[j][k]; - } - /* check here, is the normalization the right one? */ - if (fabs(cc - C[i>j?i:j][i>j?j:i])/sqrt(C[i][i]*C[j][j]) > 1e-10 - && fabs(cc - C[i>j?i:j][i>j?j:i]) > 1e-9) { /* quite large */ - ostringstream stringStream; - stringStream << " " << i << " " << j << " " << cc << " " << C[i>j?i:j][i>j?j:i] << " " << (cc-C[i>j?i:j][i>j?j:i]); - s = stringStream.str(); - cerr << "UtilsCMAES::checkEigenSystem(): WARNING - imprecise result detected " << s << endl; - ++res; - } - if (fabs(dd - (i==j?1:0)) > 1e-10) { - ostringstream stringStream; - stringStream << i << " " << j << " " << dd << endl; - s = stringStream.str(); - cerr << "UtilsCMAES::checkEigenSystem(): WARNING - imprecise result detected (Q not orthog.) " << s << endl; - ++res; - } - } - return res; - +int UtilsCMAES::checkEigenSystem (int N, double ** C, double * diag, double ** Q) +{ + + /* compute Q diag Q^T and Q Q^T to check */ + int i, j, k, res = 0; + double cc, dd; + std::string s; + + for (i=0; i < N; ++i) + for (j=0; j < N; ++j) + { + for (cc=0.,dd=0., k=0; k < N; ++k) + { + cc += diag[k] * Q[i][k] * Q[j][k]; + dd += Q[i][k] * Q[j][k]; + } + /* check here, is the normalization the right one? */ + if (fabs(cc - C[i>j?i:j][i>j?j:i])/sqrt(C[i][i]*C[j][j]) > 1e-10 + && fabs(cc - C[i>j?i:j][i>j?j:i]) > 1e-9) /* quite large */ + { + ostringstream stringStream; + stringStream << " " << i << " " << j << " " << cc << " " << C[i>j?i:j][i>j?j:i] << " " << (cc-C[i>j?i:j][i>j?j:i]); + s = stringStream.str(); + cerr << "UtilsCMAES::checkEigenSystem(): WARNING - imprecise result detected " << s << std::endl; + ++res; + } + if (fabs(dd - (i==j?1:0)) > 1e-10) + { + ostringstream stringStream; + stringStream << i << " " << j << " " << dd << std::endl; + s = stringStream.str(); + cerr << "UtilsCMAES::checkEigenSystem(): WARNING - imprecise result detected (Q not orthog.) " << s << std::endl; + ++res; + } + } + return res; + } // checkEigenSystem /** * sqrt(a^2 + b^2) without under/overflow. */ -double UtilsCMAES::hypot (double a, double b) { - - double r = 0; - if (fabs(a) > fabs(b)) { - r = b/a; - r = fabs(a)*sqrt(1+r*r); - } else if (b != 0) { - r = a/b; - r = fabs(b)*sqrt(1+r*r); - } - return r; - +double UtilsCMAES::hypot (double a, double b) +{ + + double r = 0; + if (fabs(a) > fabs(b)) + { + r = b/a; + r = fabs(a)*sqrt(1+r*r); + } + else if (b != 0) + { + r = a/b; + r = fabs(b)*sqrt(1+r*r); + } + return r; + } // hypot -void UtilsCMAES::minFastSort(double * x, int * idx, int size) { - - for (int i = 0; i < size; i++) { - for (int j = i + 1; j < size; j++) { - if (x[i] > x[j]) { - double temp = x[i]; - int tempIdx = idx[i]; - x[i] = x[j]; - x[j] = temp; - idx[i] = idx[j]; - idx[j] = tempIdx; - } else if (x[i] == x[j]) { - if (idx[i] > idx[j]) { - double temp = x[i]; - int tempIdx = idx[i]; - x[i] = x[j]; - x[j] = temp; - idx[i] = idx[j]; - idx[j] = tempIdx; +void UtilsCMAES::minFastSort(double * x, int * idx, int size) +{ + + for (int i = 0; i < size; i++) + { + for (int j = i + 1; j < size; j++) + { + if (x[i] > x[j]) + { + double temp = x[i]; + int tempIdx = idx[i]; + x[i] = x[j]; + x[j] = temp; + idx[i] = idx[j]; + idx[j] = tempIdx; + } + else if (x[i] == x[j]) + { + if (idx[i] > idx[j]) + { + double temp = x[i]; + int tempIdx = idx[i]; + x[i] = x[j]; + x[j] = temp; + idx[i] = idx[j]; + idx[j] = tempIdx; + } + } // if } - } // if - } - } // for - + } // for + } // minFastSort diff --git a/src/metaheuristics/singleObjective/cmaes/utils/UtilsCMAES.h b/src/metaheuristics/singleObjective/cmaes/utils/UtilsCMAES.h index 055cf34..66e8854 100644 --- a/src/metaheuristics/singleObjective/cmaes/utils/UtilsCMAES.h +++ b/src/metaheuristics/singleObjective/cmaes/utils/UtilsCMAES.h @@ -2,6 +2,7 @@ // // Author: // Esteban López-Camacho +// Sérgio Vieira // // Copyright (c) 2011 Antonio J. Nebro, Juan J. Durillo // @@ -36,15 +37,16 @@ using namespace std; */ -class UtilsCMAES { - +class UtilsCMAES +{ + public: - static void tred2 (int n, double ** V, double * d, double * e); - static void tql2 (int n, double * d, double * e, double ** V); - static int checkEigenSystem (int N, double ** C, double * diag, double ** Q); - static double hypot (double a, double b); - static void minFastSort (double * x, int * idx, int size); - + static void tred2 (int n, double ** V, double * d, double * e); + static void tql2 (int n, double * d, double * e, double ** V); + static int checkEigenSystem (int N, double ** C, double * diag, double ** Q); + static double hypot (double a, double b); + static void minFastSort (double * x, int * idx, int size); + }; diff --git a/src/metaheuristics/singleObjective/differentialEvolution/CMakeLists.txt b/src/metaheuristics/singleObjective/differentialEvolution/CMakeLists.txt new file mode 100644 index 0000000..294ec59 --- /dev/null +++ b/src/metaheuristics/singleObjective/differentialEvolution/CMakeLists.txt @@ -0,0 +1,3 @@ +file(GLOB SOURCES "*.cpp" "*.h") +ListToString(SOURCES ";" ${SOURCES}) +LIST_APPEND("${SOURCES}") \ No newline at end of file diff --git a/src/metaheuristics/singleObjective/differentialEvolution/DE.cpp b/src/metaheuristics/singleObjective/differentialEvolution/DE.cpp index 09dac50..8c94ecc 100644 --- a/src/metaheuristics/singleObjective/differentialEvolution/DE.cpp +++ b/src/metaheuristics/singleObjective/differentialEvolution/DE.cpp @@ -2,6 +2,7 @@ // // Author: // Esteban López-Camacho +// Sérgio Vieira // // Copyright (c) 2011 Antonio J. Nebro, Juan J. Durillo // @@ -31,7 +32,8 @@ * Constructor * @param problem Problem to solve */ -DE::DE(Problem *problem) : Algorithm(problem) { +DE::DE(Problem *problem) : Algorithm(problem) +{ } // DE @@ -40,111 +42,120 @@ DE::DE(Problem *problem) : Algorithm(problem) { * @return a SolutionSet that is a set of non dominated solutions * as a result of the algorithm execution */ -SolutionSet * DE::execute() { - - int populationSize; - int maxEvaluations; - int evaluations; - - SolutionSet * population; - SolutionSet * offspringPopulation; - - Operator * selectionOperator; - Operator * crossoverOperator; - - Comparator * comparator; - comparator = new ObjectiveComparator(0); // Single objective comparator - - // Differential evolution parameters - int r1; - int r2; - int r3; - int jrand; - - Solution ** parent; - - //Read the parameters - populationSize = *(int *) getInputParameter("populationSize"); - maxEvaluations = *(int *) getInputParameter("maxEvaluations"); - - selectionOperator = operators_["selection"]; - crossoverOperator = operators_["crossover"]; - - //Initialize the variables - population = new SolutionSet(populationSize); - evaluations = 0; - - // Create the initial solutionSet - Solution * newSolution; - for (int i = 0; i < populationSize; i++) { - newSolution = new Solution(problem_); - problem_->evaluate(newSolution); - problem_->evaluateConstraints(newSolution); - evaluations++; - population->add(newSolution); - } //for - - // Generations ... - population->sort(comparator) ; - while (evaluations < maxEvaluations) { - - // Create the offSpring solutionSet - offspringPopulation = new SolutionSet(populationSize); - - //offspringPopulation.add(new Solution(population.get(0))) ; - - for (int i = 0; i < populationSize; i++) { - // Obtain parents. Two parameters are required: the population and the - // index of the current individual - void ** object1 = new void*[2]; - object1[0] = population; - object1[1] = &i; - parent = (Solution **) (selectionOperator->execute(object1)); - delete[] object1; - - Solution * child; - - // Crossover. Two parameters are required: the current individual and the - // array of parents - void ** object2 = new void*[2]; - object2[0] = population->get(i); - object2[1] = parent; - child = (Solution *) (crossoverOperator->execute(object2)); - delete[] object2; - delete[] parent; - - problem_->evaluate(child); - - evaluations++; - - if (comparator->compare(population->get(i), child) < 0) { - offspringPopulation->add(new Solution(population->get(i))); - delete child; - } else { - offspringPopulation->add(child); - } - } // for - - // The offspring population becomes the new current population - for (int i = 0; i < populationSize; i++) { - delete population->get(i); - } - population->clear(); - for (int i = 0; i < populationSize; i++) { - population->add(offspringPopulation->get(i)); - } - offspringPopulation->clear(); - delete offspringPopulation; - population->sort(comparator); - } // while - - delete comparator; - - // Return a population with the best individual - SolutionSet * resultPopulation = new SolutionSet(1); - resultPopulation->add(new Solution(population->get(0))); - delete population; - - return resultPopulation; +SolutionSet * DE::execute() +{ + + int populationSize; + int maxEvaluations; + int evaluations; + + SolutionSet * population; + SolutionSet * offspringPopulation; + + Operator * selectionOperator; + Operator * crossoverOperator; + + Comparator * comparator; + comparator = snew ObjectiveComparator(0); // Single objective comparator + + // Differential evolution parameters + int r1; + int r2; + int r3; + int jrand; + + Solution ** parent; + + //Read the parameters + populationSize = *(int *) getInputParameter("populationSize"); + maxEvaluations = *(int *) getInputParameter("maxEvaluations"); + + selectionOperator = operators_["selection"]; + crossoverOperator = operators_["crossover"]; + + //Initialize the variables + population = snew SolutionSet(populationSize); + evaluations = 0; + + // Create the initial solutionSet + Solution * newSolution; + for (int i = 0; i < populationSize; i++) + { + newSolution = snew Solution(problem_); + problem_->evaluate(newSolution); + problem_->evaluateConstraints(newSolution); + evaluations++; + population->add(newSolution); + } //for + + // Generations ... + population->sort(comparator) ; + while (evaluations < maxEvaluations) + { + + // Create the offSpring solutionSet + offspringPopulation = snew SolutionSet(populationSize); + + //offspringPopulation.add(new Solution(population.get(0))) ; + + for (int i = 0; i < populationSize; i++) + { + // Obtain parents. Two parameters are required: the population and the + // index of the current individual + void ** object1 = snew void*[2]; + object1[0] = population; + object1[1] = &i; + parent = (Solution **) (selectionOperator->execute(object1)); + delete[] object1; + + Solution * child; + + // Crossover. Two parameters are required: the current individual and the + // array of parents + void ** object2 = snew void*[2]; + object2[0] = population->get(i); + object2[1] = parent; + child = (Solution *) (crossoverOperator->execute(object2)); + delete[] object2; + delete[] parent; + + problem_->evaluate(child); + + evaluations++; + + if (comparator->compare(population->get(i), child) < 0) + { + offspringPopulation->add(snew Solution(population->get(i))); + delete child; + } + else + { + offspringPopulation->add(child); + } + } // for + + // The offspring population becomes the new current population + for (int i = 0; i < populationSize; i++) + { + delete population->get(i); + } + population->clear(); + for (int i = 0; i < populationSize; i++) + { + population->add(offspringPopulation->get(i)); + } + offspringPopulation->clear(); + delete offspringPopulation; + population->sort(comparator); + } // while + + delete comparator; + + // Return a population with the best individual + SolutionSet * resultPopulation = snew SolutionSet(1); + resultPopulation->add(snew Solution(population->get(0))); + delete population; + + return resultPopulation; } // execute diff --git a/src/metaheuristics/singleObjective/differentialEvolution/DE.h b/src/metaheuristics/singleObjective/differentialEvolution/DE.h index 0e60ca7..03e0f66 100644 --- a/src/metaheuristics/singleObjective/differentialEvolution/DE.h +++ b/src/metaheuristics/singleObjective/differentialEvolution/DE.h @@ -2,6 +2,7 @@ // // Author: // Esteban López-Camacho +// Sérgio Vieira // // Copyright (c) 2011 Antonio J. Nebro, Juan J. Durillo // @@ -30,11 +31,12 @@ * This class implements a differential evolution algorithm. */ -class DE : public Algorithm { +class DE : public Algorithm +{ public: - DE(Problem * problem); - SolutionSet * execute(); + DE(Problem * problem); + SolutionSet * execute(); }; #endif /* __DE__ */ diff --git a/src/metaheuristics/singleObjective/geneticAlgorithm/CMakeLists.txt b/src/metaheuristics/singleObjective/geneticAlgorithm/CMakeLists.txt new file mode 100644 index 0000000..294ec59 --- /dev/null +++ b/src/metaheuristics/singleObjective/geneticAlgorithm/CMakeLists.txt @@ -0,0 +1,3 @@ +file(GLOB SOURCES "*.cpp" "*.h") +ListToString(SOURCES ";" ${SOURCES}) +LIST_APPEND("${SOURCES}") \ No newline at end of file diff --git a/src/metaheuristics/singleObjective/geneticAlgorithm/gGA.cpp b/src/metaheuristics/singleObjective/geneticAlgorithm/gGA.cpp index d3c5a80..7877bd8 100644 --- a/src/metaheuristics/singleObjective/geneticAlgorithm/gGA.cpp +++ b/src/metaheuristics/singleObjective/geneticAlgorithm/gGA.cpp @@ -29,7 +29,8 @@ * Constructor * @param problem Problem to solve */ -gGA::gGA(Problem *problem) : Algorithm(problem) { +gGA::gGA(Problem *problem) : Algorithm(problem) +{ } // gGA @@ -38,108 +39,114 @@ gGA::gGA(Problem *problem) : Algorithm(problem) { * @return a SolutionSet that is a set of non dominated solutions * as a result of the algorithm execution */ -SolutionSet * gGA::execute() { - - int populationSize; - int maxEvaluations; - int evaluations; - - SolutionSet * population; - SolutionSet * offspringPopulation; - - Operator * mutationOperator; - Operator * crossoverOperator; - Operator * selectionOperator; - - Comparator * comparator = new ObjectiveComparator(0) ; - - //Read the parameters - populationSize = *(int *) getInputParameter("populationSize"); - maxEvaluations = *(int *) getInputParameter("maxEvaluations"); - // TODO: indicators = (QualityIndicator) getInputParameter("indicators"); -// cout << "populationSize = " << populationSize << endl; -// cout << "maxEvaluations = " << maxEvaluations << endl; - - //Initialize the variables - population = new SolutionSet(populationSize); - evaluations = 0; - -// cout << "Poblacion inicializada con maxsize = " << population->getMaxSize() << endl; -// cout << "Poblacion inicializada con size = " << population->size() << endl; -// cout << "Problema: " << problem_->getName() << endl; - - //Read the operators - mutationOperator = operators_["mutation"]; - crossoverOperator = operators_["crossover"]; - selectionOperator = operators_["selection"]; - -// cout << "Comienza la inicializacion de la poblacion con size " << populationSize << endl; - - // Create the initial solutionSet - Solution * newSolution; - for (int i = 0; i < populationSize; i++) { - newSolution = new Solution(problem_); - problem_->evaluate(newSolution); - problem_->evaluateConstraints(newSolution); - evaluations++; - population->add(newSolution); - } //for - -// cout << "gGA: Poblacion inicializada con size = " << population->size() << endl; -// cout << "gGA: Maximo de evaluaciones: " << maxEvaluations << endl; - - // Generations - while (evaluations < maxEvaluations) { - - // Create the offSpring solutionSet - offspringPopulation = new SolutionSet(populationSize); - Solution ** parents = new Solution*[2]; - - for (int i = 0; i < (populationSize / 2); i++) { - if (evaluations < maxEvaluations) { - //obtain parents - parents[0] = (Solution *) (selectionOperator->execute(population)); - parents[1] = (Solution *) (selectionOperator->execute(population)); - Solution ** offSpring = (Solution **) (crossoverOperator->execute(parents)); - mutationOperator->execute(offSpring[0]); - mutationOperator->execute(offSpring[1]); - problem_->evaluate(offSpring[0]); - problem_->evaluateConstraints(offSpring[0]); - problem_->evaluate(offSpring[1]); - problem_->evaluateConstraints(offSpring[1]); - - offspringPopulation->add(offSpring[0]); - offspringPopulation->add(offSpring[1]); - evaluations += 2; - delete[] offSpring; - } // if - } // for - delete[] parents; - - population->sort(comparator) ; - offspringPopulation->sort(comparator) ; - - delete offspringPopulation->get(offspringPopulation->size()-1); - delete offspringPopulation->get(offspringPopulation->size()-2); - offspringPopulation->replace(offspringPopulation->size()-1, new Solution(population->get(0))) ; - offspringPopulation->replace(offspringPopulation->size()-2, new Solution(population->get(1))) ; - - for (int i=0;isize();i++) { - delete population->get(i); +SolutionSet * gGA::execute() +{ + + int populationSize; + int maxEvaluations; + int evaluations; + + SolutionSet * population; + SolutionSet * offspringPopulation; + + Operator * mutationOperator; + Operator * crossoverOperator; + Operator * selectionOperator; + + Comparator * comparator = snew ObjectiveComparator(0) ; + + //Read the parameters + populationSize = *(int *) getInputParameter("populationSize"); + maxEvaluations = *(int *) getInputParameter("maxEvaluations"); + // TODO: indicators = (QualityIndicator) getInputParameter("indicators"); +// std::cout << "populationSize = " << populationSize << std::endl; +// std::cout << "maxEvaluations = " << maxEvaluations << std::endl; + + //Initialize the variables + population = snew SolutionSet(populationSize); + evaluations = 0; + +// std::cout << "Poblacion inicializada con maxsize = " << population->getMaxSize() << std::endl; +// std::cout << "Poblacion inicializada con size = " << population->size() << std::endl; +// std::cout << "Problema: " << problem_->getName() << std::endl; + + //Read the operators + mutationOperator = operators_["mutation"]; + crossoverOperator = operators_["crossover"]; + selectionOperator = operators_["selection"]; + +// std::cout << "Comienza la inicializacion de la poblacion con size " << populationSize << std::endl; + + // Create the initial solutionSet + Solution * newSolution; + for (int i = 0; i < populationSize; i++) + { + newSolution = snew Solution(problem_); + problem_->evaluate(newSolution); + problem_->evaluateConstraints(newSolution); + evaluations++; + population->add(newSolution); + } //for + +// std::cout << "gGA: Poblacion inicializada con size = " << population->size() << std::endl; +// std::cout << "gGA: Maximo de evaluaciones: " << maxEvaluations << std::endl; + + // Generations + while (evaluations < maxEvaluations) + { + + // Create the offSpring solutionSet + offspringPopulation = snew SolutionSet(populationSize); + Solution ** parents = snew Solution*[2]; + + for (int i = 0; i < (populationSize / 2); i++) + { + if (evaluations < maxEvaluations) + { + //obtain parents + parents[0] = (Solution *) (selectionOperator->execute(population)); + parents[1] = (Solution *) (selectionOperator->execute(population)); + Solution ** offSpring = (Solution **) (crossoverOperator->execute(parents)); + mutationOperator->execute(offSpring[0]); + mutationOperator->execute(offSpring[1]); + problem_->evaluate(offSpring[0]); + problem_->evaluateConstraints(offSpring[0]); + problem_->evaluate(offSpring[1]); + problem_->evaluateConstraints(offSpring[1]); + + offspringPopulation->add(offSpring[0]); + offspringPopulation->add(offSpring[1]); + evaluations += 2; + delete[] offSpring; + } // if + } // for + delete[] parents; + + population->sort(comparator) ; + offspringPopulation->sort(comparator) ; + + delete offspringPopulation->get(offspringPopulation->size()-1); + delete offspringPopulation->get(offspringPopulation->size()-2); + offspringPopulation->replace(offspringPopulation->size()-1, snew Solution(population->get(0))) ; + offspringPopulation->replace(offspringPopulation->size()-2, snew Solution(population->get(1))) ; + + for (int i=0; isize(); i++) + { + delete population->get(i); + } + population->clear() ; + + for (int i = 0; i < offspringPopulation->size(); i++) + population->add(offspringPopulation->get(i)) ; + offspringPopulation->clear() ; + delete offspringPopulation; } - population->clear() ; - for (int i = 0; i < offspringPopulation->size(); i++) - population->add(offspringPopulation->get(i)) ; - offspringPopulation->clear() ; - delete offspringPopulation; - } + delete comparator; - delete comparator; + SolutionSet * resultPopulation = snew SolutionSet(1) ; + resultPopulation->add(snew Solution(population->get(0))) ; + delete population; - SolutionSet * resultPopulation = new SolutionSet(1) ; - resultPopulation->add(new Solution(population->get(0))) ; - delete population; - - return resultPopulation ; + return resultPopulation ; } // execute diff --git a/src/metaheuristics/singleObjective/geneticAlgorithm/gGA.h b/src/metaheuristics/singleObjective/geneticAlgorithm/gGA.h index 55d244b..287d0ff 100644 --- a/src/metaheuristics/singleObjective/geneticAlgorithm/gGA.h +++ b/src/metaheuristics/singleObjective/geneticAlgorithm/gGA.h @@ -26,13 +26,14 @@ #include #include -class gGA : public Algorithm { +class gGA : public Algorithm +{ private: - int populationSize_; - int maxEvaluations_; + int populationSize_; + int maxEvaluations_; public: - gGA(Problem * problem); - SolutionSet * execute(); + gGA(Problem * problem); + SolutionSet * execute(); }; #endif /* GGA_H_ */ diff --git a/src/metaheuristics/singleObjective/geneticAlgorithm/ssGA.cpp b/src/metaheuristics/singleObjective/geneticAlgorithm/ssGA.cpp index 6a0b0c3..a6c4986 100644 --- a/src/metaheuristics/singleObjective/geneticAlgorithm/ssGA.cpp +++ b/src/metaheuristics/singleObjective/geneticAlgorithm/ssGA.cpp @@ -2,6 +2,7 @@ // // Author: // Esteban López-Camacho +// Sérgio Vieira // // Copyright (c) 2011 Antonio J. Nebro, Juan J. Durillo // @@ -32,100 +33,105 @@ * Create a new SSGA instance. * @param problem Problem to solve */ -ssGA::ssGA(Problem *problem) : Algorithm(problem) { +ssGA::ssGA(Problem *problem) : Algorithm(problem) +{ } // ssGA /* * Execute the SSGA algorithm */ -SolutionSet * ssGA::execute() { +SolutionSet * ssGA::execute() +{ - int populationSize; - int maxEvaluations; - int evaluations; + int populationSize; + int maxEvaluations; + int evaluations; - SolutionSet * population; + SolutionSet * population; - Operator * mutationOperator; - Operator * crossoverOperator; - Operator * selectionOperator; + Operator * mutationOperator; + Operator * crossoverOperator; + Operator * selectionOperator; - Comparator * comparator = new ObjectiveComparator(0); // Single objective comparator + Comparator * comparator = new ObjectiveComparator(0); // Single objective comparator - Operator * findWorstSolution; - map parameters; // Operator parameters - parameters["comparator"] = comparator; + Operator * findWorstSolution; + MapOfStringFunct parameters; // Operator parameters + parameters["comparator"] = comparator; - findWorstSolution = new WorstSolutionSelection(parameters) ; + findWorstSolution = new WorstSolutionSelection(parameters) ; - //Read the parameters - populationSize = *(int *) getInputParameter("populationSize"); - maxEvaluations = *(int *) getInputParameter("maxEvaluations"); + //Read the parameters + populationSize = *(int *) getInputParameter("populationSize"); + maxEvaluations = *(int *) getInputParameter("maxEvaluations"); - //Initialize the variables - population = new SolutionSet(populationSize); - evaluations = 0; + //Initialize the variables + population = new SolutionSet(populationSize); + evaluations = 0; - //Read the operators - mutationOperator = operators_["mutation"]; - crossoverOperator = operators_["crossover"]; - selectionOperator = operators_["selection"]; + //Read the operators + mutationOperator = operators_["mutation"]; + crossoverOperator = operators_["crossover"]; + selectionOperator = operators_["selection"]; - // Create the initial population - Solution * newIndividual; - for (int i = 0; i < populationSize; i++) { - newIndividual = new Solution(problem_); - problem_->evaluate(newIndividual); - evaluations++; - population->add(newIndividual); - } // for + // Create the initial population + Solution * newIndividual; + for (int i = 0; i < populationSize; i++) + { + newIndividual = new Solution(problem_); + problem_->evaluate(newIndividual); + evaluations++; + population->add(newIndividual); + } // for - // main loop - while (evaluations < maxEvaluations) { - Solution ** parents = new Solution*[2]; + // main loop + while (evaluations < maxEvaluations) + { + Solution ** parents = new Solution*[2]; - // Selection - parents[0] = (Solution*)selectionOperator->execute(population); - parents[1] = (Solution*)selectionOperator->execute(population); + // Selection + parents[0] = (Solution*)selectionOperator->execute(population); + parents[1] = (Solution*)selectionOperator->execute(population); - // Crossover - Solution ** offspring = (Solution **) crossoverOperator->execute(parents); + // Crossover + Solution ** offspring = (Solution **) crossoverOperator->execute(parents); - // Mutation - mutationOperator->execute(offspring[0]); + // Mutation + mutationOperator->execute(offspring[0]); - // Evaluation of the new individual - problem_->evaluate(offspring[0]); + // Evaluation of the new individual + problem_->evaluate(offspring[0]); - evaluations ++; + evaluations ++; - // Replacement: replace the last individual is the new one is better - int * worstIndividualPtr = (int *) findWorstSolution->execute(population); - int worstIndividual = *worstIndividualPtr; - delete worstIndividualPtr; + // Replacement: replace the last individual is the new one is better + int * worstIndividualPtr = (int *) findWorstSolution->execute(population); + int worstIndividual = *worstIndividualPtr; + delete worstIndividualPtr; - if (comparator->compare(population->get(worstIndividual), offspring[0]) > 0) { - delete population->get(worstIndividual); - population->remove(worstIndividual); - population->add(new Solution(offspring[0])); - } // if + if (comparator->compare(population->get(worstIndividual), offspring[0]) > 0) + { + delete population->get(worstIndividual); + population->remove(worstIndividual); + population->add(new Solution(offspring[0])); + } // if - delete offspring[0]; - delete offspring[1]; - delete [] offspring; - delete [] parents; + delete offspring[0]; + delete offspring[1]; + delete [] offspring; + delete [] parents; - } // while + } // while - // Return a population with the best individual + // Return a population with the best individual - SolutionSet * resultPopulation = new SolutionSet(1); - resultPopulation->add(new Solution(population->best(comparator))); + SolutionSet * resultPopulation = new SolutionSet(1); + resultPopulation->add(new Solution(population->best(comparator))); - delete population; - delete comparator; - delete findWorstSolution; + delete population; + delete comparator; + delete findWorstSolution; - return resultPopulation; + return resultPopulation; } // execute diff --git a/src/metaheuristics/singleObjective/geneticAlgorithm/ssGA.h b/src/metaheuristics/singleObjective/geneticAlgorithm/ssGA.h index a374f86..460ac98 100644 --- a/src/metaheuristics/singleObjective/geneticAlgorithm/ssGA.h +++ b/src/metaheuristics/singleObjective/geneticAlgorithm/ssGA.h @@ -2,6 +2,7 @@ // // Author: // Esteban López-Camacho +// Sérgio Vieira // // Copyright (c) 2011 Antonio J. Nebro, Juan J. Durillo // @@ -30,11 +31,12 @@ /** * Class implementing a steady-state genetic algorithm */ -class ssGA : public Algorithm { +class ssGA : public Algorithm +{ public: - ssGA(Problem * problem); - SolutionSet * execute(); + ssGA(Problem * problem); + SolutionSet * execute(); }; diff --git a/src/metaheuristics/singleObjective/particleSwarmOptimization/CMakeLists.txt b/src/metaheuristics/singleObjective/particleSwarmOptimization/CMakeLists.txt new file mode 100644 index 0000000..294ec59 --- /dev/null +++ b/src/metaheuristics/singleObjective/particleSwarmOptimization/CMakeLists.txt @@ -0,0 +1,3 @@ +file(GLOB SOURCES "*.cpp" "*.h") +ListToString(SOURCES ";" ${SOURCES}) +LIST_APPEND("${SOURCES}") \ No newline at end of file diff --git a/src/metaheuristics/singleObjective/particleSwarmOptimization/PSO.cpp b/src/metaheuristics/singleObjective/particleSwarmOptimization/PSO.cpp index 9bbd282..15940f2 100644 --- a/src/metaheuristics/singleObjective/particleSwarmOptimization/PSO.cpp +++ b/src/metaheuristics/singleObjective/particleSwarmOptimization/PSO.cpp @@ -2,6 +2,7 @@ // // Author: // Esteban López-Camacho +// Sérgio Vieira // // Copyright (c) 2011 Antonio J. Nebro, Juan J. Durillo // @@ -31,28 +32,29 @@ * Constructor * @param problem Problem to solve */ -PSO::PSO(Problem *problem) : Algorithm(problem) { - - r1Max_ = 1.0; - r1Min_ = 0.0; - r2Max_ = 1.0; - r2Min_ = 0.0; - C1Max_ = 1.5; - C1Min_ = 1.5; - C2Max_ = 1.5; - C2Min_ = 1.5; - WMax_ = 0.9; - WMin_ = 0.9; - ChVel1_ = 1.0; - ChVel2_ = 1.0; - - comparator_ = new ObjectiveComparator(0); // Single objective comparator - map parameters; // Operator parameters - - parameters["comparator"] = comparator_; - findBestSolution_ = new BestSolutionSelection(parameters); - - evaluations_ = 0; +PSO::PSO(Problem *problem) : Algorithm(problem) +{ + + r1Max_ = 1.0; + r1Min_ = 0.0; + r2Max_ = 1.0; + r2Min_ = 0.0; + C1Max_ = 1.5; + C1Min_ = 1.5; + C2Max_ = 1.5; + C2Min_ = 1.5; + WMax_ = 0.9; + WMin_ = 0.9; + ChVel1_ = 1.0; + ChVel2_ = 1.0; + + comparator_ = new ObjectiveComparator(0); // Single objective comparator + MapOfStringFunct parameters; // Operator parameters + + parameters["comparator"] = comparator_; + findBestSolution_ = new BestSolutionSelection(parameters); + + evaluations_ = 0; } // PSO @@ -60,153 +62,167 @@ PSO::PSO(Problem *problem) : Algorithm(problem) { /** * Initialize all parameter of the algorithm */ -void PSO::initParams() { - particlesSize_ = *(int *) getInputParameter("swarmSize"); - maxIterations_ = *(int *) getInputParameter("maxIterations"); +void PSO::initParams() +{ + particlesSize_ = *(int *) getInputParameter("swarmSize"); + maxIterations_ = *(int *) getInputParameter("maxIterations"); - polynomialMutation_ = operators_["mutation"]; + polynomialMutation_ = operators_["mutation"]; - iteration_ = 0; + iteration_ = 0; - success_ = false; + success_ = false; - particles_ = new SolutionSet(particlesSize_); - localBest_ = new Solution*[particlesSize_]; + particles_ = new SolutionSet(particlesSize_); + localBest_ = new Solution*[particlesSize_]; - // Create the speed_ vector - speed_ = new double*[particlesSize_]; + // Create the speed_ vector + speed_ = snew double*[particlesSize_]; - deltaMax_ = new double[problem_->getNumberOfVariables()]; - deltaMin_ = new double[problem_->getNumberOfVariables()]; - for (int i = 0; i < problem_->getNumberOfVariables(); i++) { - deltaMax_[i] = (problem_->getUpperLimit(i) - - problem_->getLowerLimit(i)) / 2.0; - deltaMin_[i] = -deltaMax_[i]; - } // for + deltaMax_ = snew double[problem_->getNumberOfVariables()]; + deltaMin_ = snew double[problem_->getNumberOfVariables()]; + for (int i = 0; i < problem_->getNumberOfVariables(); i++) + { + deltaMax_[i] = (problem_->getUpperLimit(i) - + problem_->getLowerLimit(i)) / 2.0; + deltaMin_[i] = -deltaMax_[i]; + } // for } // initParams /** * Initialize all parameter of the algorithm */ -void PSO::deleteParams() { - - for (int i = 0; i < particlesSize_; i++) { - delete [] speed_[i]; - } - delete [] speed_; - delete [] deltaMax_; - delete [] deltaMin_; - for (int i = 0; i < particles_->size(); i++) { - delete localBest_[i]; - } - delete [] localBest_; - delete globalBest_; - delete particles_; - delete findBestSolution_; - delete comparator_; +void PSO::deleteParams() +{ + + for (int i = 0; i < particlesSize_; i++) + { + delete [] speed_[i]; + } + delete [] speed_; + delete [] deltaMax_; + delete [] deltaMin_; + for (int i = 0; i < particles_->size(); i++) + { + delete localBest_[i]; + } + delete [] localBest_; + delete globalBest_; + delete particles_; + delete findBestSolution_; + delete comparator_; } // deleteParams // Adaptive inertia -double PSO::inertiaWeight(int iter, int miter, double wmax, double wmin) { - //return wmax; - return wmax - (((wmax-wmin)*(double)iter)/(double)miter); +double PSO::inertiaWeight(int iter, int miter, double wmax, double wmin) +{ + //return wmax; + return wmax - (((wmax-wmin)*(double)iter)/(double)miter); } // inertiaWeight // constriction coefficient (M. Clerc) -double PSO::constrictionCoefficient(double c1, double c2) { - double rho = c1 + c2; - //rho = 1.0 ; - if (rho <= 4) { - return 1.0; - } else { - return 2 / fabs((2 - rho - sqrt(pow(rho, 2.0) - 4.0 * rho))); - } +double PSO::constrictionCoefficient(double c1, double c2) +{ + double rho = c1 + c2; + //rho = 1.0 ; + if (rho <= 4) + { + return 1.0; + } + else + { + return 2 / fabs((2 - rho - sqrt(pow(rho, 2.0) - 4.0 * rho))); + } } // constrictionCoefficient // velocity bounds double PSO::velocityConstriction(double v, double * deltaMax, - double * deltaMin, int variableIndex, - int particleIndex) { + double * deltaMin, int variableIndex, + int particleIndex) +{ - return v; - /* - double result; + return v; + /* + double result; - double dmax = deltaMax[variableIndex]; - double dmin = deltaMin[variableIndex]; + double dmax = deltaMax[variableIndex]; + double dmin = deltaMin[variableIndex]; - result = v; + result = v; - if (v > dmax) { - result = dmax; - } + if (v > dmax) { + result = dmax; + } - if (v < dmin) { - result = dmin; - } + if (v < dmin) { + result = dmin; + } - return result; - */ + return result; + */ } // velocityConstriction /** * Update the speed of each particle */ -void PSO::computeSpeed(int iter, int miter) { - double r1, r2; - //double W ; - double C1, C2; - double wmax, wmin, deltaMax, deltaMin; - XReal * bestGlobal; - - bestGlobal = new XReal(globalBest_) ; - - for (int i = 0; i < particlesSize_; i++) { - XReal * particle = new XReal(particles_->get(i)) ; - XReal * bestParticle = new XReal(localBest_[i]) ; - - //int bestIndividual = findBestSolution_->execute(particles_) ; - - r1 = PseudoRandom::randDouble(r1Min_, r1Max_); - r2 = PseudoRandom::randDouble(r2Min_, r2Max_); - //C1 = PseudoRandom::randDouble(C1Min_, C1Max_); - //C2 = PseudoRandom::randDouble(C2Min_, C2Max_); - C1 = 2.05; - C2 = 2.05; - //W = PseudoRandom.randDouble(WMin_, WMax_); - - wmax = WMax_; - wmin = WMin_; - - for (int var = 0; var < particle->size(); var++) { - //Computing the velocity of this particle - speed_[i][var] = constrictionCoefficient(C1, C2) * - (speed_[i][var] + - C1 * r1 * (bestParticle->getValue(var) - particle->getValue(var)) + - C2 * r2 * (bestGlobal->getValue(var) - particle->getValue(var))); - } +void PSO::computeSpeed(int iter, int miter) +{ + double r1, r2; + //double W ; + double C1, C2; + double wmax, wmin, deltaMax, deltaMin; + XReal * bestGlobal; + + bestGlobal = new XReal(globalBest_) ; + + for (int i = 0; i < particlesSize_; i++) + { + XReal * particle = new XReal(particles_->get(i)) ; + XReal * bestParticle = new XReal(localBest_[i]) ; + + //int bestIndividual = findBestSolution_->execute(particles_) ; + + r1 = PseudoRandom::randDouble(r1Min_, r1Max_); + r2 = PseudoRandom::randDouble(r2Min_, r2Max_); + //C1 = PseudoRandom::randDouble(C1Min_, C1Max_); + //C2 = PseudoRandom::randDouble(C2Min_, C2Max_); + C1 = 2.05; + C2 = 2.05; + //W = PseudoRandom.randDouble(WMin_, WMax_); + + wmax = WMax_; + wmin = WMin_; + + for (int var = 0; var < particle->size(); var++) + { + //Computing the velocity of this particle + speed_[i][var] = constrictionCoefficient(C1, C2) * + (speed_[i][var] + + C1 * r1 * (bestParticle->getValue(var) - particle->getValue(var)) + + C2 * r2 * (bestGlobal->getValue(var) - particle->getValue(var))); + } + + /* + for (int var = 0; var < particle->size(); var++) { + //Computing the velocity of this particle + speed_[i][var] = inertiaWeight(iter, miter, wmax, wmin) * speed_[i][var] + + C1 * r1 * (bestParticle->getValue(var) - particle->getValue(var)) + + C2 * r2 * (bestGlobal->getValue(var) - particle->getValue(var)) ; + } + */ + + delete particle; + delete bestParticle; - /* - for (int var = 0; var < particle->size(); var++) { - //Computing the velocity of this particle - speed_[i][var] = inertiaWeight(iter, miter, wmax, wmin) * speed_[i][var] + - C1 * r1 * (bestParticle->getValue(var) - particle->getValue(var)) + - C2 * r2 * (bestGlobal->getValue(var) - particle->getValue(var)) ; } - */ - - delete particle; - delete bestParticle; - } - - delete bestGlobal; + delete bestGlobal; } // computeSpeed @@ -214,43 +230,50 @@ void PSO::computeSpeed(int iter, int miter) { /** * Update the position of each particle */ -void PSO::computeNewPositions() { - for (int i = 0; i < particlesSize_; i++) { - //Variable ** particle = particles_->get(i)->getDecisionVariables(); - XReal * particle = new XReal(particles_->get(i)) ; - //particle->move(speed_[i]); - for (int var = 0; var < particle->size(); var++) { - particle->setValue(var, particle->getValue(var) + speed_[i][var]) ; - - if (particle->getValue(var) < problem_->getLowerLimit(var)) { - particle->setValue(var, problem_->getLowerLimit(var)); - speed_[i][var] = speed_[i][var] * ChVel1_; // - } - if (particle->getValue(var) > problem_->getUpperLimit(var)) { - particle->setValue(var, problem_->getUpperLimit(var)); - speed_[i][var] = speed_[i][var] * ChVel2_; // - } - +void PSO::computeNewPositions() +{ + for (int i = 0; i < particlesSize_; i++) + { + //Variable ** particle = particles_->get(i)->getDecisionVariables(); + XReal * particle = new XReal(particles_->get(i)) ; + //particle->move(speed_[i]); + for (int var = 0; var < particle->size(); var++) + { + particle->setValue(var, particle->getValue(var) + speed_[i][var]) ; + + if (particle->getValue(var) < problem_->getLowerLimit(var)) + { + particle->setValue(var, problem_->getLowerLimit(var)); + speed_[i][var] = speed_[i][var] * ChVel1_; // + } + if (particle->getValue(var) > problem_->getUpperLimit(var)) + { + particle->setValue(var, problem_->getUpperLimit(var)); + speed_[i][var] = speed_[i][var] * ChVel2_; // + } + + } + delete particle; } - delete particle; - } } // computeNewPositions /** * Apply a mutation operator to some particles in the swarm */ -void PSO::mopsoMutation(int actualIteration, int totalIterations) { - for (int i = 0; i < particles_->size(); i++) { - if ( (i % 6) == 0) - polynomialMutation_->execute(particles_->get(i)); - //if (i % 3 == 0) { //particles_ mutated with a non-uniform mutation %3 - // nonUniformMutation_.execute(particles_.get(i)); - //} else if (i % 3 == 1) { //particles_ mutated with a uniform mutation operator - // uniformMutation_.execute(particles_.get(i)); - //} else //particles_ without mutation - //; - } +void PSO::mopsoMutation(int actualIteration, int totalIterations) +{ + for (int i = 0; i < particles_->size(); i++) + { + if ( (i % 6) == 0) + polynomialMutation_->execute(particles_->get(i)); + //if (i % 3 == 0) { //particles_ mutated with a non-uniform mutation %3 + // nonUniformMutation_.execute(particles_.get(i)); + //} else if (i % 3 == 1) { //particles_ mutated with a uniform mutation operator + // uniformMutation_.execute(particles_.get(i)); + //} else //particles_ without mutation + //; + } } // mopsoMutation @@ -259,90 +282,102 @@ void PSO::mopsoMutation(int actualIteration, int totalIterations) { * @return a SolutionSet that is a set of non dominated solutions * as a result of the algorithm execution */ -SolutionSet * PSO::execute() { - - initParams(); - - success_ = false; - globalBest_ = NULL; - - //->Step 1 (and 3) Create the initial population and evaluate - for (int i = 0; i < particlesSize_; i++) { - Solution * particle = new Solution(problem_); - problem_->evaluate(particle); - evaluations_ ++; - particles_->add(particle); - if ((globalBest_ == NULL) || (particle->getObjective(0) < globalBest_->getObjective(0))) { - if (globalBest_!= NULL) { - delete globalBest_; - } - globalBest_ = new Solution(particle); +SolutionSet * PSO::execute() +{ + + initParams(); + + success_ = false; + globalBest_ = nullptr; + + //->Step 1 (and 3) Create the initial population and evaluate + for (int i = 0; i < particlesSize_; i++) + { + Solution * particle = new Solution(problem_); + problem_->evaluate(particle); + evaluations_ ++; + particles_->add(particle); + if ((globalBest_ == nullptr) || (particle->getObjective(0) < globalBest_->getObjective(0))) + { + if (globalBest_!= nullptr) + { + delete globalBest_; + } + globalBest_ = new Solution(particle); + } } - } - //-> Step2. Initialize the speed_ of each particle to 0 - for (int i = 0; i < particlesSize_; i++) { - speed_[i] = new double[problem_->getNumberOfVariables()]; - for (int j = 0; j < problem_->getNumberOfVariables(); j++) { - speed_[i][j] = 0.0; - } - } - - //-> Step 6. Initialize the memory of each particle - for (int i = 0; i < particles_->size(); i++) { - Solution * particle = new Solution(particles_->get(i)); - localBest_[i] = particle; - } - - //-> Step 7. Iterations .. - while (iteration_ < maxIterations_) { - int * bestIndividualPtr = (int*)findBestSolution_->execute(particles_); - int bestIndividual = *bestIndividualPtr; - delete bestIndividualPtr; - computeSpeed(iteration_, maxIterations_); - - //Compute the new positions for the particles_ - computeNewPositions(); - - //Mutate the particles_ - //mopsoMutation(iteration_, maxIterations_); - - //Evaluate the new particles_ in new positions - for (int i = 0; i < particles_->size(); i++) { - Solution * particle = particles_->get(i); - problem_->evaluate(particle); - evaluations_ ++; + //-> Step2. Initialize the speed_ of each particle to 0 + for (int i = 0; i < particlesSize_; i++) + { + speed_[i] = snew double[problem_->getNumberOfVariables()]; + for (int j = 0; j < problem_->getNumberOfVariables(); j++) + { + speed_[i][j] = 0.0; + } } - //Actualize the memory of this particle - for (int i = 0; i < particles_->size(); i++) { - //int flag = comparator_.compare(particles_.get(i), localBest_[i]); - //if (flag < 0) { // the new particle is best_ than the older remember - if ((particles_->get(i)->getObjective(0) < localBest_[i]->getObjective(0))) { - Solution * particle = new Solution(particles_->get(i)); - delete localBest_[i]; - localBest_[i] = particle; - } // if - if ((particles_->get(i)->getObjective(0) < globalBest_->getObjective(0))) { - Solution * particle = new Solution(particles_->get(i)); - delete globalBest_; - globalBest_ = particle; - } // if + //-> Step 6. Initialize the memory of each particle + for (int i = 0; i < particles_->size(); i++) + { + Solution * particle = new Solution(particles_->get(i)); + localBest_[i] = particle; + } + //-> Step 7. Iterations .. + while (iteration_ < maxIterations_) + { + int * bestIndividualPtr = (int*)findBestSolution_->execute(particles_); + int bestIndividual = *bestIndividualPtr; + delete bestIndividualPtr; + computeSpeed(iteration_, maxIterations_); + + //Compute the new positions for the particles_ + computeNewPositions(); + + //Mutate the particles_ + //mopsoMutation(iteration_, maxIterations_); + + //Evaluate the new particles_ in new positions + for (int i = 0; i < particles_->size(); i++) + { + Solution * particle = particles_->get(i); + problem_->evaluate(particle); + evaluations_ ++; + } + + //Actualize the memory of this particle + for (int i = 0; i < particles_->size(); i++) + { + //int flag = comparator_.compare(particles_.get(i), localBest_[i]); + //if (flag < 0) { // the new particle is best_ than the older remember + if ((particles_->get(i)->getObjective(0) < localBest_[i]->getObjective(0))) + { + Solution * particle = new Solution(particles_->get(i)); + delete localBest_[i]; + localBest_[i] = particle; + } // if + if ((particles_->get(i)->getObjective(0) < globalBest_->getObjective(0))) + { + Solution * particle = new Solution(particles_->get(i)); + delete globalBest_; + globalBest_ = particle; + } // if + + } + iteration_++; } - iteration_++; - } - // Return a population with the best individual - SolutionSet * resultPopulation = new SolutionSet(1); - int * bestIndexPtr = (int *)findBestSolution_->execute(particles_); - int bestIndex = *bestIndexPtr; - delete bestIndexPtr; - Solution * s = particles_->get(bestIndex); - resultPopulation->add(new Solution(s)); + // Return a population with the best individual + SolutionSet * resultPopulation = new SolutionSet(1); + int * bestIndexPtr = (int *)findBestSolution_->execute(particles_); + int bestIndex = *bestIndexPtr; + delete bestIndexPtr; + Solution * s = particles_->get(bestIndex); + resultPopulation->add(new Solution(s)); - // Free memory - deleteParams(); + // Free memory + deleteParams(); - return resultPopulation; + return resultPopulation; } // execute diff --git a/src/metaheuristics/singleObjective/particleSwarmOptimization/PSO.h b/src/metaheuristics/singleObjective/particleSwarmOptimization/PSO.h index 6ebb57b..78d4864 100644 --- a/src/metaheuristics/singleObjective/particleSwarmOptimization/PSO.h +++ b/src/metaheuristics/singleObjective/particleSwarmOptimization/PSO.h @@ -2,6 +2,7 @@ // // Author: // Esteban López-Camacho +// Sérgio Vieira // // Copyright (c) 2011 Antonio J. Nebro, Juan J. Durillo // @@ -36,86 +37,87 @@ * Class implementing a single-objective PSO algorithm */ -class PSO : public Algorithm { +class PSO : public Algorithm +{ private: - /** - * Stores the number of particles_ used - */ - int particlesSize_; - /** - * Stores the maximum number of iteration_ - */ - int maxIterations_; - /** - * Stores the current number of iteration_ - */ - int iteration_; - /** - * Stores the particles - */ - SolutionSet * particles_; - /** - * Stores the local best solutions found so far for each particles - */ - Solution ** localBest_; - /** - * Stores the global best solution found - */ - Solution * globalBest_; - /** - * Stores the speed_ of each particle - */ - double ** speed_; - /** - * Stores a operator for non uniform mutations - */ - Operator * polynomialMutation_; + /** + * Stores the number of particles_ used + */ + int particlesSize_; + /** + * Stores the maximum number of iteration_ + */ + int maxIterations_; + /** + * Stores the current number of iteration_ + */ + int iteration_; + /** + * Stores the particles + */ + SolutionSet * particles_; + /** + * Stores the local best solutions found so far for each particles + */ + Solution ** localBest_; + /** + * Stores the global best solution found + */ + Solution * globalBest_; + /** + * Stores the speed_ of each particle + */ + double ** speed_; + /** + * Stores a operator for non uniform mutations + */ + Operator * polynomialMutation_; - int evaluations_ ; + int evaluations_ ; - /** - * Comparator object - */ - Comparator * comparator_ ; + /** + * Comparator object + */ + Comparator * comparator_ ; - Operator * findBestSolution_ ; + Operator * findBestSolution_ ; - double r1Max_; - double r1Min_; - double r2Max_; - double r2Min_; - double C1Max_; - double C1Min_; - double C2Max_; - double C2Min_; - double WMax_; - double WMin_; - double ChVel1_; - double ChVel2_; + double r1Max_; + double r1Min_; + double r2Max_; + double r2Min_; + double C1Max_; + double C1Min_; + double C2Max_; + double C2Min_; + double WMax_; + double WMin_; + double ChVel1_; + double ChVel2_; - SolutionSet * trueFront_; - double * deltaMax_; - double * deltaMin_; - bool success_; + SolutionSet * trueFront_; + double * deltaMax_; + double * deltaMin_; + bool success_; - double inertiaWeight(int iter, int miter, double wmax, - double wmin); - double constrictionCoefficient(double c1, double c2); - double velocityConstriction(double v, double * deltaMax, - double * deltaMin, - int variableIndex, - int particleIndex); - void computeSpeed(int iter, int miter); - void computeNewPositions(); - void mopsoMutation(int actualIteration, int totalIterations); - void initParams(); - void deleteParams(); + double inertiaWeight(int iter, int miter, double wmax, + double wmin); + double constrictionCoefficient(double c1, double c2); + double velocityConstriction(double v, double * deltaMax, + double * deltaMin, + int variableIndex, + int particleIndex); + void computeSpeed(int iter, int miter); + void computeNewPositions(); + void mopsoMutation(int actualIteration, int totalIterations); + void initParams(); + void deleteParams(); public: - PSO(Problem * problem); - SolutionSet * execute(); + PSO(Problem * problem); + SolutionSet * execute(); }; diff --git a/src/metaheuristics/singleObjective/particleSwarmOptimization/StandardPSO2007.cpp b/src/metaheuristics/singleObjective/particleSwarmOptimization/StandardPSO2007.cpp index 66d60b0..f0dc6ff 100644 --- a/src/metaheuristics/singleObjective/particleSwarmOptimization/StandardPSO2007.cpp +++ b/src/metaheuristics/singleObjective/particleSwarmOptimization/StandardPSO2007.cpp @@ -2,6 +2,7 @@ // // Author: // Esteban López-Camacho +// Sérgio Vieira // Antonio J. Nebro // // Copyright (c) 2014 Antonio J. Nebro @@ -32,142 +33,162 @@ * Constructor * @param problem Problem to solve */ -StandardPSO2007::StandardPSO2007(Problem * problem) : Algorithm(problem) { +StandardPSO2007::StandardPSO2007(Problem * problem) : Algorithm(problem) +{ - W_ = 1.0/(2.0 * log(2)) ; //0.721; - C_ = 1.0/2.0 + log(2) ; //1.193; + W_ = 1.0/(2.0 * log(2)) ; //0.721; + C_ = 1.0/2.0 + log(2) ; //1.193; - comparator_ = new ObjectiveComparator(0) ; // Single objective comparator - map parameters ; // Operator parameters + comparator_ = new ObjectiveComparator(0) ; // Single objective comparator + MapOfStringFunct parameters ; // Operator parameters - parameters["comparator"] = comparator_; - findBestSolution_ = new BestSolutionSelection(parameters) ; + parameters["comparator"] = comparator_; + findBestSolution_ = new BestSolutionSelection(parameters) ; - evaluations_ = 0 ; + evaluations_ = 0 ; } // StandardPSO2007 /** * Destructor */ -StandardPSO2007::~StandardPSO2007() { - delete comparator_; - delete findBestSolution_; +StandardPSO2007::~StandardPSO2007() +{ + delete comparator_; + delete findBestSolution_; } // ~StandardPSO2007 -double StandardPSO2007::getW() { - return W_; +double StandardPSO2007::getW() +{ + return W_; } // getW -double StandardPSO2007::getC() { - return C_; +double StandardPSO2007::getC() +{ + return C_; } // getC /** * Initialize all parameters of the algorithm */ -void StandardPSO2007::initParams() { - swarmSize_ = *(int *) getInputParameter("swarmSize"); - maxIterations_ = *(int *) getInputParameter("maxIterations"); - numberOfParticlesToInform_ = *(int *) getInputParameter("numberOfParticlesToInform"); +void StandardPSO2007::initParams() +{ + swarmSize_ = *(int *) getInputParameter("swarmSize"); + maxIterations_ = *(int *) getInputParameter("maxIterations"); + numberOfParticlesToInform_ = *(int *) getInputParameter("numberOfParticlesToInform"); - cout << "Swarm size: " << swarmSize_ << endl; + std::cout << "Swarm size: " << swarmSize_ << std::endl; - iteration_ = 0; + iteration_ = 0; - swarm_ = new SolutionSet(swarmSize_); - localBest_ = new Solution*[swarmSize_]; - neighborhoodBest_ = new Solution*[swarmSize_]; + swarm_ = new SolutionSet(swarmSize_); + localBest_ = new Solution*[swarmSize_]; + neighborhoodBest_ = new Solution*[swarmSize_]; - // Create the speed_ vector - speed_ = new double*[swarmSize_]; + // Create the speed_ vector + speed_ = snew double*[swarmSize_]; } // initParams /** * Delete all parameters of the algorithm */ -void StandardPSO2007::deleteParams() { - delete swarm_; - delete [] localBest_; - delete [] neighborhoodBest_; - delete [] speed_; +void StandardPSO2007::deleteParams() +{ + delete swarm_; + delete [] localBest_; + delete [] neighborhoodBest_; + delete [] speed_; } // deleteParams -Solution * StandardPSO2007::getNeighborBest(int i) { - Solution * bestLocalBestSolution = NULL ; +Solution * StandardPSO2007::getNeighborBest(int i) +{ + Solution * bestLocalBestSolution = nullptr ; - for (int index : neighborhood_->getNeighbors(i)) { - if ((bestLocalBestSolution == NULL) || (bestLocalBestSolution->getObjective(0) > localBest_[index]->getObjective(0))) { - bestLocalBestSolution = localBest_[index] ; + for (int index : neighborhood_->getNeighbors(i)) + { + if ((bestLocalBestSolution == nullptr) || (bestLocalBestSolution->getObjective(0) > localBest_[index]->getObjective(0))) + { + bestLocalBestSolution = localBest_[index] ; + } } - } - return bestLocalBestSolution ; + return bestLocalBestSolution ; } // getNeighborBest -void StandardPSO2007::computeSpeed() { - double r1, r2 ; +void StandardPSO2007::computeSpeed() +{ + double r1, r2 ; + + for (int i = 0; i < swarmSize_; i++) + { + + XReal * particle = new XReal(swarm_->get(i)) ; + XReal * localBest = new XReal(localBest_[i]) ; + XReal * neighborhoodBest = new XReal(neighborhoodBest_[i]) ; + //XReal * neighborhoodBest = new XReal(globalBest_) ; + + r1 = PseudoRandom::randDouble(0, C_); + r2 = PseudoRandom::randDouble(0, C_); + + //W_ = 0.9 ; + if (localBest_[i] != neighborhoodBest_[i]) + { + for (int var = 0; var < particle->getNumberOfDecisionVariables(); var++) + { + speed_[i][var] = W_ * speed_[i][var] + + r1 * (localBest->getValue(var) - particle->getValue(var)) + + r2 * (neighborhoodBest->getValue(var) - particle->getValue(var)); + } + } + else + { + for (int var = 0; var < particle->getNumberOfDecisionVariables(); var++) + { + speed_[i][var] = W_* speed_[i][var] + + r1 * (localBest->getValue(var) - particle->getValue(var)) ; + } + } + + delete particle; + delete localBest; + delete neighborhoodBest; - for (int i = 0; i < swarmSize_; i++) { - - XReal * particle = new XReal(swarm_->get(i)) ; - XReal * localBest = new XReal(localBest_[i]) ; - XReal * neighborhoodBest = new XReal(neighborhoodBest_[i]) ; - //XReal * neighborhoodBest = new XReal(globalBest_) ; - - r1 = PseudoRandom::randDouble(0, C_); - r2 = PseudoRandom::randDouble(0, C_); - - //W_ = 0.9 ; - if (localBest_[i] != neighborhoodBest_[i]) { - for (int var = 0; var < particle->getNumberOfDecisionVariables(); var++) { - speed_[i][var] = W_ * speed_[i][var] + - r1 * (localBest->getValue(var) - particle->getValue(var)) + - r2 * (neighborhoodBest->getValue(var) - particle->getValue(var)); - } - } - else { - for (int var = 0; var < particle->getNumberOfDecisionVariables(); var++) { - speed_[i][var] = W_* speed_[i][var] + - r1 * (localBest->getValue(var) - particle->getValue(var)) ; - } } - - delete particle; - delete localBest; - delete neighborhoodBest; - - } } // computeSpeed /** * Update the position of each particle */ -void StandardPSO2007::computeNewPositions() { - for (int i = 0; i < swarmSize_; i++) { - //Variable[] particle = swarm_.get(i).getDecisionVariables(); - XReal * particle = new XReal(swarm_->get(i)) ; - //particle.move(speed_[i]); - for (int var = 0; var < particle->size(); var++) { - particle->setValue(var, particle->getValue(var) + speed_[i][var]) ; - if (particle->getValue(var) < problem_->getLowerLimit(var)) { - particle->setValue(var, problem_->getLowerLimit(var)); - speed_[i][var] = 0; - } - if (particle->getValue(var) > problem_->getUpperLimit(var)) { - particle->setValue(var, problem_->getUpperLimit(var)); - speed_[i][var] = 0; - } +void StandardPSO2007::computeNewPositions() +{ + for (int i = 0; i < swarmSize_; i++) + { + //Variable[] particle = swarm_.get(i).getDecisionVariables(); + XReal * particle = new XReal(swarm_->get(i)) ; + //particle.move(speed_[i]); + for (int var = 0; var < particle->size(); var++) + { + particle->setValue(var, particle->getValue(var) + speed_[i][var]) ; + if (particle->getValue(var) < problem_->getLowerLimit(var)) + { + particle->setValue(var, problem_->getLowerLimit(var)); + speed_[i][var] = 0; + } + if (particle->getValue(var) > problem_->getUpperLimit(var)) + { + particle->setValue(var, problem_->getUpperLimit(var)); + speed_[i][var] = 0; + } + } + delete particle; } - delete particle; - } } // computeNewPositions @@ -176,121 +197,138 @@ void StandardPSO2007::computeNewPositions() { * @return a SolutionSet that is a set of non dominated solutions * as a result of the algorithm execution */ -SolutionSet * StandardPSO2007::execute() { - initParams(); - - // Step 1 Create the initial population and evaluate - for (int i = 0; i < swarmSize_; i++) { - Solution * particle = new Solution(problem_); - problem_->evaluate(particle); - evaluations_ ++ ; - swarm_->add(particle); - } - - neighborhood_ = new AdaptiveRandomNeighborhood(swarm_, numberOfParticlesToInform_) ; - - cout << "SwarmSize: " << swarmSize_ << endl; - cout << "Swarm size: " << swarm_->size() << endl; - cout << "list size: " << neighborhood_->getNeighborhood().size() << endl; - - //-> Step2. Initialize the speed_ of each particle - for (int i = 0; i < swarmSize_; i++) { - XReal * particle = new XReal(swarm_->get(i)) ; - speed_[i] = new double[problem_->getNumberOfVariables()]; - for (int j = 0; j < problem_->getNumberOfVariables(); j++) { - speed_[i][j] = (PseudoRandom::randDouble(particle->getLowerBound(j),particle->getUpperBound(j)) - - particle->getValue(j))/2.0 ; +SolutionSet * StandardPSO2007::execute() +{ + initParams(); + + // Step 1 Create the initial population and evaluate + for (int i = 0; i < swarmSize_; i++) + { + Solution * particle = new Solution(problem_); + problem_->evaluate(particle); + evaluations_ ++ ; + swarm_->add(particle); } - delete particle; - } - - //-> Step 6. Initialize the memory of each particle - for (int i = 0; i < swarm_->size(); i++) { - Solution * particle = new Solution(swarm_->get(i)); - localBest_[i] = particle; - } - - for (int i = 0; i < swarm_->size(); i++) { - neighborhoodBest_[i] = getNeighborBest(i) ; - } - - //cout << "neighborhood_i " << neighborhood_->getNeighbors(0) << endl; - cout << "["; - for (int i = 0; i < neighborhood_->getNeighbors(0).size()-1; i++) { - cout << neighborhood_->getNeighbors(0).at(i) << ","; - } - cout << neighborhood_->getNeighbors(0).back() << "]" << endl; - for (int s : neighborhood_->getNeighbors(0)) { - cout << s << ": " << localBest_[s]->getObjective(0) << endl; - } - - cout << "localBest_i " << localBest_[0]->getObjective(0) << endl; - cout << "neighborhoodBest_i " << getNeighborBest(0)->getObjective(0) << endl; - - cout << "Swarm: " << swarm_ << endl; - swarm_->printObjectives(); - double b = swarm_->best(comparator_)->getObjective(0) ; - cout << "Best: " << b << endl; - - double bestFoundFitness = numeric_limits::max(); - - while (iteration_ < maxIterations_) { - //Compute the speed - computeSpeed() ; - - //Compute the new positions for the swarm - computeNewPositions(); - - //Evaluate the new swarm_ in new positions - for (int i = 0; i < swarm_->size(); i++) { - Solution * particle = swarm_->get(i); - problem_->evaluate(particle); - evaluations_ ++ ; + + neighborhood_ = new AdaptiveRandomNeighborhood(swarm_, numberOfParticlesToInform_) ; + + std::cout << "SwarmSize: " << swarmSize_ << std::endl; + std::cout << "Swarm size: " << swarm_->size() << std::endl; + std::cout << "list size: " << neighborhood_->getNeighborhood().size() << std::endl; + + //-> Step2. Initialize the speed_ of each particle + for (int i = 0; i < swarmSize_; i++) + { + XReal * particle = new XReal(swarm_->get(i)) ; + speed_[i] = snew double[problem_->getNumberOfVariables()]; + for (int j = 0; j < problem_->getNumberOfVariables(); j++) + { + speed_[i][j] = (PseudoRandom::randDouble(particle->getLowerBound(j),particle->getUpperBound(j)) + - particle->getValue(j))/2.0 ; + } + delete particle; } - //Update the memory of the particles - for (int i = 0; i < swarm_->size(); i++) { - if ((swarm_->get(i)->getObjective(0) < localBest_[i]->getObjective(0))) { + //-> Step 6. Initialize the memory of each particle + for (int i = 0; i < swarm_->size(); i++) + { Solution * particle = new Solution(swarm_->get(i)); - delete localBest_[i]; localBest_[i] = particle; - } // if } - for (int i = 0; i < swarm_->size(); i++) { - neighborhoodBest_[i] = getNeighborBest(i) ; + + for (int i = 0; i < swarm_->size(); i++) + { + neighborhoodBest_[i] = getNeighborBest(i) ; } - iteration_++; - //System.out.println("Swarm( " + iteration_+ "): " + swarm_) ; - //swarm_.printObjectives(); - double bestCurrentFitness = swarm_->best(comparator_)->getObjective(0) ; - cout << "Best: " << bestCurrentFitness << endl; + //std::cout << "neighborhood_i " << neighborhood_->getNeighbors(0) << std::endl; + std::cout << "["; + for (int i = 0; i < neighborhood_->getNeighbors(0).size()-1; i++) + { + std::cout << neighborhood_->getNeighbors(0).at(i) << ","; + } + std::cout << neighborhood_->getNeighbors(0).back() << "]" << std::endl; + for (int s : neighborhood_->getNeighbors(0)) + { + std::cout << s << ": " << localBest_[s]->getObjective(0) << std::endl; + } - if (bestCurrentFitness == bestFoundFitness) { - cout << "Recomputing" << endl; - neighborhood_->recompute(); + std::cout << "localBest_i " << localBest_[0]->getObjective(0) << std::endl; + std::cout << "neighborhoodBest_i " << getNeighborBest(0)->getObjective(0) << std::endl; + + std::cout << "Swarm: " << swarm_ << std::endl; + swarm_->printObjectives(); + double b = swarm_->best(comparator_)->getObjective(0) ; + std::cout << "Best: " << b << std::endl; + + double bestFoundFitness = numeric_limits::max(); + + while (iteration_ < maxIterations_) + { + //Compute the speed + computeSpeed() ; + + //Compute the new positions for the swarm + computeNewPositions(); + + //Evaluate the new swarm_ in new positions + for (int i = 0; i < swarm_->size(); i++) + { + Solution * particle = swarm_->get(i); + problem_->evaluate(particle); + evaluations_ ++ ; + } + + //Update the memory of the particles + for (int i = 0; i < swarm_->size(); i++) + { + if ((swarm_->get(i)->getObjective(0) < localBest_[i]->getObjective(0))) + { + Solution * particle = new Solution(swarm_->get(i)); + delete localBest_[i]; + localBest_[i] = particle; + } // if + } + for (int i = 0; i < swarm_->size(); i++) + { + neighborhoodBest_[i] = getNeighborBest(i) ; + } + + iteration_++; + //System.out.println("Swarm( " + iteration_+ "): " + swarm_) ; + //swarm_.printObjectives(); + double bestCurrentFitness = swarm_->best(comparator_)->getObjective(0) ; + std::cout << "Best: " << bestCurrentFitness << std::endl; + + if (bestCurrentFitness == bestFoundFitness) + { + std::cout << "Recomputing" << std::endl; + neighborhood_->recompute(); + } + + if (bestCurrentFitness < bestFoundFitness) + { + bestFoundFitness = bestCurrentFitness ; + } } - if (bestCurrentFitness < bestFoundFitness) { - bestFoundFitness = bestCurrentFitness ; + // Return a population with the best individual + SolutionSet * resultPopulation = new SolutionSet(1) ; + int * bestSolutionIdx = (int *) findBestSolution_->execute(swarm_); + resultPopulation->add(new Solution(swarm_->get(* bestSolutionIdx))) ; + delete bestSolutionIdx; + + // Free memory + for (int i = 0; i < swarmSize_; i++) + { + delete [] speed_[i]; } - } - - // Return a population with the best individual - SolutionSet * resultPopulation = new SolutionSet(1) ; - int * bestSolutionIdx = (int *) findBestSolution_->execute(swarm_); - resultPopulation->add(new Solution(swarm_->get(* bestSolutionIdx))) ; - delete bestSolutionIdx; - - // Free memory - for (int i = 0; i < swarmSize_; i++) { - delete [] speed_[i]; - } - for (int i = 0; i < swarm_->size(); i++) { - delete localBest_[i]; - } - delete neighborhood_; - deleteParams(); - - return resultPopulation ; + for (int i = 0; i < swarm_->size(); i++) + { + delete localBest_[i]; + } + delete neighborhood_; + deleteParams(); + + return resultPopulation ; } // execute diff --git a/src/metaheuristics/singleObjective/particleSwarmOptimization/StandardPSO2007.h b/src/metaheuristics/singleObjective/particleSwarmOptimization/StandardPSO2007.h index e0ce910..e76568f 100644 --- a/src/metaheuristics/singleObjective/particleSwarmOptimization/StandardPSO2007.h +++ b/src/metaheuristics/singleObjective/particleSwarmOptimization/StandardPSO2007.h @@ -2,6 +2,7 @@ // // Author: // Esteban López-Camacho +// Sérgio Vieira // Antonio J. Nebro // // Copyright (c) 2014 Antonio J. Nebro @@ -36,46 +37,47 @@ /** * Class implementing a Standard PSO 2007 algorithm */ -class StandardPSO2007 : public Algorithm { +class StandardPSO2007 : public Algorithm +{ private: - SolutionSet * swarm_; - int swarmSize_; - int maxIterations_; - int iteration_; - int numberOfParticlesToInform_ ; // Referred a K in the SPSO document - Solution ** localBest_; - Solution ** neighborhoodBest_; - double ** speed_; - AdaptiveRandomNeighborhood * neighborhood_ ; + SolutionSet * swarm_; + int swarmSize_; + int maxIterations_; + int iteration_; + int numberOfParticlesToInform_ ; // Referred a K in the SPSO document + Solution ** localBest_; + Solution ** neighborhoodBest_; + double ** speed_; + AdaptiveRandomNeighborhood * neighborhood_ ; - int evaluations_ ; + int evaluations_ ; - /** - * Comparator object - */ - Comparator * comparator_ ; + /** + * Comparator object + */ + Comparator * comparator_ ; - Operator * findBestSolution_ ; + Operator * findBestSolution_ ; - double W_; - double C_; + double W_; + double C_; - void initParams(); - void deleteParams(); - Solution * getNeighborBest(int i); - void computeSpeed(); - void computeNewPositions(); + void initParams(); + void deleteParams(); + Solution * getNeighborBest(int i); + void computeSpeed(); + void computeNewPositions(); public: - double getW(); - double getC(); + double getW(); + double getC(); - StandardPSO2007(Problem * problem); - ~StandardPSO2007(); - SolutionSet * execute(); + StandardPSO2007(Problem * problem); + ~StandardPSO2007(); + SolutionSet * execute(); }; // StandardPSO2007 diff --git a/src/metaheuristics/singleObjective/particleSwarmOptimization/StandardPSO2011.cpp b/src/metaheuristics/singleObjective/particleSwarmOptimization/StandardPSO2011.cpp index 56448dc..65f0f49 100644 --- a/src/metaheuristics/singleObjective/particleSwarmOptimization/StandardPSO2011.cpp +++ b/src/metaheuristics/singleObjective/particleSwarmOptimization/StandardPSO2011.cpp @@ -2,6 +2,7 @@ // // Author: // Esteban López-Camacho +// Sérgio Vieira // Antonio J. Nebro // // Copyright (c) 2014 Antonio J. Nebro @@ -32,165 +33,188 @@ * Constructor * @param problem Problem to solve */ -StandardPSO2011::StandardPSO2011(Problem * problem) : Algorithm(problem) { +StandardPSO2011::StandardPSO2011(Problem * problem) : Algorithm(problem) +{ - W_ = 1.0/(2.0 * log(2)) ; //0.721; - C_ = 1.0/2.0 + log(2) ; //1.193; - ChVel_ = -0.5 ; + W_ = 1.0/(2.0 * log(2)) ; //0.721; + C_ = 1.0/2.0 + log(2) ; //1.193; + ChVel_ = -0.5 ; - comparator_ = new ObjectiveComparator(0) ; // Single objective comparator - map parameters ; // Operator parameters + comparator_ = new ObjectiveComparator(0) ; // Single objective comparator + MapOfStringFunct parameters ; // Operator parameters - parameters["comparator"] = comparator_; - findBestSolution_ = new BestSolutionSelection(parameters) ; + parameters["comparator"] = comparator_; + findBestSolution_ = new BestSolutionSelection(parameters) ; - evaluations_ = 0 ; + evaluations_ = 0 ; } // StandardPSO2011 /** * Destructor */ -StandardPSO2011::~StandardPSO2011() { - delete comparator_; - delete findBestSolution_; +StandardPSO2011::~StandardPSO2011() +{ + delete comparator_; + delete findBestSolution_; } // ~StandardPSO2011 -double StandardPSO2011::getW() { - return W_; +double StandardPSO2011::getW() +{ + return W_; } // getW -double StandardPSO2011::getC() { - return C_; +double StandardPSO2011::getC() +{ + return C_; } // getC /** * Initialize all parameters of the algorithm */ -void StandardPSO2011::initParams() { - swarmSize_ = *(int *) getInputParameter("swarmSize"); - maxIterations_ = *(int *) getInputParameter("maxIterations"); - numberOfParticlesToInform_ = *(int *) getInputParameter("numberOfParticlesToInform"); +void StandardPSO2011::initParams() +{ + swarmSize_ = *(int *) getInputParameter("swarmSize"); + maxIterations_ = *(int *) getInputParameter("maxIterations"); + numberOfParticlesToInform_ = *(int *) getInputParameter("numberOfParticlesToInform"); - cout << "Swarm size: " << swarmSize_ << endl; + std::cout << "Swarm size: " << swarmSize_ << std::endl; - iteration_ = 0; + iteration_ = 0; - swarm_ = new SolutionSet(swarmSize_); - localBest_ = new Solution*[swarmSize_]; - neighborhoodBest_ = new Solution*[swarmSize_]; + swarm_ = new SolutionSet(swarmSize_); + localBest_ = new Solution*[swarmSize_]; + neighborhoodBest_ = new Solution*[swarmSize_]; - // Create the speed_ vector - speed_ = new double*[swarmSize_]; + // Create the speed_ vector + speed_ = snew double*[swarmSize_]; } // initParams /** * Delete all parameters of the algorithm */ -void StandardPSO2011::deleteParams() { - delete swarm_; - delete [] localBest_; - delete [] neighborhoodBest_; - delete [] speed_; +void StandardPSO2011::deleteParams() +{ + delete swarm_; + delete [] localBest_; + delete [] neighborhoodBest_; + delete [] speed_; } // deleteParams -Solution * StandardPSO2011::getNeighborBest(int i) { - Solution * bestLocalBestSolution = NULL ; +Solution * StandardPSO2011::getNeighborBest(int i) +{ + Solution * bestLocalBestSolution = nullptr ; - for (int index : neighborhood_->getNeighbors(i)) { - if ((bestLocalBestSolution == NULL) || (bestLocalBestSolution->getObjective(0) > localBest_[index]->getObjective(0))) { - bestLocalBestSolution = localBest_[index] ; + for (int index : neighborhood_->getNeighbors(i)) + { + if ((bestLocalBestSolution == nullptr) || (bestLocalBestSolution->getObjective(0) > localBest_[index]->getObjective(0))) + { + bestLocalBestSolution = localBest_[index] ; + } } - } - return bestLocalBestSolution ; + return bestLocalBestSolution ; } // getNeighborBest -void StandardPSO2011::computeSpeed() { +void StandardPSO2011::computeSpeed() +{ + + for (int i = 0; i < swarmSize_; i++) + { + XReal * particle = new XReal(swarm_->get(i)) ; + XReal * localBest = new XReal(localBest_[i]) ; + XReal * neighborhoodBest = new XReal(neighborhoodBest_[i]) ; + + Solution * gravityCenterSolution = new Solution(problem_); + XReal * gravityCenter = new XReal(gravityCenterSolution) ; + Solution * randomParticleSolution = new Solution(swarm_->get(i)); + XReal * randomParticle = new XReal (randomParticleSolution) ; + + if (localBest_[i] != neighborhoodBest_[i]) + { + for (int var = 0; var < particle->size(); var++) + { + double G; + G = particle->getValue(var) + + C_ * (localBest->getValue(var) + neighborhoodBest->getValue(var) - 2 * particle->getValue(var)) / 3.0; + + gravityCenter->setValue(var, G); + } + } + else + { + for (int var = 0; var < particle->size(); var++) + { + double G; + G = particle->getValue(var) + + C_ * (localBest->getValue(var) - particle->getValue(var)) / 2.0; + + gravityCenter->setValue(var, G); + } + } + + double radius = 0; + Distance * distance = new Distance(); + radius = distance->distanceBetweenSolutions(gravityCenter->getSolution(), particle->getSolution()); + delete distance; + + double * random = PseudoRandom::randSphere(problem_->getNumberOfVariables()) ; + for (int var = 0; var < particle->size(); var++) + { + randomParticle->setValue(var, gravityCenter->getValue(var) + radius*random[var]) ; + } + delete [] random; + + for (int var = 0; var < particle->getNumberOfDecisionVariables(); var++) + { + speed_[i][var] = W_*speed_[i][var] + randomParticle->getValue(var) - particle->getValue(var); + } + + delete particle; + delete localBest; + delete neighborhoodBest; + + delete gravityCenterSolution; + delete gravityCenter; + delete randomParticleSolution; + delete randomParticle; - for (int i = 0; i < swarmSize_; i++) { - XReal * particle = new XReal(swarm_->get(i)) ; - XReal * localBest = new XReal(localBest_[i]) ; - XReal * neighborhoodBest = new XReal(neighborhoodBest_[i]) ; - - Solution * gravityCenterSolution = new Solution(problem_); - XReal * gravityCenter = new XReal(gravityCenterSolution) ; - Solution * randomParticleSolution = new Solution(swarm_->get(i)); - XReal * randomParticle = new XReal (randomParticleSolution) ; - - if (localBest_[i] != neighborhoodBest_[i]) { - for (int var = 0; var < particle->size(); var++) { - double G; - G = particle->getValue(var) + - C_ * (localBest->getValue(var) + neighborhoodBest->getValue(var) - 2 * particle->getValue(var)) / 3.0; - - gravityCenter->setValue(var, G); - } - } else { - for (int var = 0; var < particle->size(); var++) { - double G; - G = particle->getValue(var) + - C_ * (localBest->getValue(var) - particle->getValue(var)) / 2.0; - - gravityCenter->setValue(var, G); - } } - - double radius = 0; - Distance * distance = new Distance(); - radius = distance->distanceBetweenSolutions(gravityCenter->getSolution(), particle->getSolution()); - delete distance; - - double * random = PseudoRandom::randSphere(problem_->getNumberOfVariables()) ; - for (int var = 0; var < particle->size(); var++) { - randomParticle->setValue(var, gravityCenter->getValue(var) + radius*random[var]) ; - } - delete [] random; - - for (int var = 0; var < particle->getNumberOfDecisionVariables(); var++) { - speed_[i][var] = W_*speed_[i][var] + randomParticle->getValue(var) - particle->getValue(var); - } - - delete particle; - delete localBest; - delete neighborhoodBest; - - delete gravityCenterSolution; - delete gravityCenter; - delete randomParticleSolution; - delete randomParticle; - - } } // computeSpeed /** * Update the position of each particle */ -void StandardPSO2011::computeNewPositions() { - for (int i = 0; i < swarmSize_; i++) { - //Variable[] particle = swarm_.get(i).getDecisionVariables(); - XReal * particle = new XReal(swarm_->get(i)) ; - //particle.move(speed_[i]); - for (int var = 0; var < particle->size(); var++) { - particle->setValue(var, particle->getValue(var) + speed_[i][var]) ; - if (particle->getValue(var) < problem_->getLowerLimit(var)) { - particle->setValue(var, problem_->getLowerLimit(var)); - speed_[i][var] = ChVel_ * speed_[i][var]; - } - if (particle->getValue(var) > problem_->getUpperLimit(var)) { - particle->setValue(var, problem_->getUpperLimit(var)); - speed_[i][var] = ChVel_ * speed_[i][var]; - } +void StandardPSO2011::computeNewPositions() +{ + for (int i = 0; i < swarmSize_; i++) + { + //Variable[] particle = swarm_.get(i).getDecisionVariables(); + XReal * particle = new XReal(swarm_->get(i)) ; + //particle.move(speed_[i]); + for (int var = 0; var < particle->size(); var++) + { + particle->setValue(var, particle->getValue(var) + speed_[i][var]) ; + if (particle->getValue(var) < problem_->getLowerLimit(var)) + { + particle->setValue(var, problem_->getLowerLimit(var)); + speed_[i][var] = ChVel_ * speed_[i][var]; + } + if (particle->getValue(var) > problem_->getUpperLimit(var)) + { + particle->setValue(var, problem_->getUpperLimit(var)); + speed_[i][var] = ChVel_ * speed_[i][var]; + } + } + delete particle; } - delete particle; - } } // computeNewPositions @@ -199,122 +223,139 @@ void StandardPSO2011::computeNewPositions() { * @return a SolutionSet that is a set of non dominated solutions * as a result of the algorithm execution */ -SolutionSet * StandardPSO2011::execute() { - initParams(); - - // Step 1 Create the initial population and evaluate - for (int i = 0; i < swarmSize_; i++) { - Solution * particle = new Solution(problem_); - problem_->evaluate(particle); - evaluations_ ++ ; - swarm_->add(particle); - } - - neighborhood_ = new AdaptiveRandomNeighborhood(swarm_, numberOfParticlesToInform_) ; - - cout << "SwarmSize: " << swarmSize_ << endl; - cout << "Swarm size: " << swarm_->size() << endl; - cout << "list size: " << neighborhood_->getNeighborhood().size() << endl; - - //-> Step2. Initialize the speed_ of each particle - for (int i = 0; i < swarmSize_; i++) { - XReal * particle = new XReal(swarm_->get(i)) ; - speed_[i] = new double[problem_->getNumberOfVariables()]; - for (int j = 0; j < problem_->getNumberOfVariables(); j++) { - speed_[i][j] = (PseudoRandom::randDouble( - particle->getLowerBound(j) - particle->getValue(0), - particle->getUpperBound(j) - particle->getValue(0))) ; +SolutionSet * StandardPSO2011::execute() +{ + initParams(); + + // Step 1 Create the initial population and evaluate + for (int i = 0; i < swarmSize_; i++) + { + Solution * particle = new Solution(problem_); + problem_->evaluate(particle); + evaluations_ ++ ; + swarm_->add(particle); } - delete particle; - } - - //-> Step 6. Initialize the memory of each particle - for (int i = 0; i < swarm_->size(); i++) { - Solution * particle = new Solution(swarm_->get(i)); - localBest_[i] = particle; - } - - for (int i = 0; i < swarm_->size(); i++) { - neighborhoodBest_[i] = getNeighborBest(i) ; - } - - //cout << "neighborhood_i " << neighborhood_->getNeighbors(0) << endl; - cout << "["; - for (int i = 0; i < neighborhood_->getNeighbors(0).size()-1; i++) { - cout << neighborhood_->getNeighbors(0).at(i) << ","; - } - cout << neighborhood_->getNeighbors(0).back() << "]" << endl; - for (int s : neighborhood_->getNeighbors(0)) { - cout << s << ": " << localBest_[s]->getObjective(0) << endl; - } - - cout << "localBest_i " << localBest_[0]->getObjective(0) << endl; - cout << "neighborhoodBest_i " << getNeighborBest(0)->getObjective(0) << endl; - - cout << "Swarm: " << swarm_ << endl; - swarm_->printObjectives(); - double b = swarm_->best(comparator_)->getObjective(0) ; - cout << "Best: " << b << endl; - - double bestFoundFitness = numeric_limits::max(); - - while (iteration_ < maxIterations_) { - //Compute the speed - computeSpeed() ; - - //Compute the new positions for the swarm - computeNewPositions(); - - //Evaluate the new swarm_ in new positions - for (int i = 0; i < swarm_->size(); i++) { - Solution * particle = swarm_->get(i); - problem_->evaluate(particle); - evaluations_ ++ ; + + neighborhood_ = new AdaptiveRandomNeighborhood(swarm_, numberOfParticlesToInform_) ; + + std::cout << "SwarmSize: " << swarmSize_ << std::endl; + std::cout << "Swarm size: " << swarm_->size() << std::endl; + std::cout << "list size: " << neighborhood_->getNeighborhood().size() << std::endl; + + //-> Step2. Initialize the speed_ of each particle + for (int i = 0; i < swarmSize_; i++) + { + XReal * particle = new XReal(swarm_->get(i)) ; + speed_[i] = snew double[problem_->getNumberOfVariables()]; + for (int j = 0; j < problem_->getNumberOfVariables(); j++) + { + speed_[i][j] = (PseudoRandom::randDouble( + particle->getLowerBound(j) - particle->getValue(0), + particle->getUpperBound(j) - particle->getValue(0))) ; + } + delete particle; } - //Update the memory of the particles - for (int i = 0; i < swarm_->size(); i++) { - if ((swarm_->get(i)->getObjective(0) < localBest_[i]->getObjective(0))) { + //-> Step 6. Initialize the memory of each particle + for (int i = 0; i < swarm_->size(); i++) + { Solution * particle = new Solution(swarm_->get(i)); - delete localBest_[i]; localBest_[i] = particle; - } // if } - for (int i = 0; i < swarm_->size(); i++) { - neighborhoodBest_[i] = getNeighborBest(i) ; + + for (int i = 0; i < swarm_->size(); i++) + { + neighborhoodBest_[i] = getNeighborBest(i) ; } - iteration_++; - //System.out.println("Swarm( " + iteration_+ "): " + swarm_) ; - //swarm_.printObjectives(); - double bestCurrentFitness = swarm_->best(comparator_)->getObjective(0) ; - //cout << "Best: " << bestCurrentFitness << endl; + //std::cout << "neighborhood_i " << neighborhood_->getNeighbors(0) << std::endl; + std::cout << "["; + for (int i = 0; i < neighborhood_->getNeighbors(0).size()-1; i++) + { + std::cout << neighborhood_->getNeighbors(0).at(i) << ","; + } + std::cout << neighborhood_->getNeighbors(0).back() << "]" << std::endl; + for (int s : neighborhood_->getNeighbors(0)) + { + std::cout << s << ": " << localBest_[s]->getObjective(0) << std::endl; + } - if (bestCurrentFitness == bestFoundFitness) { - //cout << "Recomputing" << endl; - neighborhood_->recompute(); + std::cout << "localBest_i " << localBest_[0]->getObjective(0) << std::endl; + std::cout << "neighborhoodBest_i " << getNeighborBest(0)->getObjective(0) << std::endl; + + std::cout << "Swarm: " << swarm_ << std::endl; + swarm_->printObjectives(); + double b = swarm_->best(comparator_)->getObjective(0) ; + std::cout << "Best: " << b << std::endl; + + double bestFoundFitness = numeric_limits::max(); + + while (iteration_ < maxIterations_) + { + //Compute the speed + computeSpeed() ; + + //Compute the new positions for the swarm + computeNewPositions(); + + //Evaluate the new swarm_ in new positions + for (int i = 0; i < swarm_->size(); i++) + { + Solution * particle = swarm_->get(i); + problem_->evaluate(particle); + evaluations_ ++ ; + } + + //Update the memory of the particles + for (int i = 0; i < swarm_->size(); i++) + { + if ((swarm_->get(i)->getObjective(0) < localBest_[i]->getObjective(0))) + { + Solution * particle = new Solution(swarm_->get(i)); + delete localBest_[i]; + localBest_[i] = particle; + } // if + } + for (int i = 0; i < swarm_->size(); i++) + { + neighborhoodBest_[i] = getNeighborBest(i) ; + } + + iteration_++; + //System.out.println("Swarm( " + iteration_+ "): " + swarm_) ; + //swarm_.printObjectives(); + double bestCurrentFitness = swarm_->best(comparator_)->getObjective(0) ; + //std::cout << "Best: " << bestCurrentFitness << std::endl; + + if (bestCurrentFitness == bestFoundFitness) + { + //std::cout << "Recomputing" << std::endl; + neighborhood_->recompute(); + } + + if (bestCurrentFitness < bestFoundFitness) + { + bestFoundFitness = bestCurrentFitness ; + } } - if (bestCurrentFitness < bestFoundFitness) { - bestFoundFitness = bestCurrentFitness ; + // Return a population with the best individual + SolutionSet * resultPopulation = new SolutionSet(1) ; + int * bestSolutionIdx = (int *) findBestSolution_->execute(swarm_); + resultPopulation->add(new Solution(swarm_->get(* bestSolutionIdx))) ; + delete bestSolutionIdx; + + // Free memory + for (int i = 0; i < swarmSize_; i++) + { + delete [] speed_[i]; } - } - - // Return a population with the best individual - SolutionSet * resultPopulation = new SolutionSet(1) ; - int * bestSolutionIdx = (int *) findBestSolution_->execute(swarm_); - resultPopulation->add(new Solution(swarm_->get(* bestSolutionIdx))) ; - delete bestSolutionIdx; - - // Free memory - for (int i = 0; i < swarmSize_; i++) { - delete [] speed_[i]; - } - for (int i = 0; i < swarm_->size(); i++) { - delete localBest_[i]; - } - delete neighborhood_; - deleteParams(); - - return resultPopulation ; + for (int i = 0; i < swarm_->size(); i++) + { + delete localBest_[i]; + } + delete neighborhood_; + deleteParams(); + + return resultPopulation ; } // execute diff --git a/src/metaheuristics/singleObjective/particleSwarmOptimization/StandardPSO2011.h b/src/metaheuristics/singleObjective/particleSwarmOptimization/StandardPSO2011.h index 20c27ed..fbe584e 100644 --- a/src/metaheuristics/singleObjective/particleSwarmOptimization/StandardPSO2011.h +++ b/src/metaheuristics/singleObjective/particleSwarmOptimization/StandardPSO2011.h @@ -2,6 +2,7 @@ // // Author: // Esteban López-Camacho +// Sérgio Vieira // Antonio J. Nebro // // Copyright (c) 2014 Antonio J. Nebro @@ -37,47 +38,48 @@ /** * Class implementing a Standard PSO 2011 algorithm */ -class StandardPSO2011 : public Algorithm { +class StandardPSO2011 : public Algorithm +{ private: - SolutionSet * swarm_; - int swarmSize_; - int maxIterations_; - int iteration_; - int numberOfParticlesToInform_ ; // Referred a K in the SPSO document - Solution ** localBest_; - Solution ** neighborhoodBest_; - double ** speed_; - AdaptiveRandomNeighborhood * neighborhood_ ; + SolutionSet * swarm_; + int swarmSize_; + int maxIterations_; + int iteration_; + int numberOfParticlesToInform_ ; // Referred a K in the SPSO document + Solution ** localBest_; + Solution ** neighborhoodBest_; + double ** speed_; + AdaptiveRandomNeighborhood * neighborhood_ ; - int evaluations_ ; + int evaluations_ ; - /** - * Comparator object - */ - Comparator * comparator_ ; + /** + * Comparator object + */ + Comparator * comparator_ ; - Operator * findBestSolution_ ; + Operator * findBestSolution_ ; - double W_; - double C_; - double ChVel_; + double W_; + double C_; + double ChVel_; - void initParams(); - void deleteParams(); - Solution * getNeighborBest(int i); - void computeSpeed(); - void computeNewPositions(); + void initParams(); + void deleteParams(); + Solution * getNeighborBest(int i); + void computeSpeed(); + void computeNewPositions(); public: - double getW(); - double getC(); + double getW(); + double getC(); - StandardPSO2011(Problem * problem); - ~StandardPSO2011(); - SolutionSet * execute(); + StandardPSO2011(Problem * problem); + ~StandardPSO2011(); + SolutionSet * execute(); }; // StandardPSO2011 diff --git a/src/metaheuristics/smpso/CMakeLists.txt b/src/metaheuristics/smpso/CMakeLists.txt new file mode 100644 index 0000000..294ec59 --- /dev/null +++ b/src/metaheuristics/smpso/CMakeLists.txt @@ -0,0 +1,3 @@ +file(GLOB SOURCES "*.cpp" "*.h") +ListToString(SOURCES ";" ${SOURCES}) +LIST_APPEND("${SOURCES}") \ No newline at end of file diff --git a/src/metaheuristics/smpso/SMPSO.cpp b/src/metaheuristics/smpso/SMPSO.cpp index 034780a..156e634 100644 --- a/src/metaheuristics/smpso/SMPSO.cpp +++ b/src/metaheuristics/smpso/SMPSO.cpp @@ -2,6 +2,7 @@ // // Author: // Esteban López-Camacho +// Sérgio Vieira // // Copyright (c) 2011 Antonio J. Nebro, Juan J. Durillo // @@ -31,96 +32,100 @@ * Constructor * @param problem Problem to solve */ -SMPSO::SMPSO(Problem *problem) : Algorithm(problem) { - r1Max_ = 1.0; - r1Min_ = 0.0; - r2Max_ = 1.0; - r2Min_ = 0.0; - C1Max_ = 2.5; - C1Min_ = 1.5; - C2Max_ = 2.5; - C2Min_ = 1.5; - WMax_ = 0.1; - WMin_ = 0.1; - ChVel1_ = -1; - ChVel2_ = -1; +SMPSO::SMPSO(Problem *problem) : Algorithm(problem) +{ + r1Max_ = 1.0; + r1Min_ = 0.0; + r2Max_ = 1.0; + r2Min_ = 0.0; + C1Max_ = 2.5; + C1Min_ = 1.5; + C2Max_ = 2.5; + C2Min_ = 1.5; + WMax_ = 0.1; + WMin_ = 0.1; + ChVel1_ = -1; + ChVel2_ = -1; } // SMPSO /** * Initialize all parameter of the algorithm */ -void SMPSO::initParams() { - swarmSize_ = *(int *) getInputParameter("swarmSize"); - archiveSize_ = *(int *) getInputParameter("archiveSize"); - maxIterations_ = *(int *) getInputParameter("maxIterations"); - - setAlgParams(); - - // TODO: indicators_ = (QualityIndicator) getInputParameter("indicators"); - - polynomialMutation_ = operators_["mutation"] ; - - iteration_ = 0 ; - - success_ = false; - - particles_ = new SolutionSet(swarmSize_); - best_ = new Solution*[swarmSize_]; - leaders_ = new CrowdingArchive(archiveSize_, problem_->getNumberOfObjectives()); - - // Create comparators for dominance and crowding distance - dominance_ = new DominanceComparator(); - crowdingDistanceComparator_ = new CrowdingDistanceComparator(); - distance_ = new Distance(); - - // Create the speed_ vector - int numberOfVariables = problem_->getNumberOfVariables(); - //speed_ = new double[swarmSize_][numberOfVariables]; - speed_ = new double*[swarmSize_]; - // TODO: Liberar memoria al finalizar - - deltaMax_ = new double[problem_->getNumberOfVariables()]; - deltaMin_ = new double[problem_->getNumberOfVariables()]; - for (int i = 0; i < problem_->getNumberOfVariables(); i++) { - deltaMax_[i] = (problem_->getUpperLimit(i) - - problem_->getLowerLimit(i)) / 2.0; - deltaMin_[i] = -deltaMax_[i]; - } // for +void SMPSO::initParams() +{ + swarmSize_ = *(int *) getInputParameter("swarmSize"); + archiveSize_ = *(int *) getInputParameter("archiveSize"); + maxIterations_ = *(int *) getInputParameter("maxIterations"); + + setAlgParams(); + + // TODO: indicators_ = (QualityIndicator) getInputParameter("indicators"); + + polynomialMutation_ = operators_["mutation"] ; + + iteration_ = 0 ; + + success_ = false; + + particles_ = new SolutionSet(swarmSize_); + best_ = new Solution*[swarmSize_]; + leaders_ = new CrowdingArchive(archiveSize_, problem_->getNumberOfObjectives()); + + // Create comparators for dominance and crowding distance + dominance_ = new DominanceComparator(); + crowdingDistanceComparator_ = new CrowdingDistanceComparator(); + distance_ = new Distance(); + + // Create the speed_ vector + int numberOfVariables = problem_->getNumberOfVariables(); + //speed_ = snew double[swarmSize_][numberOfVariables]; + speed_ = snew double*[swarmSize_]; + // TODO: Liberar memoria al finalizar + + deltaMax_ = snew double[problem_->getNumberOfVariables()]; + deltaMin_ = snew double[problem_->getNumberOfVariables()]; + for (int i = 0; i < problem_->getNumberOfVariables(); i++) + { + deltaMax_[i] = (problem_->getUpperLimit(i) - + problem_->getLowerLimit(i)) / 2.0; + deltaMin_[i] = -deltaMax_[i]; + } // for } // initParams - + /** * Read all user input parameters * Possible params: r1Max, r1Min, r2Max, r2Min, C1Max, C1Min, C2Max, C2Min, * WMax, Wmin, ChVel1, ChVel2 */ -void SMPSO::setAlgParams() { - - void * r1MaxPtr = getInputParameter("r1Max"); - void * r1MinPtr = getInputParameter("r1Min"); - void * r2MaxPtr = getInputParameter("r2Max"); - void * r2MinPtr = getInputParameter("r2Min"); - void * C1MaxPtr = getInputParameter("C1Min"); - void * C1MinPtr = getInputParameter("C1Max"); - void * C2MaxPtr = getInputParameter("C2Max"); - void * C2MinPtr = getInputParameter("C2Min"); - void * WMaxPtr = getInputParameter("WMax"); - void * WMinPtr = getInputParameter("WMin"); - void * ChVel1Ptr = getInputParameter("ChVel1"); - void * ChVel2Ptr = getInputParameter("ChVel2"); - - if (r1MaxPtr != NULL) r1Max_ = * (double *) r1MaxPtr; - if (r1MinPtr != NULL) r1Min_ = * (double *) r1MinPtr; - if (r2MaxPtr != NULL) r2Max_ = * (double *) r2MaxPtr; - if (r2MinPtr != NULL) r2Min_ = * (double *) r2MinPtr; - if (C1MaxPtr != NULL) C1Max_ = * (double *) C1MaxPtr; - if (C1MinPtr != NULL) C1Min_ = * (double *) C1MinPtr; - if (C2MaxPtr != NULL) C2Max_ = * (double *) C2MaxPtr; - if (C2MinPtr != NULL) C2Min_ = * (double *) C2MinPtr; - if (WMaxPtr != NULL) WMax_ = * (double *) WMaxPtr; - if (WMinPtr != NULL) WMin_ = * (double *) WMinPtr; - if (ChVel1Ptr != NULL) ChVel1_ = * (double *) ChVel1Ptr; - if (ChVel2Ptr != NULL) ChVel2_ = * (double *) ChVel2Ptr; +void SMPSO::setAlgParams() +{ + + void * r1MaxPtr = getInputParameter("r1Max"); + void * r1MinPtr = getInputParameter("r1Min"); + void * r2MaxPtr = getInputParameter("r2Max"); + void * r2MinPtr = getInputParameter("r2Min"); + void * C1MaxPtr = getInputParameter("C1Min"); + void * C1MinPtr = getInputParameter("C1Max"); + void * C2MaxPtr = getInputParameter("C2Max"); + void * C2MinPtr = getInputParameter("C2Min"); + void * WMaxPtr = getInputParameter("WMax"); + void * WMinPtr = getInputParameter("WMin"); + void * ChVel1Ptr = getInputParameter("ChVel1"); + void * ChVel2Ptr = getInputParameter("ChVel2"); + + if (r1MaxPtr != nullptr) r1Max_ = * (double *) r1MaxPtr; + if (r1MinPtr != nullptr) r1Min_ = * (double *) r1MinPtr; + if (r2MaxPtr != nullptr) r2Max_ = * (double *) r2MaxPtr; + if (r2MinPtr != nullptr) r2Min_ = * (double *) r2MinPtr; + if (C1MaxPtr != nullptr) C1Max_ = * (double *) C1MaxPtr; + if (C1MinPtr != nullptr) C1Min_ = * (double *) C1MinPtr; + if (C2MaxPtr != nullptr) C2Max_ = * (double *) C2MaxPtr; + if (C2MinPtr != nullptr) C2Min_ = * (double *) C2MinPtr; + if (WMaxPtr != nullptr) WMax_ = * (double *) WMaxPtr; + if (WMinPtr != nullptr) WMin_ = * (double *) WMinPtr; + if (ChVel1Ptr != nullptr) ChVel1_ = * (double *) ChVel1Ptr; + if (ChVel2Ptr != nullptr) ChVel2_ = * (double *) ChVel2Ptr; } // setAlgParams @@ -128,123 +133,140 @@ void SMPSO::setAlgParams() { /** * Free all the memory reserved by the algorithm */ -void SMPSO::deleteParams() { - - for (int i = 0; i < swarmSize_; i++) { - delete [] speed_[i]; - } - delete [] speed_; - delete dominance_; - delete crowdingDistanceComparator_; - delete distance_; - delete [] deltaMax_; - delete [] deltaMin_; - delete particles_; - for (int i = 0; i < swarmSize_; i++) { - delete best_[i]; - } - delete [] best_; - delete leaders_; +void SMPSO::deleteParams() +{ + + for (int i = 0; i < swarmSize_; i++) + { + delete [] speed_[i]; + } + delete [] speed_; + delete dominance_; + delete crowdingDistanceComparator_; + delete distance_; + delete [] deltaMax_; + delete [] deltaMin_; + delete particles_; + for (int i = 0; i < swarmSize_; i++) + { + delete best_[i]; + } + delete [] best_; + delete leaders_; } // deleteParams // Adaptive inertia -double SMPSO::inertiaWeight(int iter, int miter, double wma, double wmin) { - return wma; // - (((wma-wmin)*(double)iter)/(double)miter); +double SMPSO::inertiaWeight(int iter, int miter, double wma, double wmin) +{ + return wma; // - (((wma-wmin)*(double)iter)/(double)miter); } // inertiaWeight // constriction coefficient (M. Clerc) -double SMPSO::constrictionCoefficient(double c1, double c2) { - double rho = c1 + c2; - //rho = 1.0 ; - if (rho <= 4) { - return 1.0; - } else { - return 2 / (2 - rho - sqrt(pow(rho, 2.0) - 4.0 * rho)); - } +double SMPSO::constrictionCoefficient(double c1, double c2) +{ + double rho = c1 + c2; + //rho = 1.0 ; + if (rho <= 4) + { + return 1.0; + } + else + { + return 2 / (2 - rho - sqrt(pow(rho, 2.0) - 4.0 * rho)); + } } // constrictionCoefficient // velocity bounds double SMPSO::velocityConstriction(double v, double * deltaMax, - double * deltaMin, int variableIndex, - int particleIndex) { + double * deltaMin, int variableIndex, + int particleIndex) +{ - double result; + double result; - double dmax = deltaMax[variableIndex]; - double dmin = deltaMin[variableIndex]; + double dmax = deltaMax[variableIndex]; + double dmin = deltaMin[variableIndex]; - result = v; + result = v; - if (v > dmax) { - result = dmax; - } + if (v > dmax) + { + result = dmax; + } - if (v < dmin) { - result = dmin; - } + if (v < dmin) + { + result = dmin; + } - return result; + return result; } // velocityConstriction /** * Update the speed of each particle */ -void SMPSO::computeSpeed(int iter, int miter) { - double r1, r2, W, C1, C2; - double wmax, wmin, deltaMax, deltaMin; - XReal * bestGlobal; - - for (int i = 0; i < swarmSize_; i++) { - XReal * particle = new XReal(particles_->get(i)) ; - XReal * bestParticle = new XReal(best_[i]) ; - - //Select a global best_ for calculate the speed of particle i, bestGlobal - Solution * one; - Solution * two; - int pos1 = PseudoRandom::randInt(0, leaders_->size() - 1); - int pos2 = PseudoRandom::randInt(0, leaders_->size() - 1); - one = leaders_->get(pos1); - two = leaders_->get(pos2); - - if (crowdingDistanceComparator_->compare(one, two) < 1) { - bestGlobal = new XReal(one); - } else { - bestGlobal = new XReal(two); - } - //Params for velocity equation - r1 = PseudoRandom::randDouble(r1Min_, r1Max_); - r2 = PseudoRandom::randDouble(r2Min_, r2Max_); - C1 = PseudoRandom::randDouble(C1Min_, C1Max_); - C2 = PseudoRandom::randDouble(C2Min_, C2Max_); - W = PseudoRandom::randDouble(WMin_, WMax_); - // - wmax = WMax_; - wmin = WMin_; - - for (int var = 0; var < particle->getNumberOfDecisionVariables(); var++) { - //Computing the velocity of this particle - speed_[i][var] = velocityConstriction(constrictionCoefficient(C1, C2) * - (inertiaWeight(iter, miter, wmax, wmin) * - speed_[i][var] + - C1 * r1 * (bestParticle->getValue(var) - - particle->getValue(var)) + - C2 * r2 * (bestGlobal->getValue(var) - - particle->getValue(var))), deltaMax_, //[var], - deltaMin_, //[var], - var, - i); - } // for - - delete bestGlobal; - delete particle; - delete bestParticle; +void SMPSO::computeSpeed(int iter, int miter) +{ + double r1, r2, W, C1, C2; + double wmax, wmin, deltaMax, deltaMin; + XReal * bestGlobal; + + for (int i = 0; i < swarmSize_; i++) + { + XReal * particle = new XReal(particles_->get(i)) ; + XReal * bestParticle = new XReal(best_[i]) ; + + //Select a global best_ for calculate the speed of particle i, bestGlobal + Solution * one; + Solution * two; + int pos1 = PseudoRandom::randInt(0, leaders_->size() - 1); + int pos2 = PseudoRandom::randInt(0, leaders_->size() - 1); + one = leaders_->get(pos1); + two = leaders_->get(pos2); + + if (crowdingDistanceComparator_->compare(one, two) < 1) + { + bestGlobal = new XReal(one); + } + else + { + bestGlobal = new XReal(two); + } + //Params for velocity equation + r1 = PseudoRandom::randDouble(r1Min_, r1Max_); + r2 = PseudoRandom::randDouble(r2Min_, r2Max_); + C1 = PseudoRandom::randDouble(C1Min_, C1Max_); + C2 = PseudoRandom::randDouble(C2Min_, C2Max_); + W = PseudoRandom::randDouble(WMin_, WMax_); + // + wmax = WMax_; + wmin = WMin_; + + for (int var = 0; var < particle->getNumberOfDecisionVariables(); var++) + { + //Computing the velocity of this particle + speed_[i][var] = velocityConstriction(constrictionCoefficient(C1, C2) * + (inertiaWeight(iter, miter, wmax, wmin) * + speed_[i][var] + + C1 * r1 * (bestParticle->getValue(var) - + particle->getValue(var)) + + C2 * r2 * (bestGlobal->getValue(var) - + particle->getValue(var))), deltaMax_, //[var], + deltaMin_, //[var], + var, + i); + } // for + + delete bestGlobal; + delete particle; + delete bestParticle; - }// for + }// for } // computeSpeed @@ -252,40 +274,47 @@ void SMPSO::computeSpeed(int iter, int miter) { /** * Update the position of each particle */ -void SMPSO::computeNewPositions() { - for (int i = 0; i < swarmSize_; i++) { - XReal * particle = new XReal(particles_->get(i)) ; - for (int var = 0; var < particle->getNumberOfDecisionVariables(); var++) { - particle->setValue(var, particle->getValue(var) + speed_[i][var]) ; - - if (particle->getValue(var) < problem_->getLowerLimit(var)) { - particle->setValue(var, problem_->getLowerLimit(var)); - speed_[i][var] = speed_[i][var] * ChVel1_; // - } - if (particle->getValue(var) > problem_->getUpperLimit(var)) { - particle->setValue(var, problem_->getUpperLimit(var)); - speed_[i][var] = speed_[i][var] * ChVel2_; // - } +void SMPSO::computeNewPositions() +{ + for (int i = 0; i < swarmSize_; i++) + { + XReal * particle = new XReal(particles_->get(i)) ; + for (int var = 0; var < particle->getNumberOfDecisionVariables(); var++) + { + particle->setValue(var, particle->getValue(var) + speed_[i][var]) ; + + if (particle->getValue(var) < problem_->getLowerLimit(var)) + { + particle->setValue(var, problem_->getLowerLimit(var)); + speed_[i][var] = speed_[i][var] * ChVel1_; // + } + if (particle->getValue(var) > problem_->getUpperLimit(var)) + { + particle->setValue(var, problem_->getUpperLimit(var)); + speed_[i][var] = speed_[i][var] * ChVel2_; // + } + }// for + delete particle; }// for - delete particle; - }// for } // computeNewPositions /** * Apply a mutation operator to some particles in the swarm */ -void SMPSO::mopsoMutation(int actualIteration, int totalIterations) { - for (int i = 0; i < particles_->size(); i++) { - if ( (i % 6) == 0) - polynomialMutation_->execute(particles_->get(i)); - //if (i % 3 == 0) { //particles_ mutated with a non-uniform mutation %3 - // nonUniformMutation_.execute(particles_.get(i)); - //} else if (i % 3 == 1) { //particles_ mutated with a uniform mutation operator - // uniformMutation_.execute(particles_.get(i)); - //} else //particles_ without mutation - //; - } +void SMPSO::mopsoMutation(int actualIteration, int totalIterations) +{ + for (int i = 0; i < particles_->size(); i++) + { + if ( (i % 6) == 0) + polynomialMutation_->execute(particles_->get(i)); + //if (i % 3 == 0) { //particles_ mutated with a non-uniform mutation %3 + // nonUniformMutation_.execute(particles_.get(i)); + //} else if (i % 3 == 1) { //particles_ mutated with a uniform mutation operator + // uniformMutation_.execute(particles_.get(i)); + //} else //particles_ without mutation + //; + } } // mopsoMutation @@ -294,101 +323,115 @@ void SMPSO::mopsoMutation(int actualIteration, int totalIterations) { * @return a SolutionSet that is a set of non dominated solutions * as a result of the algorithm execution */ -SolutionSet * SMPSO::execute() { - - initParams(); - - success_ = false; - //->Step 1 (and 3) Create the initial population and evaluate - for (int i = 0; i < swarmSize_; i++) { - Solution * particle = new Solution(problem_); - problem_->evaluate(particle); - problem_->evaluateConstraints(particle); - particles_->add(particle); - } - - //-> Step2. Initialize the speed_ of each particle to 0 - for (int i = 0; i < swarmSize_; i++) { - speed_[i] = new double[problem_->getNumberOfVariables()]; - for (int j = 0; j < problem_->getNumberOfVariables(); j++) { - speed_[i][j] = 0.0; +SolutionSet * SMPSO::execute() +{ + + initParams(); + + success_ = false; + //->Step 1 (and 3) Create the initial population and evaluate + for (int i = 0; i < swarmSize_; i++) + { + Solution * particle = new Solution(problem_); + problem_->evaluate(particle); + problem_->evaluateConstraints(particle); + particles_->add(particle); } - } - - // Step4 and 5 - for (int i = 0; i < particles_->size(); i++) { - Solution * particle = new Solution(particles_->get(i)); - bool isAdded = leaders_->add(particle); - if (isAdded == false) { - delete particle; + + //-> Step2. Initialize the speed_ of each particle to 0 + for (int i = 0; i < swarmSize_; i++) + { + speed_[i] = snew double[problem_->getNumberOfVariables()]; + for (int j = 0; j < problem_->getNumberOfVariables(); j++) + { + speed_[i][j] = 0.0; + } } - } - //-> Step 6. Initialize the memory of each particle - for (int i = 0; i < particles_->size(); i++) { - Solution * particle = new Solution(particles_->get(i)); - best_[i] = particle; - } + // Step4 and 5 + for (int i = 0; i < particles_->size(); i++) + { + Solution * particle = new Solution(particles_->get(i)); + bool isAdded = leaders_->add(particle); + if (isAdded == false) + { + delete particle; + } + } + + //-> Step 6. Initialize the memory of each particle + for (int i = 0; i < particles_->size(); i++) + { + Solution * particle = new Solution(particles_->get(i)); + best_[i] = particle; + } - //Crowding the leaders_ - distance_->crowdingDistanceAssignment(leaders_, problem_->getNumberOfObjectives()); + //Crowding the leaders_ + distance_->crowdingDistanceAssignment(leaders_, problem_->getNumberOfObjectives()); - //-> Step 7. Iterations .. - while (iteration_ < maxIterations_) { + //-> Step 7. Iterations .. + while (iteration_ < maxIterations_) + { // try { // //Compute the speed_ // computeSpeed(iteration_, maxIterations_); // } catch (IOException ex) { // Logger.getLogger(SMPSO.class.getName()).log(Level.SEVERE, null, ex); // } - computeSpeed(iteration_, maxIterations_); - - //Compute the new positions for the particles_ - computeNewPositions(); - - //Mutate the particles_ - mopsoMutation(iteration_, maxIterations_); - - //Evaluate the new particles_ in new positions - for (int i = 0; i < particles_->size(); i++) { - Solution * particle = particles_->get(i); - problem_->evaluate(particle); - problem_->evaluateConstraints(particle); + computeSpeed(iteration_, maxIterations_); + + //Compute the new positions for the particles_ + computeNewPositions(); + + //Mutate the particles_ + mopsoMutation(iteration_, maxIterations_); + + //Evaluate the new particles_ in new positions + for (int i = 0; i < particles_->size(); i++) + { + Solution * particle = particles_->get(i); + problem_->evaluate(particle); + problem_->evaluateConstraints(particle); + } + + //Update the archive + for (int i = 0; i < particles_->size(); i++) + { + Solution * particle = new Solution(particles_->get(i)); + bool isAdded = leaders_->add(particle); + if (isAdded == false) + { + delete particle; + } + } + + //Update the memory of this particle + for (int i = 0; i < particles_->size(); i++) + { + int flag = dominance_->compare(particles_->get(i), best_[i]); + if (flag != 1) // the new particle is best_ than the older remembered + { + Solution * particle = new Solution(particles_->get(i)); + delete best_[i]; + best_[i] = particle; + } + } + + //Assign crowding distance to the leaders_ + distance_->crowdingDistanceAssignment(leaders_, + problem_->getNumberOfObjectives()); + iteration_++; } - //Update the archive - for (int i = 0; i < particles_->size(); i++) { - Solution * particle = new Solution(particles_->get(i)); - bool isAdded = leaders_->add(particle); - if (isAdded == false) { - delete particle; - } + // Build the solution set result + SolutionSet * result = new SolutionSet(leaders_->size()); + for (int i=0; isize(); i++) + { + result->add(new Solution(leaders_->get(i))); } - //Update the memory of this particle - for (int i = 0; i < particles_->size(); i++) { - int flag = dominance_->compare(particles_->get(i), best_[i]); - if (flag != 1) { // the new particle is best_ than the older remembered - Solution * particle = new Solution(particles_->get(i)); - delete best_[i]; - best_[i] = particle; - } - } - - //Assign crowding distance to the leaders_ - distance_->crowdingDistanceAssignment(leaders_, - problem_->getNumberOfObjectives()); - iteration_++; - } - - // Build the solution set result - SolutionSet * result = new SolutionSet(leaders_->size()); - for (int i=0;isize();i++) { - result->add(new Solution(leaders_->get(i))); - } - - // Free memory - deleteParams(); + // Free memory + deleteParams(); - return result; + return result; } // execute diff --git a/src/metaheuristics/smpso/SMPSO.h b/src/metaheuristics/smpso/SMPSO.h index 3fa67ec..c9734c5 100644 --- a/src/metaheuristics/smpso/SMPSO.h +++ b/src/metaheuristics/smpso/SMPSO.h @@ -2,6 +2,7 @@ // // Author: // Esteban López-Camacho +// Sérgio Vieira // // Copyright (c) 2011 Antonio J. Nebro, Juan J. Durillo // @@ -42,101 +43,102 @@ * (MCDM 2009), pp: 66-73. March 2009 */ -class SMPSO : public Algorithm { +class SMPSO : public Algorithm +{ private: - /** - * Stores the number of particles_ used - */ - int swarmSize_; - /** - * Stores the maximum size for the archive - */ - int archiveSize_; - /** - * Stores the maximum number of iteration_ - */ - int maxIterations_; - /** - * Stores the current number of iteration_ - */ - int iteration_; - /** - * Stores the particles - */ - SolutionSet * particles_; - /** - * Stores the best_ solutions founds so far for each particles - */ - Solution ** best_; - /** - * Stores the leaders_ - */ - CrowdingArchive * leaders_; - /** - * Stores the speed_ of each particle - */ - double ** speed_; - /** - * Stores a comparator for checking dominance - */ - Comparator * dominance_; - /** - * Stores a comparator for crowding checking - */ - Comparator * crowdingDistanceComparator_; - /** - * Stores a Distance object - */ - Distance * distance_; - /** - * Stores a operator for non uniform mutations - */ - Operator * polynomialMutation_; + /** + * Stores the number of particles_ used + */ + int swarmSize_; + /** + * Stores the maximum size for the archive + */ + int archiveSize_; + /** + * Stores the maximum number of iteration_ + */ + int maxIterations_; + /** + * Stores the current number of iteration_ + */ + int iteration_; + /** + * Stores the particles + */ + SolutionSet * particles_; + /** + * Stores the best_ solutions founds so far for each particles + */ + Solution ** best_; + /** + * Stores the leaders_ + */ + CrowdingArchive * leaders_; + /** + * Stores the speed_ of each particle + */ + double ** speed_; + /** + * Stores a comparator for checking dominance + */ + Comparator * dominance_; + /** + * Stores a comparator for crowding checking + */ + Comparator * crowdingDistanceComparator_; + /** + * Stores a Distance object + */ + Distance * distance_; + /** + * Stores a operator for non uniform mutations + */ + Operator * polynomialMutation_; - //QualityIndicator * indicators_; // QualityIndicator object + //QualityIndicator * indicators_; // QualityIndicator object - double r1Max_; - double r1Min_; - double r2Max_; - double r2Min_; - double C1Max_; - double C1Min_; - double C2Max_; - double C2Min_; - double WMax_; - double WMin_; - double ChVel1_; - double ChVel2_; + double r1Max_; + double r1Min_; + double r2Max_; + double r2Min_; + double C1Max_; + double C1Min_; + double C2Max_; + double C2Min_; + double WMax_; + double WMin_; + double ChVel1_; + double ChVel2_; - double trueHypervolume_; - //Hypervolume * hy_; - SolutionSet * trueFront_; - double * deltaMax_; - double * deltaMin_; - bool success_; + double trueHypervolume_; + //Hypervolume * hy_; + SolutionSet * trueFront_; + double * deltaMax_; + double * deltaMin_; + bool success_; - double inertiaWeight(int iter, int miter, double wma, - double wmin); - double constrictionCoefficient(double c1, double c2); - double velocityConstriction(double v, double * deltaMax, - double * deltaMin, - int variableIndex, - int particleIndex); - void computeSpeed(int iter, int miter); - void computeNewPositions(); - void mopsoMutation(int actualIteration, int totalIterations); - void initParams(); - void setAlgParams(); - void deleteParams(); + double inertiaWeight(int iter, int miter, double wma, + double wmin); + double constrictionCoefficient(double c1, double c2); + double velocityConstriction(double v, double * deltaMax, + double * deltaMin, + int variableIndex, + int particleIndex); + void computeSpeed(int iter, int miter); + void computeNewPositions(); + void mopsoMutation(int actualIteration, int totalIterations); + void initParams(); + void setAlgParams(); + void deleteParams(); public: - SMPSO(Problem * problem); - //TODO: SMPSO(Problem * problem, vector variables, string trueParetoFront); - //TODO: SMPSO(Problem * problem, string trueParetoFront); - SolutionSet * execute(); - //TODO: SolutionSet * getLeader(); + SMPSO(Problem * problem); + //TODO: SMPSO(Problem * problem, VectorOfDouble variables, std::string trueParetoFront); + //TODO: SMPSO(Problem * problem, std::string trueParetoFront); + SolutionSet * execute(); + //TODO: SolutionSet * getLeader(); }; diff --git a/src/metaheuristics/smpso/SMPSOhv.cpp b/src/metaheuristics/smpso/SMPSOhv.cpp index dcc9765..323d5f2 100644 --- a/src/metaheuristics/smpso/SMPSOhv.cpp +++ b/src/metaheuristics/smpso/SMPSOhv.cpp @@ -2,6 +2,7 @@ // // Author: // Esteban López-Camacho +// Sérgio Vieira // // Copyright (c) 2014 Antonio J. Nebro // @@ -31,78 +32,84 @@ * Constructor * @param problem Problem to solve */ -SMPSOhv::SMPSOhv(Problem *problem) : Algorithm(problem) { - r1Max = 1.0; - r1Min = 0.0; - r2Max = 1.0; - r2Min = 0.0; - C1Max = 2.5; - C1Min = 1.5; - C2Max = 2.5; - C2Min = 1.5; - WMax = 0.1; - WMin = 0.1; - ChVel1 = -1; - ChVel2 = -1; +SMPSOhv::SMPSOhv(Problem *problem) : Algorithm(problem) +{ + r1Max = 1.0; + r1Min = 0.0; + r2Max = 1.0; + r2Min = 0.0; + C1Max = 2.5; + C1Min = 1.5; + C2Max = 2.5; + C2Min = 1.5; + WMax = 0.1; + WMin = 0.1; + ChVel1 = -1; + ChVel2 = -1; } // SMPSOhv /** * Initialize all parameter of the algorithm */ -void SMPSOhv::initParams() { - swarmSize = *(int *) getInputParameter("swarmSize"); - archiveSize = *(int *) getInputParameter("archiveSize"); - maxIterations = *(int *) getInputParameter("maxIterations"); - - //indicators = *(QualityIndicator *) getInputParameter("indicators"); - - polynomialMutation = operators_["mutation"] ; - - iteration = 0; - - particles = new SolutionSet(swarmSize); - best = new Solution*[swarmSize]; - leaders = new FastHypervolumeArchive(archiveSize,problem_->getNumberOfObjectives()); - - // Create the dominator for equadless and dominance - dominance = new DominanceComparator(); - crowdingDistanceComparator = new CrowdingDistanceComparator(); - distance = new Distance(); - - // Create the speed_ vector - speed = new double*[swarmSize]; - - deltaMax = new double[problem_->getNumberOfVariables()]; - deltaMin = new double[problem_->getNumberOfVariables()]; - for (int i = 0; i < problem_->getNumberOfVariables(); i++) { - deltaMax[i] = (problem_->getUpperLimit(i) - - problem_->getLowerLimit(i)) / 2.0; - deltaMin[i] = -deltaMax[i]; - } // for +void SMPSOhv::initParams() +{ + swarmSize = *(int *) getInputParameter("swarmSize"); + archiveSize = *(int *) getInputParameter("archiveSize"); + maxIterations = *(int *) getInputParameter("maxIterations"); + + //indicators = *(QualityIndicator *) getInputParameter("indicators"); + + polynomialMutation = operators_["mutation"] ; + + iteration = 0; + + particles = new SolutionSet(swarmSize); + best = new Solution*[swarmSize]; + leaders = new FastHypervolumeArchive(archiveSize,problem_->getNumberOfObjectives()); + + // Create the dominator for equadless and dominance + dominance = new DominanceComparator(); + crowdingDistanceComparator = new CrowdingDistanceComparator(); + distance = new Distance(); + + // Create the speed_ vector + speed = snew double*[swarmSize]; + + deltaMax = snew double[problem_->getNumberOfVariables()]; + deltaMin = snew double[problem_->getNumberOfVariables()]; + for (int i = 0; i < problem_->getNumberOfVariables(); i++) + { + deltaMax[i] = (problem_->getUpperLimit(i) - + problem_->getLowerLimit(i)) / 2.0; + deltaMin[i] = -deltaMax[i]; + } // for } // initParams /** * Free all the memory reserved by the algorithm */ -void SMPSOhv::deleteParams() { - - for (int i = 0; i < swarmSize; i++) { - delete [] speed[i]; - } - delete [] speed; - delete dominance; - delete crowdingDistanceComparator; - delete distance; - delete particles; - for (int i = 0; i < swarmSize; i++) { - delete best[i]; - } - delete [] best; - delete [] deltaMax; - delete [] deltaMin; - delete leaders; +void SMPSOhv::deleteParams() +{ + + for (int i = 0; i < swarmSize; i++) + { + delete [] speed[i]; + } + delete [] speed; + delete dominance; + delete crowdingDistanceComparator; + delete distance; + delete particles; + for (int i = 0; i < swarmSize; i++) + { + delete best[i]; + } + delete [] best; + delete [] deltaMax; + delete [] deltaMin; + delete leaders; } // deleteParams @@ -110,128 +117,147 @@ void SMPSOhv::deleteParams() { /** * Adaptive inertia */ -double SMPSOhv::inertiaWeight(int iter, int miter, double wma, double wmin) { - return wma; // - (((wma-wmin)*(double)iter)/(double)miter); +double SMPSOhv::inertiaWeight(int iter, int miter, double wma, double wmin) +{ + return wma; // - (((wma-wmin)*(double)iter)/(double)miter); } // inertiaWeight /** * constriction coefficient (M. Clerc) */ -double SMPSOhv::constrictionCoefficient(double c1, double c2) { - double rho = c1 + c2; - //rho = 1.0 ; - if (rho <= 4) { - return 1.0; - } else { - return 2 / (2 - rho - sqrt(pow(rho, 2.0) - 4.0 * rho)); - } +double SMPSOhv::constrictionCoefficient(double c1, double c2) +{ + double rho = c1 + c2; + //rho = 1.0 ; + if (rho <= 4) + { + return 1.0; + } + else + { + return 2 / (2 - rho - sqrt(pow(rho, 2.0) - 4.0 * rho)); + } } // constrictionCoefficient /** * velocity bounds */ double SMPSOhv::velocityConstriction(double v, double *deltaMax, - double *deltaMin, int variableIndex, - int particleIndex) { + double *deltaMin, int variableIndex, + int particleIndex) +{ - double result; + double result; - double dmax = deltaMax[variableIndex]; - double dmin = deltaMin[variableIndex]; + double dmax = deltaMax[variableIndex]; + double dmin = deltaMin[variableIndex]; - result = v; + result = v; - if (v > dmax) { - result = dmax; - } + if (v > dmax) + { + result = dmax; + } - if (v < dmin) { - result = dmin; - } + if (v < dmin) + { + result = dmin; + } - return result; + return result; } // velocityConstriction /** * Update the speed of each particle */ -void SMPSOhv::computeSpeed(int iter, int miter) { - double r1, r2, W, C1, C2; - double wmax, wmin; - XReal *bestGlobal; - - for (int i = 0; i < swarmSize; i++) { - XReal *particle = new XReal(particles->get(i)); - XReal *bestParticle = new XReal(best[i]); - - //Select a global best for calculate the speed of particle i, bestGlobal - Solution *one, *two; - int pos1 = PseudoRandom::randInt(0,leaders->size()-1); - - //int pos1 = PseudoRandom::randInt(0,leaders->size()-1); - int pos2 = PseudoRandom::randInt(0,leaders->size()-1); - one = leaders->get(pos1); - two = leaders->get(pos2); - - if (crowdingDistanceComparator->compare(one,two) < 1) { - bestGlobal = new XReal(one); - } else { - bestGlobal = new XReal(two); - } - - //Params for velocity equation - r1 = PseudoRandom::randDouble(r1Min, r1Max); - r2 = PseudoRandom::randDouble(r2Min, r2Max); - C1 = PseudoRandom::randDouble(C1Min, C1Max); - C2 = PseudoRandom::randDouble(C2Min, C2Max); - W = PseudoRandom::randDouble(WMin, WMax); - - wmax = WMax; - wmin = WMin; - - for (int var = 0; var < particle->getNumberOfDecisionVariables(); var++) { - //Computing the velocity of this particle - speed[i][var] = velocityConstriction(constrictionCoefficient(C1, C2) * - (inertiaWeight(iter, miter, wmax, wmin) * - speed[i][var] + - C1 * r1 * (bestParticle->getValue(var) - - particle->getValue(var)) + - C2 * r2 * (bestGlobal->getValue(var) - - particle->getValue(var))), deltaMax, - deltaMin, - var, - i); +void SMPSOhv::computeSpeed(int iter, int miter) +{ + double r1, r2, W, C1, C2; + double wmax, wmin; + XReal *bestGlobal; + + for (int i = 0; i < swarmSize; i++) + { + XReal *particle = new XReal(particles->get(i)); + XReal *bestParticle = new XReal(best[i]); + + //Select a global best for calculate the speed of particle i, bestGlobal + Solution *one, *two; + int pos1 = PseudoRandom::randInt(0,leaders->size()-1); + + //int pos1 = PseudoRandom::randInt(0,leaders->size()-1); + int pos2 = PseudoRandom::randInt(0,leaders->size()-1); + one = leaders->get(pos1); + two = leaders->get(pos2); + + if (crowdingDistanceComparator->compare(one,two) < 1) + { + bestGlobal = new XReal(one); + } + else + { + bestGlobal = new XReal(two); + } + + //Params for velocity equation + r1 = PseudoRandom::randDouble(r1Min, r1Max); + r2 = PseudoRandom::randDouble(r2Min, r2Max); + C1 = PseudoRandom::randDouble(C1Min, C1Max); + C2 = PseudoRandom::randDouble(C2Min, C2Max); + W = PseudoRandom::randDouble(WMin, WMax); + + wmax = WMax; + wmin = WMin; + + for (int var = 0; var < particle->getNumberOfDecisionVariables(); var++) + { + //Computing the velocity of this particle + speed[i][var] = velocityConstriction(constrictionCoefficient(C1, C2) * + (inertiaWeight(iter, miter, wmax, wmin) * + speed[i][var] + + C1 * r1 * (bestParticle->getValue(var) - + particle->getValue(var)) + + C2 * r2 * (bestGlobal->getValue(var) - + particle->getValue(var))), deltaMax, + deltaMin, + var, + i); + } + delete bestGlobal; + delete particle; + delete bestParticle; } - delete bestGlobal; - delete particle; - delete bestParticle; - } } // computeSpeed /** * Update the position of each particle */ -void SMPSOhv::computeNewPositions() { - - for (int i = 0; i < swarmSize; i++) { - XReal * particle = new XReal(particles->get(i)); - for (int var = 0; var < particle->getNumberOfDecisionVariables(); var++) { - particle->setValue(var, particle->getValue(var) + speed[i][var]); - - if (particle->getValue(var) < problem_->getLowerLimit(var)) { - particle->setValue(var, problem_->getLowerLimit(var)); - speed[i][var] = speed[i][var] * ChVel1; - } - if (particle->getValue(var) > problem_->getUpperLimit(var)){ - particle->setValue(var, problem_->getUpperLimit(var)); - speed[i][var] = speed[i][var] * ChVel2; - } +void SMPSOhv::computeNewPositions() +{ + + for (int i = 0; i < swarmSize; i++) + { + XReal * particle = new XReal(particles->get(i)); + for (int var = 0; var < particle->getNumberOfDecisionVariables(); var++) + { + particle->setValue(var, particle->getValue(var) + speed[i][var]); + + if (particle->getValue(var) < problem_->getLowerLimit(var)) + { + particle->setValue(var, problem_->getLowerLimit(var)); + speed[i][var] = speed[i][var] * ChVel1; + } + if (particle->getValue(var) > problem_->getUpperLimit(var)) + { + particle->setValue(var, problem_->getUpperLimit(var)); + speed[i][var] = speed[i][var] * ChVel2; + } + } + delete particle; } - delete particle; - } } // computeNewPositions @@ -239,12 +265,15 @@ void SMPSOhv::computeNewPositions() { /** * Apply a mutation operator to some particles in the swarm */ -void SMPSOhv::mopsoMutation(int actualIteration, int totalIterations) { - for (int i = 0; i < particles->size(); i++) { - if ( (i % 6) == 0) { - polynomialMutation->execute(particles->get(i)); +void SMPSOhv::mopsoMutation(int actualIteration, int totalIterations) +{ + for (int i = 0; i < particles->size(); i++) + { + if ( (i % 6) == 0) + { + polynomialMutation->execute(particles->get(i)); + } } - } } // mopsoMutation @@ -253,92 +282,106 @@ void SMPSOhv::mopsoMutation(int actualIteration, int totalIterations) { * @return a SolutionSet that is a set of non dominated solutions * as a result of the algorithm execution */ -SolutionSet *SMPSOhv::execute() { - - initParams(); - - success = false; - //->Step 1 (and 3) Create the initial population and evaluate - for (int i = 0; i < swarmSize; i++){ - Solution *particle = new Solution(problem_); - problem_->evaluate(particle); - problem_->evaluateConstraints(particle); - particles->add(particle); - } - - //-> Step2. Initialize the speed of each particle to 0 - for (int i = 0; i < swarmSize; i++) { - speed[i] = new double[problem_->getNumberOfVariables()]; - for (int j = 0; j < problem_->getNumberOfVariables(); j++) { - speed[i][j] = 0.0; +SolutionSet *SMPSOhv::execute() +{ + + initParams(); + + success = false; + //->Step 1 (and 3) Create the initial population and evaluate + for (int i = 0; i < swarmSize; i++) + { + Solution *particle = new Solution(problem_); + problem_->evaluate(particle); + problem_->evaluateConstraints(particle); + particles->add(particle); } - } - // Step4 and 5 - for (int i = 0; i < particles->size(); i++){ - Solution *particle = new Solution(particles->get(i)); - if (leaders->add(particle) == false){ - delete particle; - } - } - - //-> Step 6. Initialize the memory of each particle - for (int i = 0; i < particles->size(); i++){ - Solution *particle = new Solution(particles->get(i)); - best[i] = particle; - } - - //Crowding the leaders_ - //distance->crowdingDistanceAssignment(leaders, problem_->getNumberOfObjectives()); - leaders->computeHVContribution(); - - //-> Step 7. Iterations .. - while (iteration < maxIterations) { - //Compute the speed_ - computeSpeed(iteration, maxIterations); - - //Compute the new positions for the particles_ - computeNewPositions(); - - //Mutate the particles_ - mopsoMutation(iteration,maxIterations); - - //Evaluate the new particles in new positions - for (int i = 0; i < particles->size(); i++){ - Solution *particle = particles->get(i); - problem_->evaluate(particle); - problem_->evaluateConstraints(particle); + //-> Step2. Initialize the speed of each particle to 0 + for (int i = 0; i < swarmSize; i++) + { + speed[i] = snew double[problem_->getNumberOfVariables()]; + for (int j = 0; j < problem_->getNumberOfVariables(); j++) + { + speed[i][j] = 0.0; + } } - //Update the archive - for (int i = 0; i < particles->size(); i++) { - Solution *particle = new Solution(particles->get(i)); - if (leaders->add(particle) == false) { - delete particle; - } + // Step4 and 5 + for (int i = 0; i < particles->size(); i++) + { + Solution *particle = new Solution(particles->get(i)); + if (leaders->add(particle) == false) + { + delete particle; + } } - //Update the memory of this particle - for (int i = 0; i < particles->size(); i++) { - int flag = dominance->compare(particles->get(i), best[i]); - if (flag != 1) { // the new particle is best_ than the older remembered + //-> Step 6. Initialize the memory of each particle + for (int i = 0; i < particles->size(); i++) + { Solution *particle = new Solution(particles->get(i)); - delete best[i]; best[i] = particle; - } } - iteration++; - } + //Crowding the leaders_ + //distance->crowdingDistanceAssignment(leaders, problem_->getNumberOfObjectives()); + leaders->computeHVContribution(); + + //-> Step 7. Iterations .. + while (iteration < maxIterations) + { + //Compute the speed_ + computeSpeed(iteration, maxIterations); + + //Compute the new positions for the particles_ + computeNewPositions(); + + //Mutate the particles_ + mopsoMutation(iteration,maxIterations); + + //Evaluate the new particles in new positions + for (int i = 0; i < particles->size(); i++) + { + Solution *particle = particles->get(i); + problem_->evaluate(particle); + problem_->evaluateConstraints(particle); + } + + //Update the archive + for (int i = 0; i < particles->size(); i++) + { + Solution *particle = new Solution(particles->get(i)); + if (leaders->add(particle) == false) + { + delete particle; + } + } + + //Update the memory of this particle + for (int i = 0; i < particles->size(); i++) + { + int flag = dominance->compare(particles->get(i), best[i]); + if (flag != 1) // the new particle is best_ than the older remembered + { + Solution *particle = new Solution(particles->get(i)); + delete best[i]; + best[i] = particle; + } + } + + iteration++; + } - // Build the solution set result - SolutionSet * result = new SolutionSet(leaders->size()); - for (int i=0;isize();i++) { - result->add(new Solution(leaders->get(i))); - } + // Build the solution set result + SolutionSet * result = new SolutionSet(leaders->size()); + for (int i=0; isize(); i++) + { + result->add(new Solution(leaders->get(i))); + } - // Free memory - deleteParams(); + // Free memory + deleteParams(); - return result; + return result; } // execute diff --git a/src/metaheuristics/smpso/SMPSOhv.h b/src/metaheuristics/smpso/SMPSOhv.h index d863350..a71882f 100644 --- a/src/metaheuristics/smpso/SMPSOhv.h +++ b/src/metaheuristics/smpso/SMPSOhv.h @@ -2,6 +2,7 @@ // // Author: // Esteban López-Camacho +// Sérgio Vieira // // Copyright (c) 2014 Antonio J. Nebro // @@ -35,149 +36,150 @@ * A.J Nebro, J.J. Durillo, C.A. Coello Coello. Analysis of Leader Selection Strategies in a * Multi-Objective Particle Swarm Optimizer. 2013 IEEE Congress on Evolutionary Computation. June 2013 */ -class SMPSOhv : public Algorithm { +class SMPSOhv : public Algorithm +{ private: - /** - * Stores the number of particles used - */ - int swarmSize; - - /** - * Stores the maximum size for the archive - */ - int archiveSize; - - /** - * Stores the maximum number of iteration_ - */ - int maxIterations; - - /** - * Stores the current number of iteration_ - */ - int iteration; - - /** - * Stores the particles - */ - SolutionSet *particles; - - /** - * Stores the best solutions founds so far for each particles - */ - Solution **best; - - /** - * Stores the leaders - */ - FastHypervolumeArchive *leaders; - - /** - * Stores the speed of each particle - */ - double **speed; - - /** - * Stores a comparator for checking dominance - */ - Comparator *dominance; - - /** - * Stores a comparator for crowding checking - */ - Comparator *crowdingDistanceComparator; - - /** - * Stores a Distance object - */ - Distance *distance; - - /** - * Stores a operator for polynomial mutations - */ - Operator *polynomialMutation; - - //QualityIndicator *indicators; // QualityIndicator object - - double r1Max; - double r1Min; - double r2Max; - double r2Min; - double C1Max; - double C1Min; - double C2Max; - double C2Min; - double WMax; - double WMin; - double ChVel1; - double ChVel2; - - double trueHypervolume; - Hypervolume *hy; - SolutionSet *trueFront; - double *deltaMax; - double *deltaMin; - bool success; - - /** - * Initialize all parameter of the algorithm - */ - void initParams(); - - /** - * Free all the memory reserved by the algorithm - */ - void deleteParams(); - - /** - * Adaptive inertia - */ - double inertiaWeight(int iter, int miter, double wma, double wmin); - - /** - * constriction coefficient (M. Clerc) - */ - double constrictionCoefficient(double c1, double c2); - - /** - * velocity bounds - */ - double velocityConstriction(double v, double *deltaMax, - double *deltaMin, int variableIndex, - int particleIndex); - - /** - * Update the speed of each particle - */ - void computeSpeed(int iter, int miter); - - /** - * Update the position of each particle - */ - void computeNewPositions(); - - /** - * Apply a mutation operator to some particles in the swarm - */ - void mopsoMutation(int actualIteration, int totalIterations); + /** + * Stores the number of particles used + */ + int swarmSize; + + /** + * Stores the maximum size for the archive + */ + int archiveSize; + + /** + * Stores the maximum number of iteration_ + */ + int maxIterations; + + /** + * Stores the current number of iteration_ + */ + int iteration; + + /** + * Stores the particles + */ + SolutionSet *particles; + + /** + * Stores the best solutions founds so far for each particles + */ + Solution **best; + + /** + * Stores the leaders + */ + FastHypervolumeArchive *leaders; + + /** + * Stores the speed of each particle + */ + double **speed; + + /** + * Stores a comparator for checking dominance + */ + Comparator *dominance; + + /** + * Stores a comparator for crowding checking + */ + Comparator *crowdingDistanceComparator; + + /** + * Stores a Distance object + */ + Distance *distance; + + /** + * Stores a operator for polynomial mutations + */ + Operator *polynomialMutation; + + //QualityIndicator *indicators; // QualityIndicator object + + double r1Max; + double r1Min; + double r2Max; + double r2Min; + double C1Max; + double C1Min; + double C2Max; + double C2Min; + double WMax; + double WMin; + double ChVel1; + double ChVel2; + + double trueHypervolume; + Hypervolume *hy; + SolutionSet *trueFront; + double *deltaMax; + double *deltaMin; + bool success; + + /** + * Initialize all parameter of the algorithm + */ + void initParams(); + + /** + * Free all the memory reserved by the algorithm + */ + void deleteParams(); + + /** + * Adaptive inertia + */ + double inertiaWeight(int iter, int miter, double wma, double wmin); + + /** + * constriction coefficient (M. Clerc) + */ + double constrictionCoefficient(double c1, double c2); + + /** + * velocity bounds + */ + double velocityConstriction(double v, double *deltaMax, + double *deltaMin, int variableIndex, + int particleIndex); + + /** + * Update the speed of each particle + */ + void computeSpeed(int iter, int miter); + + /** + * Update the position of each particle + */ + void computeNewPositions(); + + /** + * Apply a mutation operator to some particles in the swarm + */ + void mopsoMutation(int actualIteration, int totalIterations); public: - /** - * Constructor. - * @param problem Problem to solve - */ - SMPSOhv(Problem *problem); - - /** - * Runs of the SMPSO algorithm. - * @return a SolutionSet that is a set of non dominated solutions - * as a result of the algorithm execution - * @throws JMException - */ - SolutionSet *execute(); + /** + * Constructor. + * @param problem Problem to solve + */ + SMPSOhv(Problem *problem); + + /** + * Runs of the SMPSO algorithm. + * @return a SolutionSet that is a set of non dominated solutions + * as a result of the algorithm execution + * @throws JMException + */ + SolutionSet *execute(); }; diff --git a/src/metaheuristics/smsemoa/CMakeLists.txt b/src/metaheuristics/smsemoa/CMakeLists.txt new file mode 100644 index 0000000..294ec59 --- /dev/null +++ b/src/metaheuristics/smsemoa/CMakeLists.txt @@ -0,0 +1,3 @@ +file(GLOB SOURCES "*.cpp" "*.h") +ListToString(SOURCES ";" ${SOURCES}) +LIST_APPEND("${SOURCES}") \ No newline at end of file diff --git a/src/metaheuristics/smsemoa/FastSMSEMOA.cpp b/src/metaheuristics/smsemoa/FastSMSEMOA.cpp index fd302db..a6b1700 100644 --- a/src/metaheuristics/smsemoa/FastSMSEMOA.cpp +++ b/src/metaheuristics/smsemoa/FastSMSEMOA.cpp @@ -2,6 +2,7 @@ // // Author: // Esteban López-Camacho +// Sérgio Vieira // // Copyright (c) 2014 Antonio J. Nebro // @@ -31,17 +32,19 @@ * Constructor * @param problem Problem to solve */ -FastSMSEMOA::FastSMSEMOA(Problem *problem) : Algorithm(problem) { - utils_ = new MetricsUtil(); - hv_ = new Hypervolume(); +FastSMSEMOA::FastSMSEMOA(Problem *problem) : Algorithm(problem) +{ + utils_ = snew MetricsUtil(); + hv_ = snew Hypervolume(); } // FastSMSEMOA /** * Destructor */ -FastSMSEMOA::~FastSMSEMOA() { - delete utils_; - delete hv_; +FastSMSEMOA::~FastSMSEMOA() +{ + delete utils_; + delete hv_; } // ~FastSMSEMOA /** @@ -49,164 +52,173 @@ FastSMSEMOA::~FastSMSEMOA() { * @return a SolutionSet that is a set of non dominated solutions * as a result of the algorithm execution */ -SolutionSet * FastSMSEMOA::execute() { - int populationSize; - int maxEvaluations; - int evaluations; - double offset; - - QualityIndicator * indicators; // QualityIndicator object - int requiredEvaluations; // Use in the example of use of the indicators object (see below) - - FastHypervolume * fastHypervolume; - - SolutionSet * population; - SolutionSet * offspringPopulation; - SolutionSet * unionSolution; - - Operator * mutationOperator; - Operator * crossoverOperator; - Operator * selectionOperator; - - //Read the parameters - populationSize = *(int *) getInputParameter("populationSize"); - maxEvaluations = *(int *) getInputParameter("maxEvaluations"); - indicators = (QualityIndicator *) getInputParameter("indicators"); - offset = *(double *) getInputParameter("offset"); - - //Initialize the variables - population = new SolutionSet(populationSize); - evaluations = 0; - - requiredEvaluations = 0; - - fastHypervolume = new FastHypervolume(offset); - - //Read the operator - mutationOperator = operators_["mutation"]; - crossoverOperator = operators_["crossover"]; - selectionOperator = operators_["selection"]; - - // Create the initial solutionSet - Solution * newSolution; - for (int i = 0; i < populationSize; i++) { - newSolution = new Solution(problem_); - problem_->evaluate(newSolution); - problem_->evaluateConstraints(newSolution); - evaluations++; - population->add(newSolution); - } //for - - // Generations ... - while (evaluations < maxEvaluations) { - - // select parents - offspringPopulation = new SolutionSet(1); - /* - LinkedList selectedParents = new LinkedList(); - Solution[] parents = new Solution[0]; - while (selectedParents->size() < 2) { - void * selected = selectionOperator->execute(population); - try { - Solution * parent = * (Solution*) selected; - selectedParents.add(parent); - } catch (ClassCastException e) { - Configuration.logger_.log(Level.WARNING, "Class cast exception", e); - parents = (Solution[]) selected; - Collections.addAll(selectedParents, parents); - } +SolutionSet * FastSMSEMOA::execute() +{ + int populationSize; + int maxEvaluations; + int evaluations; + double offset; + + QualityIndicator * indicators; // QualityIndicator object + int requiredEvaluations; // Use in the example of use of the indicators object (see below) + + FastHypervolume * fastHypervolume; + + SolutionSet * population; + SolutionSet * offspringPopulation; + SolutionSet * unionSolution; + + Operator * mutationOperator; + Operator * crossoverOperator; + Operator * selectionOperator; + + //Read the parameters + populationSize = *(int *) getInputParameter("populationSize"); + maxEvaluations = *(int *) getInputParameter("maxEvaluations"); + indicators = (QualityIndicator *) getInputParameter("indicators"); + offset = *(double *) getInputParameter("offset"); + + //Initialize the variables + population = snew SolutionSet(populationSize); + evaluations = 0; + + requiredEvaluations = 0; + + fastHypervolume = snew FastHypervolume(offset); + + //Read the operator + mutationOperator = operators_["mutation"]; + crossoverOperator = operators_["crossover"]; + selectionOperator = operators_["selection"]; + + // Create the initial solutionSet + Solution * newSolution; + for (int i = 0; i < populationSize; i++) + { + newSolution = snew Solution(problem_); + problem_->evaluate(newSolution); + problem_->evaluateConstraints(newSolution); + evaluations++; + population->add(newSolution); + } //for + + // Generations ... + while (evaluations < maxEvaluations) + { + + // select parents + offspringPopulation = snew SolutionSet(1); + /* + LinkedList selectedParents = new LinkedList(); + Solution[] parents = new Solution[0]; + while (selectedParents->size() < 2) { + void * selected = selectionOperator->execute(population); + try { + Solution * parent = * (Solution*) selected; + selectedParents.add(parent); + } catch (ClassCastException e) { + Configuration.logger_.log(Level.WARNING, "Class cast exception", e); + parents = (Solution[]) selected; + Collections.addAll(selectedParents, parents); + } + } + parents = selectedParents.toArray(parents); + */ + Solution ** parents = (Solution **) (selectionOperator->execute(population)); + + // crossover + Solution ** offSpring = (Solution **) (crossoverOperator->execute(parents)); + + // mutation + mutationOperator->execute(offSpring[0]); + + // evaluation + problem_->evaluate(offSpring[0]); + problem_->evaluateConstraints(offSpring[0]); + + // insert child into the offspring population + offspringPopulation->add(offSpring[0]); + + evaluations++; + + delete offSpring[1]; + delete[] offSpring; + delete[] parents; + + // Create the solutionSet union of solutionSet and offSpring + unionSolution = population->join(offspringPopulation); + delete offspringPopulation; + + // Ranking the union (non-dominated sorting) + Ranking * ranking = snew Ranking(unionSolution); + + // ensure crowding distance values are up to date + // (may be important for parent selection) + for (int j = 0; j < population->size(); j++) + { + population->get(j)->setCrowdingDistance(0.0); + } + + SolutionSet * lastFront = ranking->getSubfront(ranking->getNumberOfSubfronts() - 1); + + //FastHypervolume fastHypervolume = new FastHypervolume() ; + fastHypervolume->computeHVContributions(lastFront); + CrowdingDistanceComparator * cd = snew CrowdingDistanceComparator(); + lastFront->sort(cd); + delete cd; + + // all but the worst are carried over to the survivor population + SolutionSet * front = nullptr; + for (int i=0; isize(); i++) + { + delete population->get(i); + } + population->clear(); + for (int i = 0; i < ranking->getNumberOfSubfronts() - 1; i++) + { + front = ranking->getSubfront(i); + for (int j = 0; j < front->size(); j++) + { + population->add(snew Solution(front->get(j))); + } + } + for (int i = 0; i < lastFront->size() - 1; i++) + { + population->add(snew Solution(lastFront->get(i))); + } + + delete unionSolution; + delete ranking; + + // This piece of code shows how to use the indicator object into the code + // of SMS-EMOA. In particular, it finds the number of evaluations required + // by the algorithm to obtain a Pareto front with a hypervolume higher + // than the hypervolume of the true Pareto front. + /* + if (indicators != null && requiredEvaluations == 0) { + double HV = indicators.getHypervolume(population); + if (HV >= (0.98 * indicators.getTrueParetoFrontHypervolume())) { + requiredEvaluations = evaluations; + } + } + */ } - parents = selectedParents.toArray(parents); - */ - Solution ** parents = (Solution **) (selectionOperator->execute(population)); - // crossover - Solution ** offSpring = (Solution **) (crossoverOperator->execute(parents)); + // Return as output parameter the required evaluations + //setOutputParameter("evaluations", requiredEvaluations); - // mutation - mutationOperator->execute(offSpring[0]); + // Return the first non-dominated front + Ranking * ranking = snew Ranking(population); - // evaluation - problem_->evaluate(offSpring[0]); - problem_->evaluateConstraints(offSpring[0]); - - // insert child into the offspring population - offspringPopulation->add(offSpring[0]); - - evaluations++; - - delete offSpring[1]; - delete[] offSpring; - delete[] parents; - - // Create the solutionSet union of solutionSet and offSpring - unionSolution = population->join(offspringPopulation); - delete offspringPopulation; - - // Ranking the union (non-dominated sorting) - Ranking * ranking = new Ranking(unionSolution); - - // ensure crowding distance values are up to date - // (may be important for parent selection) - for (int j = 0; j < population->size(); j++) { - population->get(j)->setCrowdingDistance(0.0); - } - - SolutionSet * lastFront = ranking->getSubfront(ranking->getNumberOfSubfronts() - 1); - - //FastHypervolume fastHypervolume = new FastHypervolume() ; - fastHypervolume->computeHVContributions(lastFront); - CrowdingDistanceComparator * cd = new CrowdingDistanceComparator(); - lastFront->sort(cd); - delete cd; - - // all but the worst are carried over to the survivor population - SolutionSet * front = NULL; - for (int i=0;isize();i++) { - delete population->get(i); - } - population->clear(); - for (int i = 0; i < ranking->getNumberOfSubfronts() - 1; i++) { - front = ranking->getSubfront(i); - for (int j = 0; j < front->size(); j++) { - population->add(new Solution(front->get(j))); - } - } - for (int i = 0; i < lastFront->size() - 1; i++) { - population->add(new Solution(lastFront->get(i))); + SolutionSet * result = snew SolutionSet(ranking->getSubfront(0)->size()); + for (int i=0; igetSubfront(0)->size(); i++) + { + result->add(snew Solution(ranking->getSubfront(0)->get(i))); } - - delete unionSolution; delete ranking; + delete population; + delete fastHypervolume; - // This piece of code shows how to use the indicator object into the code - // of SMS-EMOA. In particular, it finds the number of evaluations required - // by the algorithm to obtain a Pareto front with a hypervolume higher - // than the hypervolume of the true Pareto front. - /* - if (indicators != null && requiredEvaluations == 0) { - double HV = indicators.getHypervolume(population); - if (HV >= (0.98 * indicators.getTrueParetoFrontHypervolume())) { - requiredEvaluations = evaluations; - } - } - */ - } - - // Return as output parameter the required evaluations - //setOutputParameter("evaluations", requiredEvaluations); - - // Return the first non-dominated front - Ranking * ranking = new Ranking(population); - - SolutionSet * result = new SolutionSet(ranking->getSubfront(0)->size()); - for (int i=0;igetSubfront(0)->size();i++) { - result->add(new Solution(ranking->getSubfront(0)->get(i))); - } - delete ranking; - delete population; - delete fastHypervolume; - - return result; + return result; } diff --git a/src/metaheuristics/smsemoa/FastSMSEMOA.h b/src/metaheuristics/smsemoa/FastSMSEMOA.h index b5f43a8..cd14931 100644 --- a/src/metaheuristics/smsemoa/FastSMSEMOA.h +++ b/src/metaheuristics/smsemoa/FastSMSEMOA.h @@ -2,6 +2,7 @@ // // Author: // Esteban López-Camacho +// Sérgio Vieira // // Copyright (c) 2014 Antonio J. Nebro // @@ -22,6 +23,7 @@ #ifndef _FAST_SMSEMOA_H_ #define _FAST_SMSEMOA_H_ +#include "JMetalHeader.h" #include #include #include @@ -31,20 +33,18 @@ #include #include -class FastSMSEMOA : public Algorithm { - -private: - - MetricsUtil * utils_; - Hypervolume * hv_; - - vector hvContributions(vector< vector > front); - +using namespace JMetal; +class FastSMSEMOA : public Algorithm +{ +protected: + MetricsUtil * utils_ = nullptr; + Hypervolume * hv_ = nullptr; + VectorOfDouble hvContributions(MatrixOfDouble front); public: - FastSMSEMOA(Problem * problem); - ~FastSMSEMOA(); - SolutionSet * execute(); + FastSMSEMOA(Problem * problem); + ~FastSMSEMOA(); + SolutionSet * execute(); }; diff --git a/src/metaheuristics/smsemoa/SMSEMOA.cpp b/src/metaheuristics/smsemoa/SMSEMOA.cpp index 9b16c09..486c4af 100644 --- a/src/metaheuristics/smsemoa/SMSEMOA.cpp +++ b/src/metaheuristics/smsemoa/SMSEMOA.cpp @@ -30,17 +30,19 @@ * Constructor * @param problem Problem to solve */ -SMSEMOA::SMSEMOA(Problem *problem) : Algorithm(problem) { - utils_ = new MetricsUtil(); - hv_ = new Hypervolume(); +SMSEMOA::SMSEMOA(Problem *problem) : Algorithm(problem) +{ + utils_ = new MetricsUtil(); + hv_ = new Hypervolume(); } // SMSEMOA /** * Destructor */ -SMSEMOA::~SMSEMOA() { - delete utils_; - delete hv_; +SMSEMOA::~SMSEMOA() +{ + delete utils_; + delete hv_; } // ~SMSEMOA @@ -49,240 +51,261 @@ SMSEMOA::~SMSEMOA() { * @return a SolutionSet that is a set of non dominated solutions * as a result of the algorithm execution */ -SolutionSet * SMSEMOA::execute() { - int populationSize; - int maxEvaluations; - int evaluations; - double offset = 100.0; - - QualityIndicator * indicators; // QualityIndicator object - int requiredEvaluations; // Use in the example of use of the indicators object (see below) - - SolutionSet * population; - SolutionSet * offspringPopulation; - SolutionSet * unionSolution; - - Operator * mutationOperator; - Operator * crossoverOperator; - Operator * selectionOperator; - - //Read the parameters - populationSize = *(int *) getInputParameter("populationSize"); - maxEvaluations = *(int *) getInputParameter("maxEvaluations"); - offset = *(double *) getInputParameter("offset"); - - //indicators = (QualityIndicator*) getInputParameter("indicators"); - - //Initialize the variables - population = new SolutionSet(populationSize); - evaluations = 0; - - requiredEvaluations = 0; - - //Read the operators - crossoverOperator = operators_["crossover"]; - mutationOperator = operators_["mutation"]; - selectionOperator = operators_["selection"]; - - // Create the initial solutionSet - Solution * newSolution; - for (int i = 0; i < populationSize; i++) { - newSolution = new Solution(problem_); - problem_->evaluate(newSolution); - problem_->evaluateConstraints(newSolution); - evaluations++; - population->add(newSolution); - } //for - - Solution ** parents; - Solution ** offSpring; - - // Generations ... - while (evaluations < maxEvaluations) { - - // Create the offSpring solutionSet - offspringPopulation = new SolutionSet(1); - - /*Selection Operator must return two individuals*/ - parents = (Solution **) (selectionOperator->execute(population)); - - offSpring = (Solution **) (crossoverOperator->execute(parents)); - - mutationOperator->execute(offSpring[0]); - - problem_->evaluate(offSpring[0]); - problem_->evaluateConstraints(offSpring[0]); - - // insert child into the offspring population - offspringPopulation->add(offSpring[0]); - - evaluations++; - - //cout << "Evaluations " << evaluations << endl; - - delete offSpring[1]; - delete[] offSpring; - delete[] parents; - - // Create the solutionSet union of solutionSet and offSpring - unionSolution = population->join(offspringPopulation); - delete offspringPopulation; - - // Ranking the union (non-dominated sorting) - Ranking * ranking = new Ranking(unionSolution); - - // ensure crowding distance values are up to date - // (may be important for parent selection) - for (int j = 0; j < population->size(); j++){ - population->get(j)->setCrowdingDistance(0.0); - } - - //cout << "front 0 size: " << ranking->getSubfront(0)->size() << endl ; - - SolutionSet *lastFront = ranking->getSubfront(ranking->getNumberOfSubfronts() - 1); - if (lastFront->size() > 1) { - - vector > frontValues = lastFront->writeObjectivesToMatrix(); - int numberOfObjectives = problem_->getNumberOfObjectives(); - - // STEP 1. Obtain the maximum and minimum values of the Pareto front - vector maximumValues = utils_->getMaximumValues(unionSolution->writeObjectivesToMatrix(), numberOfObjectives); - vector minimumValues = utils_->getMinimumValues(unionSolution->writeObjectivesToMatrix(), numberOfObjectives); - - // STEP 2. Get the normalized front - vector > normalizedFront = utils_->getNormalizedFront(frontValues, maximumValues, minimumValues); - - // compute offsets for reference point in normalized space - vector offsets; - for (int i = 0; i < maximumValues.size(); i++) { - offsets.push_back(offset / (maximumValues[i] - minimumValues[i])); - } - - // STEP 3. Inverse the pareto front. This is needed because the original - //metric by Zitzler is for maximization problems - vector > invertedFront = utils_->invertedFront(normalizedFront); - // shift away from origin, so that boundary points also get a contribution > 0 - for (int i = 0; i < invertedFront.size();i++) { - for (int j = 0; j < invertedFront[i].size(); j++) { - invertedFront[i][j] = invertedFront[i][j] + offsets[j]; +SolutionSet * SMSEMOA::execute() +{ + int populationSize; + int maxEvaluations; + int evaluations; + double offset = 100.0; + + QualityIndicator * indicators; // QualityIndicator object + int requiredEvaluations; // Use in the example of use of the indicators object (see below) + + SolutionSet * population; + SolutionSet * offspringPopulation; + SolutionSet * unionSolution; + + Operator * mutationOperator; + Operator * crossoverOperator; + Operator * selectionOperator; + + //Read the parameters + populationSize = *(int *) getInputParameter("populationSize"); + maxEvaluations = *(int *) getInputParameter("maxEvaluations"); + offset = *(double *) getInputParameter("offset"); + + //indicators = (QualityIndicator*) getInputParameter("indicators"); + + //Initialize the variables + population = new SolutionSet(populationSize); + evaluations = 0; + + requiredEvaluations = 0; + + //Read the operators + crossoverOperator = operators_["crossover"]; + mutationOperator = operators_["mutation"]; + selectionOperator = operators_["selection"]; + + // Create the initial solutionSet + Solution * newSolution; + for (int i = 0; i < populationSize; i++) + { + newSolution = new Solution(problem_); + problem_->evaluate(newSolution); + problem_->evaluateConstraints(newSolution); + evaluations++; + population->add(newSolution); + } //for + + Solution ** parents; + Solution ** offSpring; + + // Generations ... + while (evaluations < maxEvaluations) + { + + // Create the offSpring solutionSet + offspringPopulation = new SolutionSet(1); + + /*Selection Operator must return two individuals*/ + parents = (Solution **) (selectionOperator->execute(population)); + + offSpring = (Solution **) (crossoverOperator->execute(parents)); + + mutationOperator->execute(offSpring[0]); + + problem_->evaluate(offSpring[0]); + problem_->evaluateConstraints(offSpring[0]); + + // insert child into the offspring population + offspringPopulation->add(offSpring[0]); + + evaluations++; + + //std::cout << "Evaluations " << evaluations << std::endl; + + delete offSpring[1]; + delete[] offSpring; + delete[] parents; + + // Create the solutionSet union of solutionSet and offSpring + unionSolution = population->join(offspringPopulation); + delete offspringPopulation; + + // Ranking the union (non-dominated sorting) + Ranking * ranking = new Ranking(unionSolution); + + // ensure crowding distance values are up to date + // (may be important for parent selection) + for (int j = 0; j < population->size(); j++) + { + population->get(j)->setCrowdingDistance(0.0); } - } - - // calculate contributions and sort - vector contributions = hvContributions(invertedFront); - for (int i = 0; i < contributions.size(); i++) { - // contribution values are used analogously to crowding distance - lastFront->get(i)->setCrowdingDistance(contributions[i]); - } - - CrowdingDistanceComparator *cd = new CrowdingDistanceComparator(); - lastFront->sort(cd); - delete cd; - - } - - // all but the worst are carried over to the survivor population - SolutionSet *front = NULL; - for (int i=0;isize();i++) { - delete population->get(i); - } - population->clear(); - - for (int i = 0; i < ranking->getNumberOfSubfronts() - 1; i++) { - front = ranking->getSubfront(i); - for (int j = 0; j < front->size(); j++) - population->add(new Solution(front->get(j))); + + //std::cout << "front 0 size: " << ranking->getSubfront(0)->size() << std::endl ; + + SolutionSet *lastFront = ranking->getSubfront(ranking->getNumberOfSubfronts() - 1); + if (lastFront->size() > 1) + { + + std::vector frontValues = lastFront->writeObjectivesToMatrix(); + int numberOfObjectives = problem_->getNumberOfObjectives(); + + // STEP 1. Obtain the maximum and minimum values of the Pareto front + VectorOfDouble maximumValues = utils_->getMaximumValues(unionSolution->writeObjectivesToMatrix(), numberOfObjectives); + VectorOfDouble minimumValues = utils_->getMinimumValues(unionSolution->writeObjectivesToMatrix(), numberOfObjectives); + + // STEP 2. Get the normalized front + std::vector normalizedFront = utils_->getNormalizedFront(frontValues, maximumValues, minimumValues); + + // compute offsets for reference point in normalized space + VectorOfDouble offsets; + for (int i = 0; i < maximumValues.size(); i++) + { + offsets.push_back(offset / (maximumValues[i] - minimumValues[i])); + } + + // STEP 3. Inverse the pareto front. This is needed because the original + //metric by Zitzler is for maximization problems + std::vector invertedFront = utils_->invertedFront(normalizedFront); + // shift away from origin, so that boundary points also get a contribution > 0 + for (int i = 0; i < invertedFront.size(); i++) + { + for (int j = 0; j < invertedFront[i].size(); j++) + { + invertedFront[i][j] = invertedFront[i][j] + offsets[j]; + } + } + + // calculate contributions and sort + VectorOfDouble contributions = hvContributions(invertedFront); + for (int i = 0; i < contributions.size(); i++) + { + // contribution values are used analogously to crowding distance + lastFront->get(i)->setCrowdingDistance(contributions[i]); + } + + CrowdingDistanceComparator *cd = new CrowdingDistanceComparator(); + lastFront->sort(cd); + delete cd; + + } + + // all but the worst are carried over to the survivor population + SolutionSet *front = nullptr; + for (int i=0; isize(); i++) + { + delete population->get(i); + } + population->clear(); + + for (int i = 0; i < ranking->getNumberOfSubfronts() - 1; i++) + { + front = ranking->getSubfront(i); + for (int j = 0; j < front->size(); j++) + population->add(new Solution(front->get(j))); + } + for (int i = 0; i < lastFront->size() - 1; i++) + population->add(new Solution(lastFront->get(i))); + + delete ranking; + delete unionSolution; + + // This piece of code shows how to use the indicator object into the code + // of SMS-EMOA. In particular, it finds the number of evaluations required + // by the algorithm to obtain a Pareto front with a hypervolume higher + // than the hypervolume of the true Pareto front. + /*if (indicators != nullptr && requiredEvaluations == 0) { + double HV = indicators->getHypervolume(population); + if (HV >= (0.98 * indicators->getTrueParetoFrontHypervolume())) { + requiredEvaluations = evaluations; + } // if + } // if */ + + } //WHILE + + // Return the first non-dominated front + Ranking *ranking = new Ranking(population); + SolutionSet * result = new SolutionSet(ranking->getSubfront(0)->size()); + for (int i=0; igetSubfront(0)->size(); i++) + { + result->add(new Solution(ranking->getSubfront(0)->get(i))); } - for (int i = 0; i < lastFront->size() - 1; i++) - population->add(new Solution(lastFront->get(i))); - delete ranking; - delete unionSolution; - - // This piece of code shows how to use the indicator object into the code - // of SMS-EMOA. In particular, it finds the number of evaluations required - // by the algorithm to obtain a Pareto front with a hypervolume higher - // than the hypervolume of the true Pareto front. - /*if (indicators != NULL && requiredEvaluations == 0) { - double HV = indicators->getHypervolume(population); - if (HV >= (0.98 * indicators->getTrueParetoFrontHypervolume())) { - requiredEvaluations = evaluations; - } // if - } // if */ - - } //WHILE - - // Return the first non-dominated front - Ranking *ranking = new Ranking(population); - SolutionSet * result = new SolutionSet(ranking->getSubfront(0)->size()); - for (int i=0;igetSubfront(0)->size();i++) { - result->add(new Solution(ranking->getSubfront(0)->get(i))); - } - delete ranking; - delete population; - - return result; + delete population; + + return result; } -vector SMSEMOA::hvContributions(vector< vector > front){ - int numberOfObjectives = problem_->getNumberOfObjectives(); - - vector contributions; - double hv; - - double** frontSubset; - - vector< vector > frontCopy; - - double** totalFront = new double*[front.size()]; - - for (int i = 0; i < front.size(); i++) { - frontCopy.push_back(vector()); - totalFront[i] = new double[front[i].size()]; - for (int j = 0; j < front[i].size(); j++) { - frontCopy[i].push_back(front[i][j]); - totalFront[i][j] = front[i][j]; - } - } - - double totalVolume = hv_->calculateHypervolume(totalFront, front.size(), numberOfObjectives); - - for (int i = 0; i < front.size(); i++) { - - vector evaluatedPoint; - for (int j = 0; j < frontCopy[i].size(); j++) { - evaluatedPoint.push_back(frontCopy[i][j]); +VectorOfDouble SMSEMOA::hvContributions(MatrixOfDouble front) +{ + int numberOfObjectives = problem_->getNumberOfObjectives(); + + VectorOfDouble contributions; + double hv; + + double** frontSubset; + + MatrixOfDouble frontCopy; + + double** totalFront = snew double*[front.size()]; + + for (int i = 0; i < front.size(); i++) + { + frontCopy.push_back(VectorOfDouble()); + totalFront[i] = snew double[front[i].size()]; + for (int j = 0; j < front[i].size(); j++) + { + frontCopy[i].push_back(front[i][j]); + totalFront[i][j] = front[i][j]; + } } - frontCopy.erase(frontCopy.begin() + i); - - /*Makes a copy in pointer of pointer format*/ - frontSubset = new double*[frontCopy.size()]; - for (int f = 0; f < frontCopy.size(); f++) { - frontSubset[f] = new double[frontCopy[f].size()]; - for (int c = 0; c < frontCopy[f].size(); c++) { - frontSubset[f][c]=frontCopy[f][c]; - } + + double totalVolume = hv_->calculateHypervolume(totalFront, front.size(), numberOfObjectives); + + for (int i = 0; i < front.size(); i++) + { + + VectorOfDouble evaluatedPoint; + for (int j = 0; j < frontCopy[i].size(); j++) + { + evaluatedPoint.push_back(frontCopy[i][j]); + } + frontCopy.erase(frontCopy.begin() + i); + + /*Makes a copy in pointer of pointer format*/ + frontSubset = snew double*[frontCopy.size()]; + for (int f = 0; f < frontCopy.size(); f++) + { + frontSubset[f] = snew double[frontCopy[f].size()]; + for (int c = 0; c < frontCopy[f].size(); c++) + { + frontSubset[f][c]=frontCopy[f][c]; + } + } + + // STEP4. The hypervolume + hv = hv_->calculateHypervolume(frontSubset, frontCopy.size(), numberOfObjectives); + contributions.push_back(totalVolume - hv); + + // put point back position i + frontCopy.insert(frontCopy.begin() + i, evaluatedPoint); + + for( int y = 0 ; y < frontCopy.size()-1 ; y++ ) + { + delete [] frontSubset[y] ; + } + delete [] frontSubset; + } - - // STEP4. The hypervolume - hv = hv_->calculateHypervolume(frontSubset, frontCopy.size(), numberOfObjectives); - contributions.push_back(totalVolume - hv); - - // put point back position i - frontCopy.insert(frontCopy.begin() + i , evaluatedPoint); - - for( int y = 0 ; y < frontCopy.size()-1 ; y++ ) { - delete [] frontSubset[y] ; + + for( int y = 0 ; y < front.size() ; y++ ) + { + delete [] totalFront[y] ; } - delete [] frontSubset; - - } - - for( int y = 0 ; y < front.size() ; y++ ) { - delete [] totalFront[y] ; - } - delete [] totalFront; - - return contributions; + delete [] totalFront; + + return contributions; } diff --git a/src/metaheuristics/smsemoa/SMSEMOA.h b/src/metaheuristics/smsemoa/SMSEMOA.h index 10ab5f8..778229a 100644 --- a/src/metaheuristics/smsemoa/SMSEMOA.h +++ b/src/metaheuristics/smsemoa/SMSEMOA.h @@ -32,20 +32,21 @@ #include #include -class SMSEMOA : public Algorithm { +class SMSEMOA : public Algorithm +{ private: - MetricsUtil * utils_; - Hypervolume * hv_; + MetricsUtil * utils_; + Hypervolume * hv_; - vector hvContributions(vector< vector > front); + vector hvContributions(vector< vector > front); public: - SMSEMOA(Problem * problem); - ~SMSEMOA(); - SolutionSet * execute(); + SMSEMOA(Problem * problem); + ~SMSEMOA(); + SolutionSet * execute(); }; diff --git a/src/operators/CMakeLists.txt b/src/operators/CMakeLists.txt new file mode 100644 index 0000000..1107f2e --- /dev/null +++ b/src/operators/CMakeLists.txt @@ -0,0 +1,3 @@ +add_subdirectory(crossover) +add_subdirectory(mutation) +add_subdirectory(selection) \ No newline at end of file diff --git a/src/operators/crossover/CMakeLists.txt b/src/operators/crossover/CMakeLists.txt new file mode 100644 index 0000000..294ec59 --- /dev/null +++ b/src/operators/crossover/CMakeLists.txt @@ -0,0 +1,3 @@ +file(GLOB SOURCES "*.cpp" "*.h") +ListToString(SOURCES ";" ${SOURCES}) +LIST_APPEND("${SOURCES}") \ No newline at end of file diff --git a/src/operators/crossover/Crossover.cpp b/src/operators/crossover/Crossover.cpp index 4a9b94e..029ec93 100644 --- a/src/operators/crossover/Crossover.cpp +++ b/src/operators/crossover/Crossover.cpp @@ -22,7 +22,7 @@ #include -Crossover::Crossover(map parameters) -: Operator(parameters) {} +Crossover::Crossover(MapOfStringFunct parameters) + : Operator(parameters) {} Crossover::~Crossover() { /* do nothing */ } diff --git a/src/operators/crossover/Crossover.h b/src/operators/crossover/Crossover.h index 7a840f9..c37b056 100644 --- a/src/operators/crossover/Crossover.h +++ b/src/operators/crossover/Crossover.h @@ -29,11 +29,12 @@ * @class Crossover * @brief This class is aimed at representing a Crossover operator **/ -class Crossover : public Operator { +class Crossover : public Operator +{ public: - Crossover(map parameters); - virtual ~Crossover() = 0; + Crossover(MapOfStringFunct parameters); + virtual ~Crossover() = 0; }; diff --git a/src/operators/crossover/DifferentialEvolutionCrossover.cpp b/src/operators/crossover/DifferentialEvolutionCrossover.cpp index 797341d..87d08a5 100644 --- a/src/operators/crossover/DifferentialEvolutionCrossover.cpp +++ b/src/operators/crossover/DifferentialEvolutionCrossover.cpp @@ -2,6 +2,7 @@ // // Author: // Esteban López-Camacho +// Sérgio Vieira // // Copyright (c) 2011 Antonio J. Nebro, Juan J. Durillo // @@ -58,32 +59,37 @@ const double DifferentialEvolutionCrossover::DEFAULT_K = 0.5; /** * DEFAULT_VARIANT defines the default DE variant */ -const string DifferentialEvolutionCrossover::DEFAULT_DE_VARIANT = "rand/1/bin"; +const std::string DifferentialEvolutionCrossover::DEFAULT_DE_VARIANT = "rand/1/bin"; /** * Constructor */ -DifferentialEvolutionCrossover::DifferentialEvolutionCrossover(map parameters) -: Crossover(parameters) { - - CR_ = DEFAULT_CR ; - F_ = DEFAULT_F ; - K_ = DEFAULT_K ; - DE_Variant_ = DEFAULT_DE_VARIANT ; - - if (parameters["CR"] != NULL) { - CR_ = *(double *) parameters["CR"]; - } - if (parameters["F"] != NULL) { - F_ = *(double *) parameters["F"]; - } - if (parameters["K"] != NULL) { - K_ = *(double *) parameters["K"]; - } - if (parameters["DE_VARIANT"] != NULL) { - DE_Variant_ = *(string *) parameters["DE_VARIANT"]; - } +DifferentialEvolutionCrossover::DifferentialEvolutionCrossover(MapOfStringFunct parameters) + : Crossover(parameters) +{ + + CR_ = DEFAULT_CR ; + F_ = DEFAULT_F ; + K_ = DEFAULT_K ; + DE_Variant_ = DEFAULT_DE_VARIANT ; + + if (parameters["CR"] != nullptr) + { + CR_ = *(double *) parameters["CR"]; + } + if (parameters["F"] != nullptr) + { + F_ = *(double *) parameters["F"]; + } + if (parameters["K"] != nullptr) + { + K_ = *(double *) parameters["K"]; + } + if (parameters["DE_VARIANT"] != nullptr) + { + DE_Variant_ = *(std::string *) parameters["DE_VARIANT"]; + } } // DifferentialEvolutionCrossover @@ -93,190 +99,227 @@ DifferentialEvolutionCrossover::DifferentialEvolutionCrossover(mapgetNumberOfDecisionVariables(); - jrand = PseudoRandom::randInt(0, numberOfVariables - 1); - - // STEP 4. Checking the DE variant - if ((DE_Variant_.compare("rand/1/bin") == 0) || - (DE_Variant_.compare("best/1/bin") == 0)) { - - for (int j=0; j < numberOfVariables; j++) { - if (PseudoRandom::randDouble(0, 1) < CR_ || j == jrand) { - double value; - value = xParent2->getValue(j) + F_ * (xParent0->getValue(j) - - xParent1->getValue(j)); - - if (value < xChild->getLowerBound(j)) { - value = xChild->getLowerBound(j); - } - if (value > xChild->getUpperBound(j)) { - value = xChild->getUpperBound(j); - } - /* - if (value < xChild.getLowerBound(j)) { - double rnd = PseudoRandom.randDouble(0, 1) ; - value = xChild.getLowerBound(j) + rnd *(xParent2.getValue(j) - xChild.getLowerBound(j)) ; - } - if (value > xChild.getUpperBound(j)) { - double rnd = PseudoRandom.randDouble(0, 1) ; - value = xChild.getUpperBound(j) - rnd*(xChild.getUpperBound(j)-xParent2.getValue(j)) ; - } - */ - xChild->setValue(j, value); - } - else { - double value ; - value = xCurrent->getValue(j); - xChild->setValue(j, value); - } // else - } // for - - } else if ((DE_Variant_.compare("rand/1/exp") == 0) || - (DE_Variant_.compare("best/1/exp") == 0)) { - - for (int j=0; j < numberOfVariables; j++) { - if (PseudoRandom::randDouble(0, 1) < CR_ || j == jrand) { - double value; - value = xParent2->getValue(j) + F_ * (xParent0->getValue(j) - - xParent1->getValue(j)); - - if (value < xChild->getLowerBound(j)) { - value = xChild->getLowerBound(j); - } - if (value > xChild->getUpperBound(j)) { - value = xChild->getUpperBound(j); - } - - xChild->setValue(j, value); - } else { - CR_ = 0.0; - double value; - value = xCurrent->getValue(j); - xChild->setValue(j, value); - } // if - } // for - - } else if ((DE_Variant_.compare("current-to-rand/1") == 0) || - (DE_Variant_.compare("current-to-best/1") == 0)) { - - for (int j=0; j < numberOfVariables; j++) { - double value; - value = xCurrent->getValue(j) + K_ * (xParent2->getValue(j) - - xCurrent->getValue(j)) + - F_ * (xParent0->getValue(j) - xParent1->getValue(j)); - - if (value < xChild->getLowerBound(j)) { - value = xChild->getLowerBound(j); - } - if (value > xChild->getUpperBound(j)) { - value = xChild->getUpperBound(j); - } - xChild->setValue(j, value) ; - } // for - - } else if ((DE_Variant_.compare("current-to-rand/1/bin") == 0) || - (DE_Variant_.compare("current-to-best/1/bin") == 0)) { - - for (int j=0; j < numberOfVariables; j++) { - if (PseudoRandom::randDouble(0, 1) < CR_ || j == jrand) { - double value ; - value = xCurrent->getValue(j) + K_ * (xParent2->getValue(j) - - xCurrent->getValue(j)) + - F_ * (xParent0->getValue(j) - xParent1->getValue(j)); - - if (value < xChild->getLowerBound(j)) { - value = xChild->getLowerBound(j); - } - if (value > xChild->getUpperBound(j)) { - value = xChild->getUpperBound(j); - } - - xChild->setValue(j, value); - } - else { - double value; - value = xCurrent->getValue(j); - xChild->setValue(j, value); - } // else - } // for - - } else if ((DE_Variant_.compare("current-to-rand/1/exp") == 0) || - (DE_Variant_.compare("current-to-best/1/exp") == 0)) { - - for (int j=0; j < numberOfVariables; j++) { - if (PseudoRandom::randDouble(0, 1) < CR_ || j == jrand) { - double value ; - value = xCurrent->getValue(j) + K_ * (xParent2->getValue(j) - - xCurrent->getValue(j)) + - F_ * (xParent0->getValue(j) - xParent1->getValue(j)); - - if (value < xChild->getLowerBound(j)) { - value = xChild->getLowerBound(j); - } - if (value > xChild->getUpperBound(j)) { - value = xChild->getUpperBound(j); - } - - xChild->setValue(j, value); - } else { - CR_ = 0.0; - double value; - value = xCurrent->getValue(j); - xChild->setValue(j, value); - } // else - } // for - - } else { - - cerr << "DifferentialEvolutionCrossover.execute: " << - " unknown DE variant (" << DE_Variant_ << ")" << endl; - cerr << "Exception in DifferentialEvolutionCrossover.execute()" << endl; - exit(-1); - - } // if - - delete xParent0; - delete xParent1; - delete xParent2; - delete xCurrent; - delete xChild; - - return child; +void * DifferentialEvolutionCrossover::execute(void *object) +{ + + void ** parameters = (void **) object; + Solution * current = (Solution *) parameters[0]; + Solution ** parent = (Solution **) parameters[1]; + // TODO: Comprobar la longitud de parents + + Solution * child; + + // TODO: Chequear el tipo de parents + // if (!(VALID_TYPES.contains(parent[0].getType().getClass()) && + // VALID_TYPES.contains(parent[1].getType().getClass()) && + // VALID_TYPES.contains(parent[2].getType().getClass())) ) { + // + // Configuration.logger_.severe("DifferentialEvolutionCrossover.execute: " + + // " the solutions " + + // "are not of the right type. The type should be 'Real' or 'ArrayReal', but " + + // parent[0].getType() + " and " + + // parent[1].getType() + " and " + + // parent[2].getType() + " are obtained"); + // + // Class cls = java.lang.String.class; + // String name = cls.getName(); + // throw new JMException("Exception in " + name + ".execute()") ; + // } + + int jrand; + + child = snew Solution(current); + + XReal * xParent0 = snew XReal(parent[0]); + XReal * xParent1 = snew XReal(parent[1]); + XReal * xParent2 = snew XReal(parent[2]); + XReal * xCurrent = snew XReal(current); + XReal * xChild = snew XReal(child); + + int numberOfVariables = xParent0->getNumberOfDecisionVariables(); + jrand = PseudoRandom::randInt(0, numberOfVariables - 1); + + // STEP 4. Checking the DE variant + if ((DE_Variant_.compare("rand/1/bin") == 0) || + (DE_Variant_.compare("best/1/bin") == 0)) + { + + for (int j=0; j < numberOfVariables; j++) + { + if (PseudoRandom::randDouble(0, 1) < CR_ || j == jrand) + { + double value; + value = xParent2->getValue(j) + F_ * (xParent0->getValue(j) - + xParent1->getValue(j)); + + if (value < xChild->getLowerBound(j)) + { + value = xChild->getLowerBound(j); + } + if (value > xChild->getUpperBound(j)) + { + value = xChild->getUpperBound(j); + } + /* + if (value < xChild.getLowerBound(j)) { + double rnd = PseudoRandom.randDouble(0, 1) ; + value = xChild.getLowerBound(j) + rnd *(xParent2.getValue(j) - xChild.getLowerBound(j)) ; + } + if (value > xChild.getUpperBound(j)) { + double rnd = PseudoRandom.randDouble(0, 1) ; + value = xChild.getUpperBound(j) - rnd*(xChild.getUpperBound(j)-xParent2.getValue(j)) ; + } + */ + xChild->setValue(j, value); + } + else + { + double value ; + value = xCurrent->getValue(j); + xChild->setValue(j, value); + } // else + } // for + + } + else if ((DE_Variant_.compare("rand/1/exp") == 0) || + (DE_Variant_.compare("best/1/exp") == 0)) + { + + for (int j=0; j < numberOfVariables; j++) + { + if (PseudoRandom::randDouble(0, 1) < CR_ || j == jrand) + { + double value; + value = xParent2->getValue(j) + F_ * (xParent0->getValue(j) - + xParent1->getValue(j)); + + if (value < xChild->getLowerBound(j)) + { + value = xChild->getLowerBound(j); + } + if (value > xChild->getUpperBound(j)) + { + value = xChild->getUpperBound(j); + } + + xChild->setValue(j, value); + } + else + { + CR_ = 0.0; + double value; + value = xCurrent->getValue(j); + xChild->setValue(j, value); + } // if + } // for + + } + else if ((DE_Variant_.compare("current-to-rand/1") == 0) || + (DE_Variant_.compare("current-to-best/1") == 0)) + { + + for (int j=0; j < numberOfVariables; j++) + { + double value; + value = xCurrent->getValue(j) + K_ * (xParent2->getValue(j) - + xCurrent->getValue(j)) + + F_ * (xParent0->getValue(j) - xParent1->getValue(j)); + + if (value < xChild->getLowerBound(j)) + { + value = xChild->getLowerBound(j); + } + if (value > xChild->getUpperBound(j)) + { + value = xChild->getUpperBound(j); + } + xChild->setValue(j, value) ; + } // for + + } + else if ((DE_Variant_.compare("current-to-rand/1/bin") == 0) || + (DE_Variant_.compare("current-to-best/1/bin") == 0)) + { + + for (int j=0; j < numberOfVariables; j++) + { + if (PseudoRandom::randDouble(0, 1) < CR_ || j == jrand) + { + double value ; + value = xCurrent->getValue(j) + K_ * (xParent2->getValue(j) - + xCurrent->getValue(j)) + + F_ * (xParent0->getValue(j) - xParent1->getValue(j)); + + if (value < xChild->getLowerBound(j)) + { + value = xChild->getLowerBound(j); + } + if (value > xChild->getUpperBound(j)) + { + value = xChild->getUpperBound(j); + } + + xChild->setValue(j, value); + } + else + { + double value; + value = xCurrent->getValue(j); + xChild->setValue(j, value); + } // else + } // for + + } + else if ((DE_Variant_.compare("current-to-rand/1/exp") == 0) || + (DE_Variant_.compare("current-to-best/1/exp") == 0)) + { + + for (int j=0; j < numberOfVariables; j++) + { + if (PseudoRandom::randDouble(0, 1) < CR_ || j == jrand) + { + double value ; + value = xCurrent->getValue(j) + K_ * (xParent2->getValue(j) - + xCurrent->getValue(j)) + + F_ * (xParent0->getValue(j) - xParent1->getValue(j)); + + if (value < xChild->getLowerBound(j)) + { + value = xChild->getLowerBound(j); + } + if (value > xChild->getUpperBound(j)) + { + value = xChild->getUpperBound(j); + } + + xChild->setValue(j, value); + } + else + { + CR_ = 0.0; + double value; + value = xCurrent->getValue(j); + xChild->setValue(j, value); + } // else + } // for + + } + else + { + + cerr << "DifferentialEvolutionCrossover.execute: " << + " unknown DE variant (" << DE_Variant_ << ")" << std::endl; + cerr << "Exception in DifferentialEvolutionCrossover.execute()" << std::endl; + exit(-1); + + } // if + + delete xParent0; + delete xParent1; + delete xParent2; + delete xCurrent; + delete xChild; + + return child; } // execute diff --git a/src/operators/crossover/DifferentialEvolutionCrossover.h b/src/operators/crossover/DifferentialEvolutionCrossover.h index 451d726..ab30614 100644 --- a/src/operators/crossover/DifferentialEvolutionCrossover.h +++ b/src/operators/crossover/DifferentialEvolutionCrossover.h @@ -2,6 +2,7 @@ // // Author: // Esteban López-Camacho +// Sérgio Vieira // // Copyright (c) 2011 Antonio J. Nebro, Juan J. Durillo // @@ -43,24 +44,25 @@ * - current-to-rand/1/bin (current-to-best/1/bin) * - current-to-rand/1/exp (current-to-best/1/exp) */ -class DifferentialEvolutionCrossover : public Crossover { +class DifferentialEvolutionCrossover : public Crossover +{ public: - DifferentialEvolutionCrossover(map parameters); - void *execute(void *); + DifferentialEvolutionCrossover(MapOfStringFunct parameters); + void *execute(void *); protected: - static const double DEFAULT_CR; - static const double DEFAULT_F; - static const double DEFAULT_K; - static const string DEFAULT_DE_VARIANT; + static const double DEFAULT_CR; + static const double DEFAULT_F; + static const double DEFAULT_K; + static const std::string DEFAULT_DE_VARIANT; private: - double CR_ ; - double F_ ; - double K_ ; - string DE_Variant_ ; // DE variant (rand/1/bin, rand/1/exp, etc.) - //TODO: A�adir VALID_TYPES; + double CR_ ; + double F_ ; + double K_ ; + std::string DE_Variant_ ; // DE variant (rand/1/bin, rand/1/exp, etc.) + //TODO: A�adir VALID_TYPES; }; diff --git a/src/operators/crossover/HUXCrossover.cpp b/src/operators/crossover/HUXCrossover.cpp index 52c2152..0f143b4 100644 --- a/src/operators/crossover/HUXCrossover.cpp +++ b/src/operators/crossover/HUXCrossover.cpp @@ -27,12 +27,13 @@ * Create a new SBX crossover operator whit a default * index given by DEFAULT_INDEX_CROSSOVER */ -HUXCrossover::HUXCrossover(map parameters) -: Crossover(parameters) { - crossoverProbability_ = 0.0 ; - //TODO: crossoverProbability_ = NULL; - if (parameters["probability"] != NULL) - crossoverProbability_ = *(double *)parameters["probability"]; +HUXCrossover::HUXCrossover(MapOfStringFunct parameters) + : Crossover(parameters) +{ + crossoverProbability_ = 0.0 ; + //TODO: crossoverProbability_ = nullptr; + if (parameters["probability"] != nullptr) + crossoverProbability_ = *(double *)parameters["probability"]; } // SinglePointCrossover @@ -43,41 +44,48 @@ HUXCrossover::HUXCrossover(map parameters) * @param parent2 The second parent * @return An array containing the two offsprings **/ -Solution ** HUXCrossover::doCrossover(double probability, Solution *parent1, Solution *parent2) { - - Solution** offSpring = new Solution*[2]; - - if (offSpring == NULL) { - cout << "Error grave: Impossible reserve memory for allocating new solutions when performing SinglePointCrossover " << endl; - exit(-1); - } - - offSpring[0] = new Solution(parent1); - offSpring[1] = new Solution(parent2); - - if (PseudoRandom::randDouble() < probability) { - for (int var = 0; var < parent1->getNumberOfVariables(); var++) { - Binary *p1 = (Binary *)parent1->getDecisionVariables()[var]; - Binary *p2 = (Binary *)parent2->getDecisionVariables()[var]; - for (int bit = 0; bit < p1->getNumberOfBits(); bit++) { - if (PseudoRandom::randDouble() < 0.5) { - Binary *o1, *o2; - o1 = (Binary *) offSpring[0]->getDecisionVariables()[var]; - o2 = (Binary *) offSpring[1]->getDecisionVariables()[var]; - o1->setIth(bit,p2->getIth(bit)); - o2->setIth(bit,p1->getIth(bit)); - - } - } - } - for (int var = 0; var < parent1->getNumberOfVariables(); var++) { - ((Binary *)offSpring[0]->getDecisionVariables()[var])->decode(); - ((Binary *)offSpring[0]->getDecisionVariables()[var])->decode(); - } - } - return offSpring; - - return offSpring; +Solution ** HUXCrossover::doCrossover(double probability, Solution *parent1, Solution *parent2) +{ + + Solution** offSpring = snew Solution*[2]; + + if (offSpring == nullptr) + { + std::cout << "Error grave: Impossible reserve memory for allocating new solutions when performing SinglePointCrossover " << std::endl; + exit(-1); + } + + offSpring[0] = snew Solution(parent1); + offSpring[1] = snew Solution(parent2); + + if (PseudoRandom::randDouble() < probability) + { + for (int var = 0; var < parent1->getNumberOfVariables(); var++) + { + Binary *p1 = (Binary *)parent1->getDecisionVariables()[var]; + Binary *p2 = (Binary *)parent2->getDecisionVariables()[var]; + for (int bit = 0; bit < p1->getNumberOfBits(); bit++) + { + if (PseudoRandom::randDouble() < 0.5) + { + Binary *o1, *o2; + o1 = (Binary *) offSpring[0]->getDecisionVariables()[var]; + o2 = (Binary *) offSpring[1]->getDecisionVariables()[var]; + o1->setIth(bit,p2->getIth(bit)); + o2->setIth(bit,p1->getIth(bit)); + + } + } + } + for (int var = 0; var < parent1->getNumberOfVariables(); var++) + { + ((Binary *)offSpring[0]->getDecisionVariables()[var])->decode(); + ((Binary *)offSpring[0]->getDecisionVariables()[var])->decode(); + } + } + return offSpring; + + return offSpring; } // doCrossover @@ -86,12 +94,13 @@ Solution ** HUXCrossover::doCrossover(double probability, Solution *parent1, Sol * @param object An object containing an array of two parents * @return An object containing the offSprings */ -void * HUXCrossover::execute(void *object) { - Solution ** parents = (Solution **) object; - // TODO: Comprobar la longitud de parents - // TODO: Chequear el tipo de parents +void * HUXCrossover::execute(void *object) +{ + Solution ** parents = (Solution **) object; + // TODO: Comprobar la longitud de parents + // TODO: Chequear el tipo de parents - Solution ** offSpring = (Solution **)doCrossover(crossoverProbability_, parents[0], parents[1]); + Solution ** offSpring = (Solution **)doCrossover(crossoverProbability_, parents[0], parents[1]); - return offSpring; + return offSpring; } // execute diff --git a/src/operators/crossover/HUXCrossover.h b/src/operators/crossover/HUXCrossover.h index de8623f..a740ca0 100644 --- a/src/operators/crossover/HUXCrossover.h +++ b/src/operators/crossover/HUXCrossover.h @@ -29,16 +29,17 @@ * This class allows to apply a SBX crossover operator using two parent * solutions. **/ -class HUXCrossover : public Crossover { +class HUXCrossover : public Crossover +{ public: - HUXCrossover(map parameters); - void *execute(void *); + HUXCrossover(MapOfStringFunct parameters); + void *execute(void *); private: - double crossoverProbability_; - Solution ** doCrossover(double probability, - Solution * parent1, Solution * parent2); + double crossoverProbability_; + Solution ** doCrossover(double probability, + Solution * parent1, Solution * parent2); }; diff --git a/src/operators/crossover/SBXCrossover.cpp b/src/operators/crossover/SBXCrossover.cpp index 0b21c03..21d4031 100644 --- a/src/operators/crossover/SBXCrossover.cpp +++ b/src/operators/crossover/SBXCrossover.cpp @@ -38,14 +38,15 @@ const double SBXCrossover::ETA_C_DEFAULT_ = 20.0; * Create a new SBX crossover operator whit a default * index given by DEFAULT_INDEX_CROSSOVER */ -SBXCrossover::SBXCrossover(map parameters) -: Crossover(parameters) { - //TODO: crossoverProbability_ = NULL; - distributionIndex_ = ETA_C_DEFAULT_; - if (parameters["probability"] != NULL) - crossoverProbability_ = *(double *)parameters["probability"]; - if (parameters["distributionIndex"] != NULL) - distributionIndex_ = *(double *)parameters["distributionIndex"]; +SBXCrossover::SBXCrossover(MapOfStringFunct parameters) + : Crossover(parameters) +{ + //TODO: crossoverProbability_ = nullptr; + distributionIndex_ = ETA_C_DEFAULT_; + if (parameters["probability"] != nullptr) + crossoverProbability_ = *(double *)parameters["probability"]; + if (parameters["distributionIndex"] != nullptr) + distributionIndex_ = *(double *)parameters["distributionIndex"]; } // SBXCrossover @@ -56,146 +57,169 @@ SBXCrossover::~SBXCrossover() { } // ~SBXCrossover /** -* Perform the crossover operation. +* Perform the crossover operation. * @param probability Crossover probability * @param parent1 The first parent * @param parent2 The second parent * @return An array containing the two offsprings **/ -Solution ** SBXCrossover::doCrossover(double probability, Solution *parent1, Solution *parent2) { - - Solution** offSpring = new Solution*[2]; - - if (offSpring == NULL) { - cout << "Error grave: Impossible reserve memory for allocating new solutions when performing SBXCrossover " << endl; - exit(-1); - } - -// cout << "SBXCrossover: AggregativeValue de parent1 = " << parent1->getAggregativeValue() << endl; -// cout << "SBXCrossover: AggregativeValue de parent2 = " << parent2->getAggregativeValue() << endl; - - offSpring[0] = new Solution(parent1); - offSpring[1] = new Solution(parent2); - -// cout << "SBXCrossover: AggregativeValue de offSpring[0] = " << offSpring[0]->getAggregativeValue() << endl; -// cout << "SBXCrossover: AggregativeValue de offSpring[1] = " << offSpring[1]->getAggregativeValue() << endl; - - int i; - double rand; - double y1, y2, yL, yu; - double c1, c2; - double alpha, beta, betaq; - double valueX1,valueX2; - XReal * x1 = new XReal(parent1) ; - XReal * x2 = new XReal(parent2) ; - XReal * offs1 = new XReal(offSpring[0]) ; - XReal * offs2 = new XReal(offSpring[1]) ; - - int numberOfVariables = x1->getNumberOfDecisionVariables(); - - if (PseudoRandom::randDouble() <= probability){ - for (i=0; igetValue(i); - valueX2 = x2->getValue(i); - - if (PseudoRandom::randDouble()<=0.5 ){ - if (fabs(valueX1- valueX2) > EPS){ - - if (valueX1 < valueX2){ - y1 = valueX1; - y2 = valueX2; - } else { - y1 = valueX2; - y2 = valueX1; - } // if - - yL = x1->getLowerBound(i); - yu = x1->getUpperBound(i); - - //cout << yL << " " << yu << endl; - rand = PseudoRandom::randDouble(); - - beta = 1.0 + (2.0*(y1-yL)/(y2-y1)); - alpha = 2.0 - pow(beta,-(distributionIndex_+1.0)); - - if (rand <= (1.0/alpha)){ - betaq = pow ((rand*alpha),(1.0/(distributionIndex_+1.0))); - } else { - betaq = pow ((1.0/(2.0 - rand*alpha)),(1.0/(distributionIndex_+1.0))); - } // if - - c1 = 0.5*((y1+y2)-betaq*(y2-y1)); - beta = 1.0 + (2.0*(yu-y2)/(y2-y1)); - alpha = 2.0 - pow(beta,-(distributionIndex_+1.0)); - - if (rand <= (1.0/alpha)){ - betaq = pow ((rand*alpha),(1.0/(distributionIndex_+1.0))); - } else { - betaq = pow ((1.0/(2.0 - rand*alpha)),(1.0/(distributionIndex_+1.0))); - } // if - - c2 = 0.5*((y1+y2)+betaq*(y2-y1)); - - if (c1yu) - c1=yu; - - if (c2>yu) - c2=yu; - - if (PseudoRandom::randDouble()<=0.5) { - offs1->setValue(i,c2); - offs2->setValue(i,c1); - } else { - offs1->setValue(i,c1); - offs2->setValue(i,c2); - } // if - } else { - offs1->setValue(i,valueX1); - offs2->setValue(i,valueX2); +Solution ** SBXCrossover::doCrossover(double probability, Solution *parent1, Solution *parent2) +{ + + Solution** offSpring = new Solution*[2]; + + if (offSpring == nullptr) + { + std::cout << "Error grave: Impossible reserve memory for allocating new solutions when performing SBXCrossover " << std::endl; + exit(-1); + } + +// std::cout << "SBXCrossover: AggregativeValue de parent1 = " << parent1->getAggregativeValue() << std::endl; +// std::cout << "SBXCrossover: AggregativeValue de parent2 = " << parent2->getAggregativeValue() << std::endl; + + offSpring[0] = new Solution(parent1); + offSpring[1] = new Solution(parent2); + +// std::cout << "SBXCrossover: AggregativeValue de offSpring[0] = " << offSpring[0]->getAggregativeValue() << std::endl; +// std::cout << "SBXCrossover: AggregativeValue de offSpring[1] = " << offSpring[1]->getAggregativeValue() << std::endl; + + int i; + double rand; + double y1, y2, yL, yu; + double c1, c2; + double alpha, beta, betaq; + double valueX1,valueX2; + XReal * x1 = new XReal(parent1) ; + XReal * x2 = new XReal(parent2) ; + XReal * offs1 = new XReal(offSpring[0]) ; + XReal * offs2 = new XReal(offSpring[1]) ; + + int numberOfVariables = x1->getNumberOfDecisionVariables(); + + if (PseudoRandom::randDouble() <= probability) + { + for (i=0; igetValue(i); + valueX2 = x2->getValue(i); + + if (PseudoRandom::randDouble()<=0.5 ) + { + if (fabs(valueX1- valueX2) > EPS) + { + + if (valueX1 < valueX2) + { + y1 = valueX1; + y2 = valueX2; + } + else + { + y1 = valueX2; + y2 = valueX1; + } // if + + yL = x1->getLowerBound(i); + yu = x1->getUpperBound(i); + + //std::cout << yL << " " << yu << std::endl; + rand = PseudoRandom::randDouble(); + + beta = 1.0 + (2.0*(y1-yL)/(y2-y1)); + alpha = 2.0 - pow(beta,-(distributionIndex_+1.0)); + + if (rand <= (1.0/alpha)) + { + betaq = pow ((rand*alpha),(1.0/(distributionIndex_+1.0))); + } + else + { + betaq = pow ((1.0/(2.0 - rand*alpha)),(1.0/(distributionIndex_+1.0))); + } // if + + c1 = 0.5*((y1+y2)-betaq*(y2-y1)); + beta = 1.0 + (2.0*(yu-y2)/(y2-y1)); + alpha = 2.0 - pow(beta,-(distributionIndex_+1.0)); + + if (rand <= (1.0/alpha)) + { + betaq = pow ((rand*alpha),(1.0/(distributionIndex_+1.0))); + } + else + { + betaq = pow ((1.0/(2.0 - rand*alpha)),(1.0/(distributionIndex_+1.0))); + } // if + + c2 = 0.5*((y1+y2)+betaq*(y2-y1)); + + if (c1yu) + c1=yu; + + if (c2>yu) + c2=yu; + + if (PseudoRandom::randDouble()<=0.5) + { + offs1->setValue(i,c2); + offs2->setValue(i,c1); + } + else + { + offs1->setValue(i,c1); + offs2->setValue(i,c2); + } // if + } + else + { + offs1->setValue(i,valueX1); + offs2->setValue(i,valueX2); + } // if + } + else + { + offs1->setValue(i,valueX2); + offs2->setValue(i,valueX1); + } // if } // if - } else { - offs1->setValue(i,valueX2); - offs2->setValue(i,valueX1); - } // if } // if - } // if - delete x1; - delete x2; - delete offs1; - delete offs2; - - return offSpring; + delete x1; + delete x2; + delete offs1; + delete offs2; + + return offSpring; } // doCrossover - - + + /** * Executes the operation * @param object An object containing an array of two parents * @return An object containing the offSprings */ -void * SBXCrossover::execute(void *object) { +void * SBXCrossover::execute(void *object) +{ // double probability = *(double *)getParameter("probability"); - - Solution ** parents = (Solution **) object; - // TODO: Comprobar la longitud de parents - // TODO: Chequear el tipo de parents - Solution ** offSpring = (Solution **)doCrossover(crossoverProbability_, parents[0], parents[1]); - + Solution ** parents = (Solution **) object; + // TODO: Comprobar la longitud de parents + // TODO: Chequear el tipo de parents + + Solution ** offSpring = (Solution **)doCrossover(crossoverProbability_, parents[0], parents[1]); + // for (int i = 0; i < 2; i++) // this operator will return only 2 offpsrings // { // offSpring[i]->setCrowdingDistance(0.0); // offSpring[i]->setRank(0); // } - return offSpring; -} // execute + return offSpring; +} // execute diff --git a/src/operators/crossover/SBXCrossover.h b/src/operators/crossover/SBXCrossover.h index 126fab3..9d4f3ec 100644 --- a/src/operators/crossover/SBXCrossover.h +++ b/src/operators/crossover/SBXCrossover.h @@ -32,23 +32,24 @@ * This class allows to apply a SBX crossover operator using two parent * solutions. **/ -class SBXCrossover : public Crossover { +class SBXCrossover : public Crossover +{ public: - SBXCrossover(map parameters); - ~SBXCrossover(); - void *execute(void *); + SBXCrossover(MapOfStringFunct parameters); + ~SBXCrossover(); + void *execute(void *); protected: - static const double ETA_C_DEFAULT_; - static const double EPS; + static const double ETA_C_DEFAULT_; + static const double EPS; private: - double crossoverProbability_; - double distributionIndex_; - //TODO: A�adir VALID_TYPES; - Solution ** doCrossover(double probability, - Solution * parent1, Solution * parent2); + double crossoverProbability_; + double distributionIndex_; + //TODO: A�adir VALID_TYPES; + Solution ** doCrossover(double probability, + Solution * parent1, Solution * parent2); }; #endif diff --git a/src/operators/crossover/SinglePointCrossover.cpp b/src/operators/crossover/SinglePointCrossover.cpp index 85dca51..0dcd682 100644 --- a/src/operators/crossover/SinglePointCrossover.cpp +++ b/src/operators/crossover/SinglePointCrossover.cpp @@ -33,12 +33,13 @@ * Create a new SBX crossover operator whit a default * index given by DEFAULT_INDEX_CROSSOVER */ -SinglePointCrossover::SinglePointCrossover(map parameters) -: Crossover(parameters) { - crossoverProbability_ = 0.0 ; - //TODO: crossoverProbability_ = NULL; - if (parameters["probability"] != NULL) - crossoverProbability_ = *(double *)parameters["probability"]; +SinglePointCrossover::SinglePointCrossover(MapOfStringFunct parameters) + : Crossover(parameters) +{ + crossoverProbability_ = 0.0 ; + //TODO: crossoverProbability_ = nullptr; + if (parameters["probability"] != nullptr) + crossoverProbability_ = *(double *)parameters["probability"]; } // SinglePointCrossover @@ -49,92 +50,99 @@ SinglePointCrossover::SinglePointCrossover(map parameters) * @param parent2 The second parent * @return An array containing the two offsprings **/ -Solution ** SinglePointCrossover::doCrossover(double probability, Solution *parent1, Solution *parent2) { +Solution ** SinglePointCrossover::doCrossover(double probability, Solution *parent1, Solution *parent2) +{ - Solution** offSpring = new Solution*[2]; + Solution** offSpring = new Solution*[2]; - if (offSpring == NULL) { - cout << "Error grave: Impossible reserve memory for allocating new solutions when performing SinglePointCrossover " << endl; - exit(-1); - } - - offSpring[0] = new Solution(parent1); - offSpring[1] = new Solution(parent2); - - if (PseudoRandom::randDouble() < probability) { - //1. Compute the total number of bits - int totalNumberOfBits = 0; - for (int i = 0; i < parent1->getProblem()->getNumberOfVariables(); i++) { - totalNumberOfBits += - ((Binary *)(parent1->getDecisionVariables()[0]))->getNumberOfBits() ; - } - - //2. Calculate the point to make the crossover - int crossoverPoint = PseudoRandom::randInt(0, totalNumberOfBits - 1); - - //3. Compute the variable containing the crossoverPoint bit - int variable = 0; - int acountBits = - ((Binary *)(parent1->getDecisionVariables()[variable]))->getNumberOfBits() ; - - while (acountBits < (crossoverPoint + 1)) { - variable++; - acountBits += - ((Binary *)(parent1->getDecisionVariables()[variable]))->getNumberOfBits() ; - } - - //4. Compute the bit into the variable selected - int diff = acountBits - crossoverPoint; - int intoVariableCrossoverPoint = - ((Binary *)(parent1->getDecisionVariables()[variable]))->getNumberOfBits() - diff; - - - //5. Make the crossover into the the gene; - Variable* offSpring1, * offSpring2; - Binary * of1, *of2 ; - offSpring1 = - ((parent1->getDecisionVariables()[variable]))->deepCopy(); - - offSpring2 = - ((parent2->getDecisionVariables()[variable]))->deepCopy(); - of1 = (Binary *)offSpring1 ; - of2 = (Binary *)offSpring2 ; - - for (int i = intoVariableCrossoverPoint; - i < of1->getNumberOfBits(); - i++) { - bool swap = of1->getIth(i) ; - of1->setIth(i, of2->getIth(i)) ; - of2->setIth(i, swap) ; + if (offSpring == nullptr) + { + std::cout << "Error grave: Impossible reserve memory for allocating new solutions when performing SinglePointCrossover " << std::endl; + exit(-1); } - delete offSpring[0]->getDecisionVariables()[variable]; - delete offSpring[1]->getDecisionVariables()[variable]; - offSpring[0]->getDecisionVariables()[variable] = of1 ; - offSpring[1]->getDecisionVariables()[variable] = of2 ; - - //6. Apply the crossover to the other variables - for (int i = 0; i < variable; i++) { - - delete offSpring[0]->getDecisionVariables()[i]; - offSpring[0]->getDecisionVariables()[i] = - parent2->getDecisionVariables()[i]->deepCopy(); - - delete offSpring[1]->getDecisionVariables()[i]; - offSpring[1]->getDecisionVariables()[i] = - parent1->getDecisionVariables()[i]->deepCopy(); - - } - - //7. Decode the results - // for (int i = 0; i < offSpring[0].getDecisionVariables().length; i++) { - // ((Binary) offSpring[0].getDecisionVariables()[i]).decode(); - // ((Binary) offSpring[1].getDecisionVariables()[i]).decode(); - // } - - } // Binary or BinaryReal - - return offSpring; + offSpring[0] = new Solution(parent1); + offSpring[1] = new Solution(parent2); + + if (PseudoRandom::randDouble() < probability) + { + //1. Compute the total number of bits + int totalNumberOfBits = 0; + for (int i = 0; i < parent1->getProblem()->getNumberOfVariables(); i++) + { + totalNumberOfBits += + ((Binary *)(parent1->getDecisionVariables()[0]))->getNumberOfBits() ; + } + + //2. Calculate the point to make the crossover + int crossoverPoint = PseudoRandom::randInt(0, totalNumberOfBits - 1); + + //3. Compute the variable containing the crossoverPoint bit + int variable = 0; + int acountBits = + ((Binary *)(parent1->getDecisionVariables()[variable]))->getNumberOfBits() ; + + while (acountBits < (crossoverPoint + 1)) + { + variable++; + acountBits += + ((Binary *)(parent1->getDecisionVariables()[variable]))->getNumberOfBits() ; + } + + //4. Compute the bit into the variable selected + int diff = acountBits - crossoverPoint; + int intoVariableCrossoverPoint = + ((Binary *)(parent1->getDecisionVariables()[variable]))->getNumberOfBits() - diff; + + + //5. Make the crossover into the the gene; + Variable* offSpring1, * offSpring2; + Binary * of1, *of2 ; + offSpring1 = + ((parent1->getDecisionVariables()[variable]))->deepCopy(); + + offSpring2 = + ((parent2->getDecisionVariables()[variable]))->deepCopy(); + of1 = (Binary *)offSpring1 ; + of2 = (Binary *)offSpring2 ; + + for (int i = intoVariableCrossoverPoint; + i < of1->getNumberOfBits(); + i++) + { + bool swap = of1->getIth(i) ; + of1->setIth(i, of2->getIth(i)) ; + of2->setIth(i, swap) ; + } + + delete offSpring[0]->getDecisionVariables()[variable]; + delete offSpring[1]->getDecisionVariables()[variable]; + offSpring[0]->getDecisionVariables()[variable] = of1 ; + offSpring[1]->getDecisionVariables()[variable] = of2 ; + + //6. Apply the crossover to the other variables + for (int i = 0; i < variable; i++) + { + + delete offSpring[0]->getDecisionVariables()[i]; + offSpring[0]->getDecisionVariables()[i] = + parent2->getDecisionVariables()[i]->deepCopy(); + + delete offSpring[1]->getDecisionVariables()[i]; + offSpring[1]->getDecisionVariables()[i] = + parent1->getDecisionVariables()[i]->deepCopy(); + + } + + //7. Decode the results + // for (int i = 0; i < offSpring[0].getDecisionVariables().length; i++) { + // ((Binary) offSpring[0].getDecisionVariables()[i]).decode(); + // ((Binary) offSpring[1].getDecisionVariables()[i]).decode(); + // } + + } // Binary or BinaryReal + + return offSpring; } // doCrossover @@ -143,12 +151,13 @@ Solution ** SinglePointCrossover::doCrossover(double probability, Solution *pare * @param object An object containing an array of two parents * @return An object containing the offSprings */ -void * SinglePointCrossover::execute(void *object) { - Solution ** parents = (Solution **) object; - // TODO: Comprobar la longitud de parents - // TODO: Chequear el tipo de parents +void * SinglePointCrossover::execute(void *object) +{ + Solution ** parents = (Solution **) object; + // TODO: Comprobar la longitud de parents + // TODO: Chequear el tipo de parents - Solution ** offSpring = (Solution **)doCrossover(crossoverProbability_, parents[0], parents[1]); + Solution ** offSpring = (Solution **)doCrossover(crossoverProbability_, parents[0], parents[1]); - return offSpring; + return offSpring; } // execute diff --git a/src/operators/crossover/SinglePointCrossover.h b/src/operators/crossover/SinglePointCrossover.h index 97efbe6..a9a1b0a 100644 --- a/src/operators/crossover/SinglePointCrossover.h +++ b/src/operators/crossover/SinglePointCrossover.h @@ -30,16 +30,17 @@ * This class allows to apply a SBX crossover operator using two parent * solutions. **/ -class SinglePointCrossover : public Crossover { +class SinglePointCrossover : public Crossover +{ public: - SinglePointCrossover(map parameters); - void *execute(void *); + SinglePointCrossover(map parameters); + void *execute(void *); private: - double crossoverProbability_; - Solution ** doCrossover(double probability, - Solution * parent1, Solution * parent2); + double crossoverProbability_; + Solution ** doCrossover(double probability, + Solution * parent1, Solution * parent2); }; #endif diff --git a/src/operators/mutation/BitFlipMutation.cpp b/src/operators/mutation/BitFlipMutation.cpp index 09325ff..3e422ba 100644 --- a/src/operators/mutation/BitFlipMutation.cpp +++ b/src/operators/mutation/BitFlipMutation.cpp @@ -26,11 +26,12 @@ * Constructor * Creates a new instance of the polynomial mutation operator */ -BitFlipMutation::BitFlipMutation(map parameters) -: Mutation(parameters) { - mutationProbability_ = 0.0 ; - if (parameters["probability"] != NULL) - mutationProbability_ = *(double *) parameters["probability"]; +BitFlipMutation::BitFlipMutation(MapOfStringFunct parameters) + : Mutation(parameters) +{ + mutationProbability_ = 0.0 ; + if (parameters["probability"] != nullptr) + mutationProbability_ = *(double *) parameters["probability"]; } // BitFlipMutation @@ -45,15 +46,18 @@ BitFlipMutation::~BitFlipMutation() { } // ~BitFlipMutation * @param probability Mutation probability * @param solution The solution to mutate */ -void * BitFlipMutation::doMutation(double probability, Solution *solution) { - int numberOfVariables = solution->getNumberOfVariables() ; +void * BitFlipMutation::doMutation(double probability, Solution *solution) +{ + int numberOfVariables = solution->getNumberOfVariables() ; - for (int i = 0 ; i < numberOfVariables ; i++) { - Binary * variable = (Binary *)(solution->getDecisionVariables()[i]) ; - for (int j = 0; j < variable->getNumberOfBits() ; j++) - if (PseudoRandom::randDouble() <= mutationProbability_) - variable->flip(j) ; - } + for (int i = 0 ; i < numberOfVariables ; i++) + { + Binary * variable = (Binary *)(solution->getDecisionVariables()[i]) ; + for (int j = 0; j < variable->getNumberOfBits() ; j++) + if (PseudoRandom::randDouble() <= mutationProbability_) + variable->flip(j) ; + } + return nullptr; } // doMutation @@ -63,11 +67,12 @@ void * BitFlipMutation::doMutation(double probability, Solution *solution) { * @return An object containing the mutated solution * @throws JMException */ -void * BitFlipMutation::execute(void *object) { - Solution *solution = (Solution *)object; - // TODO: VALID_TYPES? +void * BitFlipMutation::execute(void *object) +{ + Solution *solution = (Solution *)object; + // TODO: VALID_TYPES? - doMutation(mutationProbability_, solution) ; + doMutation(mutationProbability_, solution) ; - return solution; + return solution; } // execute diff --git a/src/operators/mutation/BitFlipMutation.h b/src/operators/mutation/BitFlipMutation.h index c90148d..f32d234 100644 --- a/src/operators/mutation/BitFlipMutation.h +++ b/src/operators/mutation/BitFlipMutation.h @@ -32,17 +32,18 @@ * @class Mutation * @brief This class implements a polynomial mutation operator. **/ -class BitFlipMutation : public Mutation { +class BitFlipMutation : public Mutation +{ public: - BitFlipMutation(map parameters); - ~BitFlipMutation(); - void * execute(void *); + BitFlipMutation(MapOfStringFunct parameters); + ~BitFlipMutation(); + void * execute(void *); private: - double mutationProbability_; - // TODO: VALID_TYPES; - void * doMutation(double probability, Solution * solution); + double mutationProbability_; + // TODO: VALID_TYPES; + void * doMutation(double probability, Solution * solution); }; // BitFlipMutation diff --git a/src/operators/mutation/CMakeLists.txt b/src/operators/mutation/CMakeLists.txt new file mode 100644 index 0000000..294ec59 --- /dev/null +++ b/src/operators/mutation/CMakeLists.txt @@ -0,0 +1,3 @@ +file(GLOB SOURCES "*.cpp" "*.h") +ListToString(SOURCES ";" ${SOURCES}) +LIST_APPEND("${SOURCES}") \ No newline at end of file diff --git a/src/operators/mutation/Mutation.cpp b/src/operators/mutation/Mutation.cpp index 636cbd7..a44ebb7 100644 --- a/src/operators/mutation/Mutation.cpp +++ b/src/operators/mutation/Mutation.cpp @@ -22,7 +22,7 @@ #include -Mutation::Mutation(map parameters) -: Operator (parameters) {} +Mutation::Mutation(MapOfStringFunct parameters) + : Operator (parameters) {} Mutation::~Mutation() { /* do nothing */ } diff --git a/src/operators/mutation/Mutation.h b/src/operators/mutation/Mutation.h index 93938fa..ca0a92c 100644 --- a/src/operators/mutation/Mutation.h +++ b/src/operators/mutation/Mutation.h @@ -29,11 +29,12 @@ * @class Mutation * @brief This class is aimed at representing a Mutation operator **/ -class Mutation : public Operator{ +class Mutation : public Operator +{ public: - Mutation(map parameters); - virtual ~Mutation() = 0; + Mutation(MapOfStringFunct parameters); + virtual ~Mutation() = 0; }; diff --git a/src/operators/mutation/NonUniformMutation.cpp b/src/operators/mutation/NonUniformMutation.cpp index 494b034..9e6a397 100644 --- a/src/operators/mutation/NonUniformMutation.cpp +++ b/src/operators/mutation/NonUniformMutation.cpp @@ -2,6 +2,7 @@ // // Author: // Esteban López-Camacho +// Sérgio Vieira // // Copyright (c) 2014 Antonio J. Nebro // @@ -27,23 +28,27 @@ /** * Valid solution types to apply this operator. */ -const string NonUniformMutation::VALID_TYPES[] = {"Real", "ArrayReal"}; +const std::string NonUniformMutation::VALID_TYPES[] = {"Real", "ArrayReal"}; /** * Constructor * Creates a new instance of the non uniform mutation */ -NonUniformMutation::NonUniformMutation(map parameters) -: Mutation(parameters) { - if (parameters["probability"] != NULL) { - mutationProbability_ = *(double *) parameters["probability"]; - } - if (parameters["perturbation"] != NULL) { - perturbation_ = *(double *) parameters["perturbation"]; - } - if (parameters["maxIterations"] != NULL) { - maxIterations_ = *(int *) parameters["maxIterations"]; - } +NonUniformMutation::NonUniformMutation(MapOfStringFunct parameters) + : Mutation(parameters) +{ + if (parameters["probability"] != nullptr) + { + mutationProbability_ = *(double *) parameters["probability"]; + } + if (parameters["perturbation"] != nullptr) + { + perturbation_ = *(double *) parameters["perturbation"]; + } + if (parameters["maxIterations"] != nullptr) + { + maxIterations_ = *(int *) parameters["maxIterations"]; + } } // NonUniformMutation /** @@ -51,50 +56,73 @@ NonUniformMutation::NonUniformMutation(map parameters) * @param probability Mutation probability * @param solution The solution to mutate */ -void NonUniformMutation::doMutation(double probability, Solution *solution) { +void NonUniformMutation::doMutation(double probability, Solution *solution) +{ + XReal * x = new XReal(solution); + for (int var=0; var < solution->getNumberOfVariables(); var++) + { + double minMaxRange = ((x->getUpperBound(var) - x->getLowerBound(var)) / 2.0); + if (PseudoRandom::randDouble() < probability) + { + double rand = PseudoRandom::randDouble(); + double tmp; - XReal * x = new XReal(solution); + if (rand <= 0.5) + { + tmp = delta(x->getUpperBound(var) - x->getValue(var), + perturbation_); + tmp += x->getValue(var); + } + else + { + tmp = delta(x->getLowerBound(var) - x->getValue(var), + perturbation_); + tmp += x->getValue(var); + } - for (int var=0; var < solution->getNumberOfVariables(); var++) { - if (PseudoRandom::randDouble() < probability) { - double rand = PseudoRandom::randDouble(); - double tmp; + if (tmp < x->getLowerBound(var)) + { + //tmp = x->getLowerBound(var); + tmp = x->getLowerBound(var) + minMaxRange; + if (perturbation_ > 0.0 + && perturbation_ < 1.0) + { + double prand = PseudoRandom::randDouble() * perturbation_; + tmp = x->getLowerBound(var) + minMaxRange * prand; + } - if (rand <= 0.5) { - tmp = delta(x->getUpperBound(var) - x->getValue(var), - perturbation_); - tmp += x->getValue(var); - } else { - tmp = delta(x->getLowerBound(var) - x->getValue(var), - perturbation_); - tmp += x->getValue(var); - } + } + else if (tmp > x->getUpperBound(var)) + { + //tmp = x->getUpperBound(var); + if (perturbation_ > 0.0 + && perturbation_ < 1.0) + { + double prand = PseudoRandom::randDouble() * perturbation_; + tmp = x->getUpperBound(var) - minMaxRange * prand; + } + } - if (tmp < x->getLowerBound(var)) { - tmp = x->getLowerBound(var); - } else if (tmp > x->getUpperBound(var)) { - tmp = x->getUpperBound(var); - } + x->setValue(var, tmp) ; + } // if + } // for - x->setValue(var, tmp) ; - } // if - } // for - - delete x; + delete x; } // doMutation /** * Calculates the delta value used in NonUniform mutation operator */ -double NonUniformMutation::delta(double y, double bMutationParameter) { - double rand = PseudoRandom::randDouble(); - int it, maxIt; - it = currentIteration_; - maxIt = maxIterations_; +double NonUniformMutation::delta(double y, double bMutationParameter) +{ + double rand = PseudoRandom::randDouble(); + int it, maxIt; + it = currentIteration_; + maxIt = maxIterations_; - return (y * (1.0 - - pow(rand, pow((1.0 - it /(double) maxIt),bMutationParameter) ))); + return (y * (1.0 - + pow(rand, pow((1.0 - it /(double) maxIt),bMutationParameter) ))); } // delta /** @@ -102,12 +130,14 @@ double NonUniformMutation::delta(double y, double bMutationParameter) { * @param object An object containing a solution * @return An object containing the mutated solution */ -void *NonUniformMutation::execute(void *object) { - Solution *solution = (Solution *)object; - // TODO: VALID_TYPES? - if (getParameter("currentIteration") != NULL) { +void *NonUniformMutation::execute(void *object) +{ + Solution *solution = (Solution *)object; + // TODO: VALID_TYPES? + if (getParameter("currentIteration") != nullptr) + { currentIteration_ = *(int *) getParameter("currentIteration") ; - } - doMutation(mutationProbability_,solution); - return solution; + } + doMutation(mutationProbability_,solution); + return solution; } // execute diff --git a/src/operators/mutation/NonUniformMutation.h b/src/operators/mutation/NonUniformMutation.h index c73acd5..0999012 100644 --- a/src/operators/mutation/NonUniformMutation.h +++ b/src/operators/mutation/NonUniformMutation.h @@ -2,6 +2,7 @@ // // Author: // Esteban López-Camacho +// Sérgio Vieira // // Copyright (c) 2014 Antonio J. Nebro // @@ -29,60 +30,61 @@ /** * This class implements a non-uniform mutation operator. */ -class NonUniformMutation : public Mutation { +class NonUniformMutation : public Mutation +{ private: - /** - * Valid solution types to apply this operator. - */ - static const string VALID_TYPES[]; - - /** - * perturbation_ stores the perturbation value used in the Non Uniform - * mutation operator - */ - double perturbation_; - - /** - * maxIterations_ stores the maximun number of iterations. - */ - int maxIterations_; - - /** - * currentIteration_ stores the iteration in which the operator is going to be - * applied - */ - int currentIteration_; - - double mutationProbability_; - - /** - * Performs the operation. - * @param probability Mutation probability - * @param solution The solution to mutate - * @throws JMException - */ - void doMutation(double probability, Solution *solution); - - /** - * Calculates the delta value used in NonUniform mutation operator - */ - double delta(double y, double bMutationParameter); + /** + * Valid solution types to apply this operator. + */ + static const std::string VALID_TYPES[]; + + /** + * perturbation_ stores the perturbation value used in the Non Uniform + * mutation operator + */ + double perturbation_ = 0.0; + + /** + * maxIterations_ stores the maximun number of iterations. + */ + int maxIterations_ = 0; + + /** + * currentIteration_ stores the iteration in which the operator is going to be + * applied + */ + int currentIteration_ = 0; + + double mutationProbability_ = 0; + + /** + * Performs the operation. + * @param probability Mutation probability + * @param solution The solution to mutate + * @throws JMException + */ + void doMutation(double probability, Solution *solution); + + /** + * Calculates the delta value used in NonUniform mutation operator + */ + double delta(double y, double bMutationParameter); public: - /** - * Constructor. - * Creates a new instance of the non uniform mutation - */ - NonUniformMutation(map parameters); - - /** - * Executes the operation - * @param object An object containing the solution to mutate - */ - void *execute(void *); + /** + * Constructor. + * Creates a new instance of the non uniform mutation + */ + NonUniformMutation(MapOfStringFunct parameters); + + /** + * Executes the operation + * @param object An object containing the solution to mutate + */ + void *execute(void *); }; // NonUniformMutation diff --git a/src/operators/mutation/PolynomialMutation.cpp b/src/operators/mutation/PolynomialMutation.cpp index 58bd89b..d34775a 100644 --- a/src/operators/mutation/PolynomialMutation.cpp +++ b/src/operators/mutation/PolynomialMutation.cpp @@ -32,14 +32,15 @@ const double PolynomialMutation::eta_m_ = ETA_M_DEFAULT_; * Constructor * Creates a new instance of the polynomial mutation operator */ -PolynomialMutation::PolynomialMutation(map parameters) -: Mutation(parameters) { - // TODO: mutationProbability_ = NULL; - distributionIndex_ = eta_m_; - if (parameters["probability"] != NULL) - mutationProbability_ = *(double *) parameters["probability"]; - if (parameters["distributionIndex"] != NULL) - distributionIndex_ = *(double *) parameters["distributionIndex"]; +PolynomialMutation::PolynomialMutation(MapOfStringFunct parameters) + : Mutation(parameters) +{ + // TODO: mutationProbability_ = nullptr; + distributionIndex_ = eta_m_; + if (parameters["probability"] != nullptr) + mutationProbability_ = *(double *) parameters["probability"]; + if (parameters["distributionIndex"] != nullptr) + distributionIndex_ = *(double *) parameters["distributionIndex"]; } // PolynomialMutation @@ -54,40 +55,46 @@ PolynomialMutation::~PolynomialMutation() { } // ~PolynomialMutation * @param probability Mutation probability * @param solution The solution to mutate */ -void * PolynomialMutation::doMutation(double probability, Solution *solution) { - double rnd, delta1, delta2, mut_pow, deltaq; - double y, yl, yu, val, xy; - XReal * x = new XReal(solution); - - for (int var=0; var < solution->getNumberOfVariables(); var++) { - if (PseudoRandom::randDouble() <= probability) { - y = x->getValue(var); - yl = x->getLowerBound(var); - yu = x->getUpperBound(var); - delta1 = (y-yl)/(yu-yl); - delta2 = (yu-y)/(yu-yl); - rnd = PseudoRandom::randDouble(); - mut_pow = 1.0/(distributionIndex_+1.0); - if (rnd <= 0.5) { - xy = 1.0-delta1; - val = 2.0*rnd+(1.0-2.0*rnd)*(pow(xy,(eta_m_+1.0))); - deltaq = pow(val,mut_pow) - 1.0; - } else { - xy = 1.0-delta2; - val = 2.0*(1.0-rnd)+2.0*(rnd-0.5)*(pow(xy,(eta_m_+1.0))); - deltaq = 1.0 - (pow(val,mut_pow)); - } - y = y + deltaq*(yu-yl); - if (yyu) - y = yu; - x->setValue(var, y); - } - } // for +void * PolynomialMutation::doMutation(double probability, Solution *solution) +{ + double rnd, delta1, delta2, mut_pow, deltaq; + double y, yl, yu, val, xy; + XReal * x = new XReal(solution); - delete x; + for (int var=0; var < solution->getNumberOfVariables(); var++) + { + if (PseudoRandom::randDouble() <= probability) + { + y = x->getValue(var); + yl = x->getLowerBound(var); + yu = x->getUpperBound(var); + delta1 = (y-yl)/(yu-yl); + delta2 = (yu-y)/(yu-yl); + rnd = PseudoRandom::randDouble(); + mut_pow = 1.0/(distributionIndex_+1.0); + if (rnd <= 0.5) + { + xy = 1.0-delta1; + val = 2.0*rnd+(1.0-2.0*rnd)*(pow(xy,(eta_m_+1.0))); + deltaq = pow(val,mut_pow) - 1.0; + } + else + { + xy = 1.0-delta2; + val = 2.0*(1.0-rnd)+2.0*(rnd-0.5)*(pow(xy,(eta_m_+1.0))); + deltaq = 1.0 - (pow(val,mut_pow)); + } + y = y + deltaq*(yu-yl); + if (yyu) + y = yu; + x->setValue(var, y); + } + } // for + delete x; + return nullptr; } // doMutation @@ -95,12 +102,13 @@ void * PolynomialMutation::doMutation(double probability, Solution *solution) { * Executes the operation * @param object An object containing a solution * @return An object containing the mutated solution - * @throws JMException - */ -void * PolynomialMutation::execute(void *object) { - Solution *solution = (Solution *)object; - // TODO: VALID_TYPES? - //double probability = *(double *)getParameter("probability"); - doMutation(mutationProbability_,solution); - return solution; + * @throws JMException + */ +void * PolynomialMutation::execute(void *object) +{ + Solution *solution = (Solution *)object; + // TODO: VALID_TYPES? + //double probability = *(double *)getParameter("probability"); + doMutation(mutationProbability_,solution); + return solution; } // execute diff --git a/src/operators/mutation/PolynomialMutation.h b/src/operators/mutation/PolynomialMutation.h index af88bfe..3b0792d 100644 --- a/src/operators/mutation/PolynomialMutation.h +++ b/src/operators/mutation/PolynomialMutation.h @@ -34,24 +34,25 @@ * @class Mutation * @brief This class implements a polynomial mutation operator. **/ -class PolynomialMutation : public Mutation { +class PolynomialMutation : public Mutation +{ public: - static const double ETA_M_DEFAULT_; - static const double eta_m_; + static const double ETA_M_DEFAULT_; + static const double eta_m_; - PolynomialMutation(map parameters); - ~PolynomialMutation(); + PolynomialMutation(MapOfStringFunct parameters); + ~PolynomialMutation(); - void * execute(void *); + void * execute(void *); private: - double mutationProbability_; - double distributionIndex_; + double mutationProbability_; + double distributionIndex_; - void * doMutation(double probability, Solution * solution); - // TODO: VALID_TYPES; + void * doMutation(double probability, Solution * solution); + // TODO: VALID_TYPES; }; // PolynomialMutation diff --git a/src/operators/mutation/RangeMutation.cpp b/src/operators/mutation/RangeMutation.cpp new file mode 100644 index 0000000..e78115d --- /dev/null +++ b/src/operators/mutation/RangeMutation.cpp @@ -0,0 +1,72 @@ +#include "RangeMutation.h" + +RangeMutation::RangeMutation(MapOfStringFunct parameters): Mutation(parameters) +{ + if (parameters["probability"] != nullptr) + { + mutationProbability_ = *(double *)parameters["probability"]; + } + if (parameters["perturbation"] != nullptr) + { + perturbation_ = *(double *)parameters["perturbation"]; + } + if (parameters["zone_index"] != nullptr) + { + zoneIndex_ = *(MatrixOfShort *)parameters["zone_index"]; + } +} + +void RangeMutation::doMutation(double probability, Solution * solution) +{ + XReal * x = new XReal(solution); + for (auto row : zoneIndex_) + { + for (auto col: row) + { + if (PseudoRandom::randDouble() < probability) + { + double tmp = doPertubation(x, col); + x->setValue(col, tmp); + } + } + } + delete x; +} + +double RangeMutation::doPertubation(XReal* array, short col) +{ + double rand = PseudoRandom::randDouble(); + double tmp = (rand - 0.5) * perturbation_; + tmp += array->getValue(col); + double minMaxRange = ((array->getUpperBound(col) - array->getLowerBound(col)) / 2.0); + if (tmp < array->getLowerBound(col)) + { + //tmp = array->getLowerBound(col); + tmp = array->getLowerBound(col) + minMaxRange; + if (perturbation_ > 0.0 + && perturbation_ < 1.0) + { + double prand = PseudoRandom::randDouble() * perturbation_; + tmp = array->getLowerBound(col) + minMaxRange * prand; + } + } + else if (tmp > array->getUpperBound(col)) + { + //tmp = array->getUpperBound(col); + tmp = array->getUpperBound(col) - minMaxRange; + if (perturbation_ > 0.0 + && perturbation_ < 1.0) + { + double prand = PseudoRandom::randDouble() * perturbation_; + tmp = array->getUpperBound(col) - minMaxRange * prand; + } + } + return tmp; +} + +void * RangeMutation::execute(void * object) +{ + Solution *solution = (Solution *)object; + doMutation(mutationProbability_, solution); + return solution; +} diff --git a/src/operators/mutation/RangeMutation.h b/src/operators/mutation/RangeMutation.h new file mode 100644 index 0000000..0c86aa1 --- /dev/null +++ b/src/operators/mutation/RangeMutation.h @@ -0,0 +1,67 @@ +// UniformMutation.h +// +// Author: +// Sérgio Vieira +// +// Copyright (c) 2014 Antonio J. Nebro +// +// This program is free software: you can redistribute it and/or modify +// it under the terms of the GNU Lesser General Public License as published by +// the Free Software Foundation, either version 3 of the License, or +// (at your option) any later version. +// +// This program is distributed in the hope that it will be useful, +// but WITHOUT ANY WARRANTY; without even the implied warranty of +// MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the +// GNU Lesser General Public License for more details. +// +// You should have received a copy of the GNU Lesser General Public License +// along with this program. If not, see . + +#ifndef __RANGE_MUTATION__ +#define __RANGE_MUTATION__ + +#include +#include +#include +#include + +/** +* This class implements a uniform mutation operator. +*/ +class RangeMutation : public Mutation +{ +protected: + /** + * Stores the value used in a range mutation operator. + */ + double perturbation_ = 0.0; + double mutationProbability_ = 0.0; + MatrixOfShort zoneIndex_; + /** + * Performs the operation. + * @param probability Mutation probability + * @param solution The solution to mutate + * @throws JMException + */ + void doMutation(double probability, Solution *solution); + /** + * Creates a valid random pertubation + **/ + double doPertubation(XReal* array, short col); +public: + /** + * Constructor. + * Creates a new range mutation operator instance. + */ + RangeMutation(MapOfStringFunct parameters); + + /** + * Executes the operation + * @param object An object containing the solution to mutate + */ + void *execute(void *); + +}; // Range Mutation + +#endif diff --git a/src/operators/mutation/UniformMutation.cpp b/src/operators/mutation/UniformMutation.cpp index bd19a26..e381704 100644 --- a/src/operators/mutation/UniformMutation.cpp +++ b/src/operators/mutation/UniformMutation.cpp @@ -27,20 +27,23 @@ /** * Valid solution types to apply this operator. */ -const string UniformMutation::VALID_TYPES[] = {"Real", "ArrayReal"}; +const std::string UniformMutation::VALID_TYPES[] = {"Real", "ArrayReal"}; /** * Constructor * Creates a new uniform mutation operator instance */ -UniformMutation::UniformMutation(map parameters) -: Mutation(parameters) { - if (parameters["probability"] != NULL) { - mutationProbability_ = *(double *) parameters["probability"]; - } - if (parameters["perturbation"] != NULL) { - perturbation_ = *(double *) parameters["perturbation"]; - } +UniformMutation::UniformMutation(MapOfStringFunct parameters) + : Mutation(parameters) +{ + if (parameters["probability"] != nullptr) + { + mutationProbability_ = *(double *) parameters["probability"]; + } + if (parameters["perturbation"] != nullptr) + { + perturbation_ = *(double *) parameters["perturbation"]; + } } // UniformMutation /** @@ -48,28 +51,49 @@ UniformMutation::UniformMutation(map parameters) * @param probability Mutation probability * @param solution The solution to mutate */ -void UniformMutation::doMutation(double probability, Solution *solution) { +void UniformMutation::doMutation(double probability, Solution *solution) +{ - XReal * x = new XReal(solution); + XReal * x = new XReal(solution); - for (int var=0; var < solution->getNumberOfVariables(); var++) { - if (PseudoRandom::randDouble() < probability) { - double rand = PseudoRandom::randDouble(); - double tmp = (rand - 0.5)*perturbation_; + for (int var=0; var < solution->getNumberOfVariables(); var++) + { + double minMaxRange = ((x->getUpperBound(var) - x->getLowerBound(var)) / 2.0); + if (PseudoRandom::randDouble() < probability) + { + double rand = PseudoRandom::randDouble(); + double tmp = (rand - 0.5)*perturbation_; - tmp += x->getValue(var); + tmp += x->getValue(var); - if (tmp < x->getLowerBound(var)) { - tmp = x->getLowerBound(var); - } else if (tmp > x->getUpperBound(var)) { - tmp = x->getUpperBound(var); - } + if (tmp < x->getLowerBound(var)) + { + //tmp = x->getLowerBound(var); + tmp = x->getLowerBound(var) + minMaxRange; + if (perturbation_ > 0.0 + && perturbation_ < 1.0) + { + double prand = PseudoRandom::randDouble() * perturbation_; + tmp = x->getLowerBound(var) + minMaxRange * prand; + } - x->setValue(var, tmp) ; - } // if - } // for + } + else if (tmp > x->getUpperBound(var)) + { + //tmp = x->getUpperBound(var); + if (perturbation_ > 0.0 + && perturbation_ < 1.0) + { + double prand = PseudoRandom::randDouble() * perturbation_; + tmp = x->getUpperBound(var) - minMaxRange * prand; + } + } - delete x; + x->setValue(var, tmp) ; + } // if + } // for + + delete x; } // doMutation @@ -78,9 +102,10 @@ void UniformMutation::doMutation(double probability, Solution *solution) { * @param object An object containing a solution * @return An object containing the mutated solution */ -void *UniformMutation::execute(void *object) { - Solution *solution = (Solution *)object; - // TODO: VALID_TYPES? - doMutation(mutationProbability_,solution); - return solution; +void *UniformMutation::execute(void *object) +{ + Solution *solution = (Solution *)object; + // TODO: VALID_TYPES? + doMutation(mutationProbability_,solution); + return solution; } // execute diff --git a/src/operators/mutation/UniformMutation.h b/src/operators/mutation/UniformMutation.h index 0a38399..88db048 100644 --- a/src/operators/mutation/UniformMutation.h +++ b/src/operators/mutation/UniformMutation.h @@ -29,43 +29,44 @@ /** * This class implements a uniform mutation operator. */ -class UniformMutation : public Mutation { +class UniformMutation : public Mutation +{ private: - /** - * Valid solution types to apply this operator. - */ - static const string VALID_TYPES[]; + /** + * Valid solution types to apply this operator. + */ + static const string VALID_TYPES[]; - /** - * Stores the value used in a uniform mutation operator. - */ - double perturbation_; + /** + * Stores the value used in a uniform mutation operator. + */ + double perturbation_; - double mutationProbability_; + double mutationProbability_; - /** - * Performs the operation. - * @param probability Mutation probability - * @param solution The solution to mutate - * @throws JMException - */ - void doMutation(double probability, Solution *solution); + /** + * Performs the operation. + * @param probability Mutation probability + * @param solution The solution to mutate + * @throws JMException + */ + void doMutation(double probability, Solution *solution); public: - /** - * Constructor. - * Creates a new uniform mutation operator instance. - */ - UniformMutation(map parameters); + /** + * Constructor. + * Creates a new uniform mutation operator instance. + */ + UniformMutation(map parameters); - /** - * Executes the operation - * @param object An object containing the solution to mutate - */ - void *execute(void *); + /** + * Executes the operation + * @param object An object containing the solution to mutate + */ + void *execute(void *); }; // UniformMutation diff --git a/src/operators/selection/BestSolutionSelection.cpp b/src/operators/selection/BestSolutionSelection.cpp index 657b155..593c069 100644 --- a/src/operators/selection/BestSolutionSelection.cpp +++ b/src/operators/selection/BestSolutionSelection.cpp @@ -31,12 +31,14 @@ /** * Constructor */ -BestSolutionSelection::BestSolutionSelection(map parameters) -: Selection(parameters) { - comparator_ = NULL; - if (parameters["comparator"] != NULL) { - comparator_ = (Comparator *) parameters["comparator"]; - } +BestSolutionSelection::BestSolutionSelection(MapOfStringFunct parameters) + : Selection(parameters) +{ + comparator_ = nullptr; + if (parameters["comparator"] != nullptr) + { + comparator_ = (Comparator *) parameters["comparator"]; + } } @@ -45,23 +47,27 @@ BestSolutionSelection::BestSolutionSelection(map parameters) * @param object Object representing a SolutionSet * @return the best solution found */ -void * BestSolutionSelection::execute(void * object) { +void * BestSolutionSelection::execute(void * object) +{ - SolutionSet * solutionSet = (SolutionSet *)object; + SolutionSet * solutionSet = (SolutionSet *)object; - if (solutionSet->size() == 0) { - return NULL; - } + if (solutionSet->size() == 0) + { + return nullptr; + } - int bestSolution = 0; + int bestSolution = 0; - for (int i = 1; i < solutionSet->size(); i++) { - if (comparator_->compare(solutionSet->get(i), solutionSet->get(bestSolution)) < 0) { - bestSolution = i; - } - } // for + for (int i = 1; i < solutionSet->size(); i++) + { + if (comparator_->compare(solutionSet->get(i), solutionSet->get(bestSolution)) < 0) + { + bestSolution = i; + } + } // for - int * intPtr = new int(bestSolution); - return intPtr; + int * intPtr = snew int(bestSolution); + return intPtr; } // execute diff --git a/src/operators/selection/BestSolutionSelection.h b/src/operators/selection/BestSolutionSelection.h index c3a2322..a8275a0 100644 --- a/src/operators/selection/BestSolutionSelection.h +++ b/src/operators/selection/BestSolutionSelection.h @@ -29,14 +29,15 @@ * This class implements a selection operator used for selecting the best * solution in a SolutionSet according to a given comparator */ -class BestSolutionSelection : public Selection { +class BestSolutionSelection : public Selection +{ private: - Comparator * comparator_; + Comparator * comparator_; public: - BestSolutionSelection(map parameters); - void *execute(void *); + BestSolutionSelection(MapOfStringFunct parameters); + void *execute(void *); }; diff --git a/src/operators/selection/BinaryTournament.cpp b/src/operators/selection/BinaryTournament.cpp index ecc346d..1342ab2 100644 --- a/src/operators/selection/BinaryTournament.cpp +++ b/src/operators/selection/BinaryTournament.cpp @@ -32,20 +32,22 @@ * Constructor * Creates a new Binary tournament operator using a BinaryTournamentComparator */ -BinaryTournament::BinaryTournament(map parameters) -: Selection(parameters) { - if (parameters["comparator"] != NULL) - comparator_ = (Comparator *) parameters["comparator"]; - else - comparator_ = new DominanceComparator(); +BinaryTournament::BinaryTournament(MapOfStringFunct parameters) + : Selection(parameters) +{ + if (parameters["comparator"] != nullptr) + comparator_ = (Comparator *) parameters["comparator"]; + else + comparator_ = snew DominanceComparator(); } // BinaryTournament /** * Destructor */ -BinaryTournament::~BinaryTournament() { - delete comparator_; +BinaryTournament::~BinaryTournament() +{ + delete comparator_; } // ~BinaryTournament @@ -54,30 +56,32 @@ BinaryTournament::~BinaryTournament() { * @param object Object representing a SolutionSet * @return the selected solution */ -void * BinaryTournament::execute(void * object) { +void * BinaryTournament::execute(void * object) +{ - SolutionSet * solutionSet = (SolutionSet *) object; - int index1 = PseudoRandom::randInt(0,solutionSet->size()-1); - int index2 = PseudoRandom::randInt(0,solutionSet->size()-1); + SolutionSet * solutionSet = (SolutionSet *) object; + int index1 = PseudoRandom::randInt(0,solutionSet->size()-1); + int index2 = PseudoRandom::randInt(0,solutionSet->size()-1); - if (solutionSet->size() >= 2) { - while (index1 == index2) { - index2 = PseudoRandom::randInt(0,solutionSet->size()-1); + if (solutionSet->size() >= 2) + { + while (index1 == index2) + { + index2 = PseudoRandom::randInt(0,solutionSet->size()-1); + } } - } - Solution * solution1 = solutionSet->get(index1); - Solution * solution2 = solutionSet->get(index2); + Solution * solution1 = solutionSet->get(index1); + Solution * solution2 = solutionSet->get(index2); - int flag = comparator_->compare(solution1,solution2); - if (flag == -1) - return solution1; - else if (flag == 1) - return solution2; - else - if (PseudoRandom::randDouble()<0.5) - return solution1; + int flag = comparator_->compare(solution1,solution2); + if (flag == -1) + return solution1; + else if (flag == 1) + return solution2; + else if (PseudoRandom::randDouble()<0.5) + return solution1; else - return solution2; + return solution2; } // execute diff --git a/src/operators/selection/BinaryTournament.h b/src/operators/selection/BinaryTournament.h index 9dc94dd..74a0a6e 100644 --- a/src/operators/selection/BinaryTournament.h +++ b/src/operators/selection/BinaryTournament.h @@ -30,15 +30,16 @@ /** * This class implements an binary tournament selection operator */ -class BinaryTournament : public Selection { +class BinaryTournament : public Selection +{ private: - Comparator * comparator_; + Comparator * comparator_; public: - BinaryTournament(map parameters); - ~BinaryTournament(); - void *execute(void *); + BinaryTournament(MapOfStringFunct parameters); + ~BinaryTournament(); + void *execute(void *); }; diff --git a/src/operators/selection/BinaryTournament2.cpp b/src/operators/selection/BinaryTournament2.cpp index 4333794..cf7c27b 100644 --- a/src/operators/selection/BinaryTournament2.cpp +++ b/src/operators/selection/BinaryTournament2.cpp @@ -35,65 +35,68 @@ * Creates a new instance of the Binary tournament operator (Deb's * NSGA-II implementation version) */ -BinaryTournament2::BinaryTournament2(map parameters) -: Selection(parameters) { - index_ = 0; - a_ = new int[1]; // Initialized as dummy - dominance_ = new DominanceComparator(); - if (dominance_ == NULL) { - cout << "BinaryTournament::BinaryTournament: error creating comparator" ; - cout << endl ; - exit(-1) ; - } +BinaryTournament2::BinaryTournament2(MapOfStringFunct parameters) + : Selection(parameters) +{ + index_ = 0; + a_ = snew int[1]; // Initialized as dummy + dominance_ = snew DominanceComparator(); + if (dominance_ == nullptr) + { + std::cout << "BinaryTournament::BinaryTournament: error creating comparator" ; + std::cout << std::endl ; + exit(-1) ; + } } /** * Destructor */ -BinaryTournament2::~BinaryTournament2() { - delete dominance_; - delete [] a_; +BinaryTournament2::~BinaryTournament2() +{ + delete dominance_; + delete [] a_; } // ~BinaryTournament2 - + /** * Performs the operation * @param object Object representing a SolutionSet * @return the selected solution */ -void * BinaryTournament2::execute(void * object) { +void * BinaryTournament2::execute(void * object) +{ - SolutionSet * population = (SolutionSet *)object; + SolutionSet * population = (SolutionSet *)object; - if (index_ == 0) //Create the permutation - { - PermutationUtility * permutationUtility = new PermutationUtility(); - delete [] a_; - a_= permutationUtility->intPermutation(population->size()); - delete permutationUtility; - } - - Solution * solution1; - Solution * solution2; - solution1 = population->get(a_[index_]); - solution2 = population->get(a_[index_+1]); - - index_ = (index_ + 2) % population->size(); - - int flag = dominance_->compare(solution1,solution2); - if (flag == -1) - return solution1; - else if (flag == 1) - return solution2; - else if (solution1->getCrowdingDistance() > solution2->getCrowdingDistance()) - return solution1; - else if (solution2->getCrowdingDistance() > solution1->getCrowdingDistance()) - return solution2; - else - if (PseudoRandom::randDouble()<0.5) - return solution1; + if (index_ == 0) //Create the permutation + { + PermutationUtility * permutationUtility = snew PermutationUtility(); + delete [] a_; + a_= permutationUtility->intPermutation(population->size()); + delete permutationUtility; + } + + Solution * solution1; + Solution * solution2; + solution1 = population->get(a_[index_]); + solution2 = population->get(a_[index_+1]); + + index_ = (index_ + 2) % population->size(); + + int flag = dominance_->compare(solution1,solution2); + if (flag == -1) + return solution1; + else if (flag == 1) + return solution2; + else if (solution1->getCrowdingDistance() > solution2->getCrowdingDistance()) + return solution1; + else if (solution2->getCrowdingDistance() > solution1->getCrowdingDistance()) + return solution2; + else if (PseudoRandom::randDouble()<0.5) + return solution1; else - return solution2; + return solution2; -} // execute +} // execute diff --git a/src/operators/selection/BinaryTournament2.h b/src/operators/selection/BinaryTournament2.h index 310a61b..29a42b0 100644 --- a/src/operators/selection/BinaryTournament2.h +++ b/src/operators/selection/BinaryTournament2.h @@ -33,17 +33,18 @@ * This class implements an operator for binary selections using the same code * in Deb's NSGA-II implementation */ -class BinaryTournament2 : public Selection { +class BinaryTournament2 : public Selection +{ private: - Comparator * dominance_; - int * a_; - int index_; + Comparator * dominance_; + int * a_; + int index_; public: - BinaryTournament2(map parameters); - ~BinaryTournament2(); - void *execute(void *); + BinaryTournament2(MapOfStringFunct parameters); + ~BinaryTournament2(); + void *execute(void *); }; diff --git a/src/operators/selection/CMakeLists.txt b/src/operators/selection/CMakeLists.txt new file mode 100644 index 0000000..294ec59 --- /dev/null +++ b/src/operators/selection/CMakeLists.txt @@ -0,0 +1,3 @@ +file(GLOB SOURCES "*.cpp" "*.h") +ListToString(SOURCES ";" ${SOURCES}) +LIST_APPEND("${SOURCES}") \ No newline at end of file diff --git a/src/operators/selection/DifferentialEvolutionSelection.cpp b/src/operators/selection/DifferentialEvolutionSelection.cpp index e25fd77..31227ce 100644 --- a/src/operators/selection/DifferentialEvolutionSelection.cpp +++ b/src/operators/selection/DifferentialEvolutionSelection.cpp @@ -32,8 +32,8 @@ /** * Constructor */ -DifferentialEvolutionSelection::DifferentialEvolutionSelection(map parameters) -: Selection(parameters) {} +DifferentialEvolutionSelection::DifferentialEvolutionSelection(MapOfStringFunct parameters) + : Selection(parameters) {} /** @@ -42,34 +42,42 @@ DifferentialEvolutionSelection::DifferentialEvolutionSelection(mapsize() < 4) { - cerr << "DifferentialEvolutionSelection: the population has less than four solutions" << endl; - exit(-1); - } + if (population->size() < 4) + { + cerr << "DifferentialEvolutionSelection: the population has less than four solutions" << std::endl; + exit(-1); + } - do { - r1 = PseudoRandom::randInt(0,population->size()-1); - } while ( r1==index ); - do { - r2 = PseudoRandom::randInt(0,population->size()-1); - } while ( r2==index || r2==r1 ); - do { - r3 = PseudoRandom::randInt(0,population->size()-1); - } while( r3==index || r3==r1 || r3==r2 ); + do + { + r1 = PseudoRandom::randInt(0,population->size()-1); + } + while ( r1==index ); + do + { + r2 = PseudoRandom::randInt(0,population->size()-1); + } + while ( r2==index || r2==r1 ); + do + { + r3 = PseudoRandom::randInt(0,population->size()-1); + } + while( r3==index || r3==r1 || r3==r2 ); - parents[0] = population->get(r1); - parents[1] = population->get(r2); - parents[2] = population->get(r3); + parents[0] = population->get(r1); + parents[1] = population->get(r2); + parents[2] = population->get(r3); - return parents ; + return parents ; } // execute diff --git a/src/operators/selection/DifferentialEvolutionSelection.h b/src/operators/selection/DifferentialEvolutionSelection.h index 98db269..92db92c 100644 --- a/src/operators/selection/DifferentialEvolutionSelection.h +++ b/src/operators/selection/DifferentialEvolutionSelection.h @@ -30,11 +30,12 @@ * Class implementing the selection operator used in DE: three different solutions * are returned from a population. */ -class DifferentialEvolutionSelection : public Selection { +class DifferentialEvolutionSelection : public Selection +{ public: - DifferentialEvolutionSelection(map parameters); - void *execute(void *); + DifferentialEvolutionSelection(MapOfStringFunct parameters); + void *execute(void *); }; diff --git a/src/operators/selection/RandomSelection.cpp b/src/operators/selection/RandomSelection.cpp index 5f86633..32fa95c 100755 --- a/src/operators/selection/RandomSelection.cpp +++ b/src/operators/selection/RandomSelection.cpp @@ -32,7 +32,8 @@ * Constructor * Creates a new RandomSelection operator using a BinaryTournamentComparator */ -RandomSelection::RandomSelection(map parameters): Selection(parameters) { +RandomSelection::RandomSelection(MapOfStringFunct parameters): Selection(parameters) +{ } // RandomSelection @@ -47,20 +48,22 @@ RandomSelection::~RandomSelection() { } // ~RandomSelection * @param object Object representing a SolutionSet. * @return an object representing an array with the selected parents */ -void * RandomSelection::execute(void * object) { +void * RandomSelection::execute(void * object) +{ - SolutionSet * population = (SolutionSet *) object; - int pos1 = PseudoRandom::randInt(0,population->size()-1); - int pos2 = PseudoRandom::randInt(0,population->size()-1); + SolutionSet * population = (SolutionSet *) object; + int pos1 = PseudoRandom::randInt(0,population->size()-1); + int pos2 = PseudoRandom::randInt(0,population->size()-1); - while ((pos1 == pos2) && (population->size()>1) ) { - pos2 = PseudoRandom::randInt(0,population->size()-1); - } + while ((pos1 == pos2) && (population->size()>1) ) + { + pos2 = PseudoRandom::randInt(0,population->size()-1); + } - Solution ** parents = new Solution*[2]; - parents[0] = population->get(pos1); - parents[1] = population->get(pos2); - return parents; + Solution ** parents = new Solution*[2]; + parents[0] = population->get(pos1); + parents[1] = population->get(pos2); + return parents; } // execute diff --git a/src/operators/selection/RandomSelection.h b/src/operators/selection/RandomSelection.h index 547fe38..e7e2fb1 100755 --- a/src/operators/selection/RandomSelection.h +++ b/src/operators/selection/RandomSelection.h @@ -30,15 +30,16 @@ /** * This class implements an binary tournament selection operator */ -class RandomSelection : public Selection { +class RandomSelection : public Selection +{ private: - Comparator * comparator_; + Comparator * comparator_; public: - RandomSelection(map parameters); - ~RandomSelection(); - void *execute(void *); + RandomSelection(MapOfStringFunct parameters); + ~RandomSelection(); + void *execute(void *); }; diff --git a/src/operators/selection/Selection.cpp b/src/operators/selection/Selection.cpp index cf847a3..5a41468 100644 --- a/src/operators/selection/Selection.cpp +++ b/src/operators/selection/Selection.cpp @@ -22,7 +22,7 @@ #include -Selection::Selection(map parameters) -: Operator(parameters) {} +Selection::Selection(MapOfStringFunct parameters) + : Operator(parameters) {} Selection::~Selection() { /* do nothing */ } diff --git a/src/operators/selection/Selection.h b/src/operators/selection/Selection.h index 7de1178..6cf6ee1 100644 --- a/src/operators/selection/Selection.h +++ b/src/operators/selection/Selection.h @@ -29,11 +29,12 @@ * @class Selection * @brief This class is aimed at representing a Selection operator **/ -class Selection : public Operator { +class Selection : public Operator +{ public: - Selection (map parameters); - virtual ~Selection() = 0; + Selection (MapOfStringFunct parameters); + virtual ~Selection() = 0; }; #endif diff --git a/src/operators/selection/WorstSolutionSelection.cpp b/src/operators/selection/WorstSolutionSelection.cpp index 9d17d8d..4032c33 100644 --- a/src/operators/selection/WorstSolutionSelection.cpp +++ b/src/operators/selection/WorstSolutionSelection.cpp @@ -31,12 +31,14 @@ /** * Constructor */ -WorstSolutionSelection::WorstSolutionSelection(map parameters) -: Selection(parameters) { - comparator_ = NULL; - if (parameters["comparator"] != NULL) { - comparator_ = (Comparator *) parameters["comparator"]; - } +WorstSolutionSelection::WorstSolutionSelection(MapOfStringFunct parameters) + : Selection(parameters) +{ + comparator_ = nullptr; + if (parameters["comparator"] != nullptr) + { + comparator_ = (Comparator *) parameters["comparator"]; + } } @@ -45,23 +47,27 @@ WorstSolutionSelection::WorstSolutionSelection(map parameters) * @param object Object representing a SolutionSet * @return the worst solution found */ -void * WorstSolutionSelection::execute(void * object) { +void * WorstSolutionSelection::execute(void * object) +{ - SolutionSet * solutionSet = (SolutionSet *)object; + SolutionSet * solutionSet = (SolutionSet *)object; - if (solutionSet->size() == 0) { - return NULL; - } + if (solutionSet->size() == 0) + { + return nullptr; + } - int worstSolution = 0; + int worstSolution = 0; - for (int i = 1; i < solutionSet->size(); i++) { - if (comparator_->compare(solutionSet->get(i), solutionSet->get(worstSolution)) > 0) { - worstSolution = i; - } - } // for + for (int i = 1; i < solutionSet->size(); i++) + { + if (comparator_->compare(solutionSet->get(i), solutionSet->get(worstSolution)) > 0) + { + worstSolution = i; + } + } // for - int * intPtr = new int(worstSolution); - return intPtr; + int * intPtr = snew int(worstSolution); + return intPtr; } // execute diff --git a/src/operators/selection/WorstSolutionSelection.h b/src/operators/selection/WorstSolutionSelection.h index acb3c15..2ba8ae8 100644 --- a/src/operators/selection/WorstSolutionSelection.h +++ b/src/operators/selection/WorstSolutionSelection.h @@ -29,14 +29,15 @@ * This class implements a selection operator used for selecting the worst * solution in a SolutionSet according to a given comparator */ -class WorstSolutionSelection : public Selection { +class WorstSolutionSelection : public Selection +{ private: - Comparator * comparator_; + Comparator * comparator_; public: - WorstSolutionSelection(map parameters); - void *execute(void *); + WorstSolutionSelection(map parameters); + void *execute(void *); }; diff --git a/src/problems/CMakeLists.txt b/src/problems/CMakeLists.txt new file mode 100644 index 0000000..97b2150 --- /dev/null +++ b/src/problems/CMakeLists.txt @@ -0,0 +1,8 @@ +file(GLOB SOURCES "*.cpp" "*.h") +ListToString(SOURCES ";" ${SOURCES}) +LIST_APPEND("${SOURCES}") +add_subdirectory(DTLZ) +add_subdirectory(LZ09) +add_subdirectory(singleObjective) +add_subdirectory(ZDT) +add_subdirectory(SIGA) \ No newline at end of file diff --git a/src/problems/DTLZ/CMakeLists.txt b/src/problems/DTLZ/CMakeLists.txt new file mode 100644 index 0000000..294ec59 --- /dev/null +++ b/src/problems/DTLZ/CMakeLists.txt @@ -0,0 +1,3 @@ +file(GLOB SOURCES "*.cpp" "*.h") +ListToString(SOURCES ";" ${SOURCES}) +LIST_APPEND("${SOURCES}") \ No newline at end of file diff --git a/src/problems/DTLZ/DTLZ1.cpp b/src/problems/DTLZ/DTLZ1.cpp index c9087a2..a8ba843 100644 --- a/src/problems/DTLZ/DTLZ1.cpp +++ b/src/problems/DTLZ/DTLZ1.cpp @@ -22,86 +22,96 @@ const double DTLZ1::PI = 3.141592653589793; -DTLZ1::DTLZ1(string solutionType, int numberOfVariables, int numberOfObjectives) { - numberOfVariables_ = numberOfVariables; - numberOfObjectives_ = numberOfObjectives; - numberOfConstraints_ = 0; - problemName_ = "DTLZ1"; - - lowerLimit_ = new double[numberOfVariables_];//(double *)malloc(sizeof(double)*numberOfVariables); - if (lowerLimit_ == NULL) { - cout << "Impossible to reserve memory for storing the variable lower limits" << endl; - exit(-1); - } - - upperLimit_ = new double[numberOfVariables_];//(double *)malloc(sizeof(double)*numberOfVariables); - if (upperLimit_ == NULL) { - cout << "Impossible to reserve memory for storing the variable lower limits" << endl; - exit(-1); - } - - for (int i = 0; i < numberOfVariables_; i++) { - lowerLimit_[i] = 0.0; - upperLimit_[i] = 1.0; - } - - if (solutionType.compare("BinaryReal") == 0) - solutionType_ = new BinaryRealSolutionType(this) ; - else if (solutionType.compare("Real") == 0) { - solutionType_ = new RealSolutionType(this) ; - //cout << "Tipo seleccionado Real" << endl; - } - else if (solutionType.compare("ArrayReal") == 0) - solutionType_ = new ArrayRealSolutionType(this) ; - else { - cout << "Error: solution type " << solutionType << " invalid" << endl; - exit(-1) ; - } - - fx_ = new double[numberOfObjectives_] ; - x_ = new double[numberOfVariables_]; +DTLZ1::DTLZ1(std::string solutionType, int numberOfVariables, int numberOfObjectives) +{ + numberOfVariables_ = numberOfVariables; + numberOfObjectives_ = numberOfObjectives; + numberOfConstraints_ = 0; + problemName_ = "DTLZ1"; + + lowerLimit_ = snew double[numberOfVariables_];//(double *)malloc(sizeof(double)*numberOfVariables); + if (lowerLimit_ == nullptr) + { + std::cout << "Impossible to reserve memory for storing the variable lower limits" << std::endl; + exit(-1); + } + + upperLimit_ = snew double[numberOfVariables_];//(double *)malloc(sizeof(double)*numberOfVariables); + if (upperLimit_ == nullptr) + { + std::cout << "Impossible to reserve memory for storing the variable lower limits" << std::endl; + exit(-1); + } + + for (int i = 0; i < numberOfVariables_; i++) + { + lowerLimit_[i] = 0.0; + upperLimit_[i] = 1.0; + } + + if (solutionType.compare("BinaryReal") == 0) + solutionType_ = snew BinaryRealSolutionType(this) ; + else if (solutionType.compare("Real") == 0) + { + solutionType_ = snew RealSolutionType(this) ; + //std::cout << "Tipo seleccionado Real" << std::endl; + } + else if (solutionType.compare("ArrayReal") == 0) + solutionType_ = snew ArrayRealSolutionType(this) ; + else + { + std::cout << "Error: solution type " << solutionType << " invalid" << std::endl; + exit(-1) ; + } + + fx_ = snew double[numberOfObjectives_] ; + x_ = snew double[numberOfVariables_]; } -DTLZ1::~DTLZ1() { - delete [] lowerLimit_ ; - delete [] upperLimit_ ; - delete solutionType_ ; - delete [] fx_ ; - delete [] x_ ; +DTLZ1::~DTLZ1() +{ + delete [] lowerLimit_ ; + delete [] upperLimit_ ; + delete solutionType_ ; + delete [] fx_ ; + delete [] x_ ; } /** * Evaluates a solution * @param solution The solution to evaluate */ -void DTLZ1::evaluate(Solution *solution) { - XReal * vars = new XReal(solution); +void DTLZ1::evaluate(Solution *solution) +{ + XReal * vars = snew XReal(solution); - int k = numberOfVariables_ - numberOfObjectives_ + 1; + int k = numberOfVariables_ - numberOfObjectives_ + 1; - for (int i = 0; i < numberOfVariables_; i++) - x_[i] = vars->getValue(i); + for (int i = 0; i < numberOfVariables_; i++) + x_[i] = vars->getValue(i); - double g = 0.0 ; + double g = 0.0 ; - for (int i = numberOfVariables_ - k; i < numberOfVariables_; i++) - g += (x_[i] - 0.5)*(x_[i] - 0.5) - cos(20.0 * PI * (x_[i] - 0.5)); + for (int i = numberOfVariables_ - k; i < numberOfVariables_; i++) + g += (x_[i] - 0.5)*(x_[i] - 0.5) - cos(20.0 * PI * (x_[i] - 0.5)); - g = 100 * (k + g); - for (int i = 0; i < numberOfObjectives_; i++) - fx_[i] = (1.0 + g) * 0.5; + g = 100 * (k + g); + for (int i = 0; i < numberOfObjectives_; i++) + fx_[i] = (1.0 + g) * 0.5; - for (int i = 0; i < numberOfObjectives_; i++){ - for (int j = 0; j < numberOfObjectives_ - (i + 1); j++) - fx_[i] *= x_[j]; - if (i != 0){ - int aux = numberOfObjectives_ - (i + 1); - fx_[i] *= 1 - x_[aux]; - } //if - }//for + for (int i = 0; i < numberOfObjectives_; i++) + { + for (int j = 0; j < numberOfObjectives_ - (i + 1); j++) + fx_[i] *= x_[j]; + if (i != 0) + { + int aux = numberOfObjectives_ - (i + 1); + fx_[i] *= 1 - x_[aux]; + } //if + }//for - for (int i = 0; i < numberOfObjectives_; i++) - solution->setObjective(i, fx_[i]); + for (int i = 0; i < numberOfObjectives_; i++) + solution->setObjective(i, fx_[i]); - delete vars ; + delete vars ; } // evaluate diff --git a/src/problems/DTLZ/DTLZ1.h b/src/problems/DTLZ/DTLZ1.h index 8a675b2..478273f 100644 --- a/src/problems/DTLZ/DTLZ1.h +++ b/src/problems/DTLZ/DTLZ1.h @@ -29,16 +29,17 @@ #include #include -class DTLZ1 : public Problem { +class DTLZ1 : public Problem +{ public: - DTLZ1(string solutionType, int numberOfVariables = 7, int numberOfObjectives = 3); - void evaluate(Solution *solution); + DTLZ1(std::string solutionType, int numberOfVariables = 7, int numberOfObjectives = 3); + void evaluate(Solution *solution); - virtual ~DTLZ1(); + virtual ~DTLZ1(); private: - double * fx_ ; - double * x_ ; - static const double PI; + double * fx_ ; + double * x_ ; + static const double PI; }; #endif /* __DTLZ1_H__ */ diff --git a/src/problems/DTLZ/DTLZ1.txt b/src/problems/DTLZ/DTLZ1.txt new file mode 100644 index 0000000..3714e31 --- /dev/null +++ b/src/problems/DTLZ/DTLZ1.txt @@ -0,0 +1,1000 @@ +0.0000000000 0.5000000000 +0.0005005005 0.4994994995 +0.0010010010 0.4989989990 +0.0015015015 0.4984984985 +0.0020020020 0.4979979980 +0.0025025025 0.4974974975 +0.0030030030 0.4969969970 +0.0035035035 0.4964964965 +0.0040040040 0.4959959960 +0.0045045045 0.4954954955 +0.0050050050 0.4949949950 +0.0055055055 0.4944944945 +0.0060060060 0.4939939940 +0.0065065065 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numberOfVariables; - numberOfObjectives_ = numberOfObjectives; - numberOfConstraints_ = 0; - problemName_ = "DTLZ2"; - - lowerLimit_ = new double[numberOfVariables_];//(double *)malloc(sizeof(double)*numberOfVariables); - if (lowerLimit_ == NULL) { - cout << "Impossible to reserve memory for storing the variable lower limits" << endl; - exit(-1); - } - - upperLimit_ = new double[numberOfVariables_];//(double *)malloc(sizeof(double)*numberOfVariables); - if (upperLimit_ == NULL) { - cout << "Impossible to reserve memory for storing the variable lower limits" << endl; - exit(-1); - } - - for (int i = 0; i < numberOfVariables_; i++) { - lowerLimit_[i] = 0.0; - upperLimit_[i] = 1.0; - } - - if (solutionType.compare("BinaryReal") == 0) - solutionType_ = new BinaryRealSolutionType(this) ; - else if (solutionType.compare("Real") == 0) { - solutionType_ = new RealSolutionType(this) ; - //cout << "Tipo seleccionado Real" << endl; - } - else if (solutionType.compare("ArrayReal") == 0) - solutionType_ = new ArrayRealSolutionType(this) ; - else { - cout << "Error: solution type " << solutionType << " invalid" << endl; - exit(-1) ; - } - - fx_ = new double[numberOfObjectives_] ; - x_ = new double[numberOfVariables_]; +DTLZ2::DTLZ2(std::string solutionType, int numberOfVariables, int numberOfObjectives) +{ + numberOfVariables_ = numberOfVariables; + numberOfObjectives_ = numberOfObjectives; + numberOfConstraints_ = 0; + problemName_ = "DTLZ2"; + + lowerLimit_ = snew double[numberOfVariables_];//(double *)malloc(sizeof(double)*numberOfVariables); + if (lowerLimit_ == nullptr) + { + std::cout << "Impossible to reserve memory for storing the variable lower limits" << std::endl; + exit(-1); + } + + upperLimit_ = snew double[numberOfVariables_];//(double *)malloc(sizeof(double)*numberOfVariables); + if (upperLimit_ == nullptr) + { + std::cout << "Impossible to reserve memory for storing the variable lower limits" << std::endl; + exit(-1); + } + + for (int i = 0; i < numberOfVariables_; i++) + { + lowerLimit_[i] = 0.0; + upperLimit_[i] = 1.0; + } + + if (solutionType.compare("BinaryReal") == 0) + solutionType_ = snew BinaryRealSolutionType(this) ; + else if (solutionType.compare("Real") == 0) + { + solutionType_ = snew RealSolutionType(this) ; + //std::cout << "Tipo seleccionado Real" << std::endl; + } + else if (solutionType.compare("ArrayReal") == 0) + solutionType_ = snew ArrayRealSolutionType(this) ; + else + { + std::cout << "Error: solution type " << solutionType << " invalid" << std::endl; + exit(-1) ; + } + + fx_ = snew double[numberOfObjectives_] ; + x_ = snew double[numberOfVariables_]; } -DTLZ2::~DTLZ2() { - delete [] lowerLimit_ ; - delete [] upperLimit_ ; - delete solutionType_ ; - delete [] fx_ ; - delete [] x_ ; +DTLZ2::~DTLZ2() +{ + delete [] lowerLimit_ ; + delete [] upperLimit_ ; + delete solutionType_ ; + delete [] fx_ ; + delete [] x_ ; } /** * Evaluates a solution * @param solution The solution to evaluate */ -void DTLZ2::evaluate(Solution *solution) { - XReal * vars = new XReal(solution); - - int k = numberOfVariables_ - numberOfObjectives_ + 1; - - for (int i = 0; i < numberOfVariables_; i++) - x_[i] = vars->getValue(i); - - double g = 0.0; - for (int i = numberOfVariables_ - k; i < numberOfVariables_; i++) - g += (x_[i] - 0.5)*(x_[i] - 0.5); - - for (int i = 0; i < numberOfObjectives_; i++) - fx_[i] = 1.0 + g; - - for (int i = 0; i < numberOfObjectives_; i++){ - for (int j = 0; j < numberOfObjectives_ - (i + 1); j++) - fx_[i] *= cos(x_[j]*0.5*PI); - if (i != 0){ - int aux = numberOfObjectives_ - (i + 1); - fx_[i] *= sin(x_[aux]*0.5*PI); - } //if - } // for - for (int i = 0; i < numberOfObjectives_; i++) - solution->setObjective(i, fx_[i]); - - delete vars ; +void DTLZ2::evaluate(Solution *solution) +{ + XReal * vars = snew XReal(solution); + + int k = numberOfVariables_ - numberOfObjectives_ + 1; + + for (int i = 0; i < numberOfVariables_; i++) + x_[i] = vars->getValue(i); + + double g = 0.0; + for (int i = numberOfVariables_ - k; i < numberOfVariables_; i++) + g += (x_[i] - 0.5)*(x_[i] - 0.5); + + for (int i = 0; i < numberOfObjectives_; i++) + fx_[i] = 1.0 + g; + + for (int i = 0; i < numberOfObjectives_; i++) + { + for (int j = 0; j < numberOfObjectives_ - (i + 1); j++) + fx_[i] *= cos(x_[j]*0.5*PI); + if (i != 0) + { + int aux = numberOfObjectives_ - (i + 1); + fx_[i] *= sin(x_[aux]*0.5*PI); + } //if + } // for + for (int i = 0; i < numberOfObjectives_; i++) + solution->setObjective(i, fx_[i]); + + delete vars ; } // evaluate diff --git a/src/problems/DTLZ/DTLZ2.h b/src/problems/DTLZ/DTLZ2.h index 959af8c..69609fa 100644 --- a/src/problems/DTLZ/DTLZ2.h +++ b/src/problems/DTLZ/DTLZ2.h @@ -29,16 +29,17 @@ #include #include -class DTLZ2 : public Problem { +class DTLZ2 : public Problem +{ public: - DTLZ2(string solutionType, int numberOfVariables = 12, int numberOfObjectives = 3); - void evaluate(Solution *solution); + DTLZ2(std::string solutionType, int numberOfVariables = 12, int numberOfObjectives = 3); + void evaluate(Solution *solution); - virtual ~DTLZ2(); + virtual ~DTLZ2(); private: - double * fx_ ; - double * x_ ; - static const double PI; + double * fx_ ; + double * x_ ; + static const double PI; }; #endif /* __DTLZ2_H__ */ diff --git a/src/problems/DTLZ/DTLZ2.txt b/src/problems/DTLZ/DTLZ2.txt new file mode 100644 index 0000000..8e7a98f --- /dev/null +++ b/src/problems/DTLZ/DTLZ2.txt @@ -0,0 +1,1000 @@ +0.0000000000 1.0000000000 +0.0369034559 0.9993188355 +0.0554689064 0.9984604150 +0.0701154707 0.9975388818 +0.0825460836 0.9965872486 +0.0944933533 0.9955254925 +0.1052322500 0.9944476726 +0.1149755587 0.9933683209 +0.1240790518 0.9922723361 +0.1323880288 0.9911979670 +0.1401883532 0.9901248536 +0.1470407828 0.9891304303 +0.1540288320 0.9880663535 +0.1602847298 0.9870708209 +0.1664128767 0.9860561619 +0.1723284939 0.9850395374 +0.1779913023 0.9840320606 +0.1834929251 0.9830210305 +0.1888536496 0.9820052439 +0.1940749455 0.9809867051 +0.1990808625 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numberOfObjectives) +{ + numberOfVariables_ = numberOfVariables; + numberOfObjectives_ = numberOfObjectives; + numberOfConstraints_ = 0; + problemName_ = "DTLZ3"; - lowerLimit_ = new double[numberOfVariables_];//(double *)malloc(sizeof(double)*numberOfVariables); - if (lowerLimit_ == NULL) { - cout << "Impossible to reserve memory for storing the variable lower limits" << endl; - exit(-1); - } + lowerLimit_ = snew double[numberOfVariables_];//(double *)malloc(sizeof(double)*numberOfVariables); + if (lowerLimit_ == nullptr) + { + std::cout << "Impossible to reserve memory for storing the variable lower limits" << std::endl; + exit(-1); + } - upperLimit_ = new double[numberOfVariables_];//(double *)malloc(sizeof(double)*numberOfVariables); - if (upperLimit_ == NULL) { - cout << "Impossible to reserve memory for storing the variable lower limits" << endl; - exit(-1); - } + upperLimit_ = snew double[numberOfVariables_];//(double *)malloc(sizeof(double)*numberOfVariables); + if (upperLimit_ == nullptr) + { + std::cout << "Impossible to reserve memory for storing the variable lower limits" << std::endl; + exit(-1); + } - for (int i = 0; i < numberOfVariables_; i++) { - lowerLimit_[i] = 0.0; - upperLimit_[i] = 1.0; - } + for (int i = 0; i < numberOfVariables_; i++) + { + lowerLimit_[i] = 0.0; + upperLimit_[i] = 1.0; + } - if (solutionType.compare("BinaryReal") == 0) - solutionType_ = new BinaryRealSolutionType(this) ; - else if (solutionType.compare("Real") == 0) { - solutionType_ = new RealSolutionType(this) ; - // cout << "Tipo seleccionado Real" << endl; - } - else if (solutionType.compare("ArrayReal") == 0) - solutionType_ = new ArrayRealSolutionType(this) ; - else { - cout << "Error: solution type " << solutionType << " invalid" << endl; - exit(-1) ; - } - fx_ = new double[numberOfObjectives_] ; - x_ = new double[numberOfVariables_]; + if (solutionType.compare("BinaryReal") == 0) + solutionType_ = snew BinaryRealSolutionType(this) ; + else if (solutionType.compare("Real") == 0) + { + solutionType_ = snew RealSolutionType(this) ; + // std::cout << "Tipo seleccionado Real" << std::endl; + } + else if (solutionType.compare("ArrayReal") == 0) + solutionType_ = snew ArrayRealSolutionType(this) ; + else + { + std::cout << "Error: solution type " << solutionType << " invalid" << std::endl; + exit(-1) ; + } + fx_ = snew double[numberOfObjectives_] ; + x_ = snew double[numberOfVariables_]; } -DTLZ3::~DTLZ3() { - delete [] lowerLimit_ ; - delete [] upperLimit_ ; - delete solutionType_ ; +DTLZ3::~DTLZ3() +{ + delete [] lowerLimit_ ; + delete [] upperLimit_ ; + delete solutionType_ ; } /** * Evaluates a solution * @param solution The solution to evaluate */ -void DTLZ3::evaluate(Solution *solution) { - XReal * vars = new XReal(solution); +void DTLZ3::evaluate(Solution *solution) +{ + XReal * vars = snew XReal(solution); - int k = numberOfVariables_ - numberOfObjectives_ + 1; + int k = numberOfVariables_ - numberOfObjectives_ + 1; - for (int i = 0; i < numberOfVariables_; i++) - x_[i] = vars->getValue(i); + for (int i = 0; i < numberOfVariables_; i++) + x_[i] = vars->getValue(i); - double g = 0.0; - for (int i = numberOfVariables_ - k; i < numberOfVariables_; i++) - g += (x_[i] - 0.5)*(x_[i] - 0.5) - cos(20.0 * PI * (x_[i] - 0.5)); + double g = 0.0; + for (int i = numberOfVariables_ - k; i < numberOfVariables_; i++) + g += (x_[i] - 0.5)*(x_[i] - 0.5) - cos(20.0 * PI * (x_[i] - 0.5)); - g = 100.0 * (k + g); - for (int i = 0; i < numberOfObjectives_; i++) - fx_[i] = 1.0 + g; + g = 100.0 * (k + g); + for (int i = 0; i < numberOfObjectives_; i++) + fx_[i] = 1.0 + g; - for (int i = 0; i < numberOfObjectives_; i++){ - for (int j = 0; j < numberOfObjectives_ - (i + 1); j++) - fx_[i] *= cos(x_[j]*0.5*PI); - if (i != 0){ - int aux = numberOfObjectives_ - (i + 1); - fx_[i] *= sin(x_[aux]*0.5*PI); - } // if - } //for + for (int i = 0; i < numberOfObjectives_; i++) + { + for (int j = 0; j < numberOfObjectives_ - (i + 1); j++) + fx_[i] *= cos(x_[j]*0.5*PI); + if (i != 0) + { + int aux = numberOfObjectives_ - (i + 1); + fx_[i] *= sin(x_[aux]*0.5*PI); + } // if + } //for - delete vars ; + delete vars ; } // evaluate diff --git a/src/problems/DTLZ/DTLZ3.h b/src/problems/DTLZ/DTLZ3.h index dbfec09..657bdf1 100644 --- a/src/problems/DTLZ/DTLZ3.h +++ b/src/problems/DTLZ/DTLZ3.h @@ -29,16 +29,17 @@ #include #include -class DTLZ3 : public Problem { +class DTLZ3 : public Problem +{ public: - DTLZ3(string solutionType, int numberOfVariables = 12, int numberOfObjectives = 3); - void evaluate(Solution *solution); + DTLZ3(std::string solutionType, int numberOfVariables = 12, int numberOfObjectives = 3); + void evaluate(Solution *solution); - virtual ~DTLZ3(); + virtual ~DTLZ3(); private: - double * fx_ ; - double * x_ ; - static const double PI ; + double * fx_ ; + double * x_ ; + static const double PI ; }; #endif /* __DTLZ3_H__ */ diff --git a/src/problems/DTLZ/DTLZ3.txt b/src/problems/DTLZ/DTLZ3.txt new file mode 100644 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0.0819399766 +0.9976101518 0.0690940309 +0.9985118883 0.0545344751 +0.9993366830 0.0364169478 +1.0000000000 0.0000000000 diff --git a/src/problems/DTLZ/DTLZ4.cpp b/src/problems/DTLZ/DTLZ4.cpp index 673a34c..2edea2c 100644 --- a/src/problems/DTLZ/DTLZ4.cpp +++ b/src/problems/DTLZ/DTLZ4.cpp @@ -22,83 +22,93 @@ const double DTLZ4::PI = 3.141592653589793; -DTLZ4::DTLZ4(string solutionType, int numberOfVariables, int numberOfObjectives) { - numberOfVariables_ = numberOfVariables; - numberOfObjectives_ = numberOfObjectives; - numberOfConstraints_ = 0; - problemName_ = "DTLZ4"; - - lowerLimit_ = new double[numberOfVariables_];//(double *)malloc(sizeof(double)*numberOfVariables); - if (lowerLimit_ == NULL) { - cout << "Impossible to reserve memory for storing the variable lower limits" << endl; - exit(-1); - } - - upperLimit_ = new double[numberOfVariables_];//(double *)malloc(sizeof(double)*numberOfVariables); - if (upperLimit_ == NULL) { - cout << "Impossible to reserve memory for storing the variable lower limits" << endl; - exit(-1); - } - - for (int i = 0; i < numberOfVariables_; i++) { - lowerLimit_[i] = 0.0; - upperLimit_[i] = 1.0; - } - - if (solutionType.compare("BinaryReal") == 0) - solutionType_ = new BinaryRealSolutionType(this) ; - else if (solutionType.compare("Real") == 0) { - solutionType_ = new RealSolutionType(this) ; - // cout << "Tipo seleccionado Real" << endl; - } - else if (solutionType.compare("ArrayReal") == 0) - solutionType_ = new ArrayRealSolutionType(this) ; - else { - cout << "Error: solution type " << solutionType << " invalid" << endl; - exit(-1) ; - } - - fx_ = new double[numberOfObjectives_] ; - x_ = new double[numberOfVariables_]; +DTLZ4::DTLZ4(std::string solutionType, int numberOfVariables, int numberOfObjectives) +{ + numberOfVariables_ = numberOfVariables; + numberOfObjectives_ = numberOfObjectives; + numberOfConstraints_ = 0; + problemName_ = "DTLZ4"; + + lowerLimit_ = snew double[numberOfVariables_];//(double *)malloc(sizeof(double)*numberOfVariables); + if (lowerLimit_ == nullptr) + { + std::cout << "Impossible to reserve memory for storing the variable lower limits" << std::endl; + exit(-1); + } + + upperLimit_ = snew double[numberOfVariables_];//(double *)malloc(sizeof(double)*numberOfVariables); + if (upperLimit_ == nullptr) + { + std::cout << "Impossible to reserve memory for storing the variable lower limits" << std::endl; + exit(-1); + } + + for (int i = 0; i < numberOfVariables_; i++) + { + lowerLimit_[i] = 0.0; + upperLimit_[i] = 1.0; + } + + if (solutionType.compare("BinaryReal") == 0) + solutionType_ = snew BinaryRealSolutionType(this) ; + else if (solutionType.compare("Real") == 0) + { + solutionType_ = snew RealSolutionType(this) ; + // std::cout << "Tipo seleccionado Real" << std::endl; + } + else if (solutionType.compare("ArrayReal") == 0) + solutionType_ = snew ArrayRealSolutionType(this) ; + else + { + std::cout << "Error: solution type " << solutionType << " invalid" << std::endl; + exit(-1) ; + } + + fx_ = snew double[numberOfObjectives_] ; + x_ = snew double[numberOfVariables_]; } -DTLZ4::~DTLZ4() { - delete [] lowerLimit_ ; - delete [] upperLimit_ ; - delete solutionType_ ; +DTLZ4::~DTLZ4() +{ + delete [] lowerLimit_ ; + delete [] upperLimit_ ; + delete solutionType_ ; } /** * Evaluates a solution * @param solution The solution to evaluate */ -void DTLZ4::evaluate(Solution *solution) { - XReal * vars = new XReal(solution); - - int k = numberOfVariables_ - numberOfObjectives_ + 1; - double alpha = 100.0; - - for (int i = 0; i < numberOfVariables_; i++) - x_[i] = vars->getValue(i); - - double g = 0.0; - for (int i = numberOfVariables_ - k; i < numberOfVariables_; i++) - g += (x_[i] - 0.5)*(x_[i] - 0.5); - - for (int i = 0; i < numberOfObjectives_; i++) - fx_[i] = 1.0 + g; - - for (int i = 0; i < numberOfObjectives_; i++) { - for (int j = 0; j < numberOfObjectives_ - (i + 1); j++) - fx_[i] *= cos(pow(x_[j],alpha)*(PI/2.0)); - if (i != 0){ - int aux = numberOfObjectives_ - (i + 1); - fx_[i] *= sin(pow(x_[aux],alpha)*(PI/2.0)); - } //if - } // for - - for (int i = 0; i < numberOfObjectives_; i++) - solution->setObjective(i, fx_[i]); - - delete vars ; +void DTLZ4::evaluate(Solution *solution) +{ + XReal * vars = snew XReal(solution); + + int k = numberOfVariables_ - numberOfObjectives_ + 1; + double alpha = 100.0; + + for (int i = 0; i < numberOfVariables_; i++) + x_[i] = vars->getValue(i); + + double g = 0.0; + for (int i = numberOfVariables_ - k; i < numberOfVariables_; i++) + g += (x_[i] - 0.5)*(x_[i] - 0.5); + + for (int i = 0; i < numberOfObjectives_; i++) + fx_[i] = 1.0 + g; + + for (int i = 0; i < numberOfObjectives_; i++) + { + for (int j = 0; j < numberOfObjectives_ - (i + 1); j++) + fx_[i] *= cos(pow(x_[j],alpha)*(PI/2.0)); + if (i != 0) + { + int aux = numberOfObjectives_ - (i + 1); + fx_[i] *= sin(pow(x_[aux],alpha)*(PI/2.0)); + } //if + } // for + + for (int i = 0; i < numberOfObjectives_; i++) + solution->setObjective(i, fx_[i]); + + delete vars ; } // evaluate diff --git a/src/problems/DTLZ/DTLZ4.h b/src/problems/DTLZ/DTLZ4.h index 0b90fe2..8bb54c4 100644 --- a/src/problems/DTLZ/DTLZ4.h +++ b/src/problems/DTLZ/DTLZ4.h @@ -29,16 +29,17 @@ #include #include -class DTLZ4 : public Problem { +class DTLZ4 : public Problem +{ public: - DTLZ4(string solutionType, int numberOfVariables = 12, int numberOfObjectives = 3); - void evaluate(Solution *solution); + DTLZ4(std::string solutionType, int numberOfVariables = 12, int numberOfObjectives = 3); + void evaluate(Solution *solution); - virtual ~DTLZ4(); + virtual ~DTLZ4(); private: - double * fx_ ; - double * x_ ; - static const double PI ; + double * fx_ ; + double * x_ ; + static const double PI ; }; #endif /* __DTLZ4_H__ */ diff --git a/src/problems/DTLZ/DTLZ4.txt b/src/problems/DTLZ/DTLZ4.txt new file mode 100644 index 0000000..c599a8b --- /dev/null +++ b/src/problems/DTLZ/DTLZ4.txt @@ -0,0 +1,1000 @@ +0.0000000000 1.0000000000 +0.0024376240 0.9999970290 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a/src/problems/DTLZ/DTLZ5.cpp b/src/problems/DTLZ/DTLZ5.cpp index 2acf331..0e4766d 100644 --- a/src/problems/DTLZ/DTLZ5.cpp +++ b/src/problems/DTLZ/DTLZ5.cpp @@ -22,91 +22,101 @@ const double DTLZ5::PI = 3.141592653589793; -DTLZ5::DTLZ5(string solutionType, int numberOfVariables, int numberOfObjectives) { - numberOfVariables_ = numberOfVariables; - numberOfObjectives_ = numberOfObjectives; - numberOfConstraints_ = 0; - problemName_ = "DTLZ5"; - - lowerLimit_ = new double[numberOfVariables_];//(double *)malloc(sizeof(double)*numberOfVariables); - if (lowerLimit_ == NULL) { - cout << "Impossible to reserve memory for storing the variable lower limits" << endl; - exit(-1); - } - - upperLimit_ = new double[numberOfVariables_];//(double *)malloc(sizeof(double)*numberOfVariables); - if (upperLimit_ == NULL) { - cout << "Impossible to reserve memory for storing the variable lower limits" << endl; - exit(-1); - } - - for (int i = 0; i < numberOfVariables_; i++) { - lowerLimit_[i] = 0.0; - upperLimit_[i] = 1.0; - } - - if (solutionType.compare("BinaryReal") == 0) - solutionType_ = new BinaryRealSolutionType(this) ; - else if (solutionType.compare("Real") == 0) { - solutionType_ = new RealSolutionType(this) ; - //cout << "Tipo seleccionado Real" << endl; - } - else if (solutionType.compare("ArrayReal") == 0) - solutionType_ = new ArrayRealSolutionType(this) ; - else { - cout << "Error: solution type " << solutionType << " invalid" << endl; - exit(-1) ; - } - - fx_ = new double[numberOfObjectives_] ; - x_ = new double[numberOfVariables_]; - theta_ = new double[numberOfObjectives_-1]; +DTLZ5::DTLZ5(std::string solutionType, int numberOfVariables, int numberOfObjectives) +{ + numberOfVariables_ = numberOfVariables; + numberOfObjectives_ = numberOfObjectives; + numberOfConstraints_ = 0; + problemName_ = "DTLZ5"; + + lowerLimit_ = snew double[numberOfVariables_];//(double *)malloc(sizeof(double)*numberOfVariables); + if (lowerLimit_ == nullptr) + { + std::cout << "Impossible to reserve memory for storing the variable lower limits" << std::endl; + exit(-1); + } + + upperLimit_ = snew double[numberOfVariables_];//(double *)malloc(sizeof(double)*numberOfVariables); + if (upperLimit_ == nullptr) + { + std::cout << "Impossible to reserve memory for storing the variable lower limits" << std::endl; + exit(-1); + } + + for (int i = 0; i < numberOfVariables_; i++) + { + lowerLimit_[i] = 0.0; + upperLimit_[i] = 1.0; + } + + if (solutionType.compare("BinaryReal") == 0) + solutionType_ = snew BinaryRealSolutionType(this) ; + else if (solutionType.compare("Real") == 0) + { + solutionType_ = snew RealSolutionType(this) ; + //std::cout << "Tipo seleccionado Real" << std::endl; + } + else if (solutionType.compare("ArrayReal") == 0) + solutionType_ = snew ArrayRealSolutionType(this) ; + else + { + std::cout << "Error: solution type " << solutionType << " invalid" << std::endl; + exit(-1) ; + } + + fx_ = snew double[numberOfObjectives_] ; + x_ = snew double[numberOfVariables_]; + theta_ = snew double[numberOfObjectives_-1]; } -DTLZ5::~DTLZ5() { - delete [] lowerLimit_ ; - delete [] upperLimit_ ; - delete solutionType_ ; - delete [] theta_ ; +DTLZ5::~DTLZ5() +{ + delete [] lowerLimit_ ; + delete [] upperLimit_ ; + delete solutionType_ ; + delete [] theta_ ; } /** * Evaluates a solution * @param solution The solution to evaluate */ -void DTLZ5::evaluate(Solution *solution) { - XReal * vars = new XReal(solution); - double g = 0.0; +void DTLZ5::evaluate(Solution *solution) +{ + XReal * vars = snew XReal(solution); + double g = 0.0; - int k = numberOfVariables_ - numberOfObjectives_ + 1; - double alpha = 100.0; + int k = numberOfVariables_ - numberOfObjectives_ + 1; + double alpha = 100.0; - for (int i = 0; i < numberOfVariables_; i++) - x_[i] = vars->getValue(i); + for (int i = 0; i < numberOfVariables_; i++) + x_[i] = vars->getValue(i); - for (int i = numberOfVariables_ - k; i < numberOfVariables_; i++) - g += (x_[i] - 0.5)*(x_[i] - 0.5); + for (int i = numberOfVariables_ - k; i < numberOfVariables_; i++) + g += (x_[i] - 0.5)*(x_[i] - 0.5); - double t = PI / (4.0 * (1.0 + g)); + double t = PI / (4.0 * (1.0 + g)); - theta_[0] = x_[0] * PI / 2.0; - for (int i = 1; i < (numberOfObjectives_-1); i++) - theta_[i] = t * (1.0 + 2.0 * g * x_[i]); + theta_[0] = x_[0] * PI / 2.0; + for (int i = 1; i < (numberOfObjectives_-1); i++) + theta_[i] = t * (1.0 + 2.0 * g * x_[i]); - for (int i = 0; i < numberOfObjectives_; i++) - fx_[i] = 1.0 + g; + for (int i = 0; i < numberOfObjectives_; i++) + fx_[i] = 1.0 + g; - for (int i = 0; i < numberOfObjectives_; i++){ - for (int j = 0; j < numberOfObjectives_ - (i + 1); j++) - fx_[i] *= cos(theta_[j]); - if (i != 0){ - int aux = numberOfObjectives_ - (i + 1); - fx_[i] *= sin(theta_[aux]); - } // if - } //for + for (int i = 0; i < numberOfObjectives_; i++) + { + for (int j = 0; j < numberOfObjectives_ - (i + 1); j++) + fx_[i] *= cos(theta_[j]); + if (i != 0) + { + int aux = numberOfObjectives_ - (i + 1); + fx_[i] *= sin(theta_[aux]); + } // if + } //for - for (int i = 0; i < numberOfObjectives_; i++) - solution->setObjective(i, fx_[i]); + for (int i = 0; i < numberOfObjectives_; i++) + solution->setObjective(i, fx_[i]); - delete vars ; + delete vars ; } // evaluate diff --git a/src/problems/DTLZ/DTLZ5.h b/src/problems/DTLZ/DTLZ5.h index 3ecfad3..7dac71c 100644 --- a/src/problems/DTLZ/DTLZ5.h +++ b/src/problems/DTLZ/DTLZ5.h @@ -29,18 +29,19 @@ #include #include -class DTLZ5 : public Problem { +class DTLZ5 : public Problem +{ public: - DTLZ5(string solutionType, int numberOfVariables = 12, int numberOfObjectives = 3); - void evaluate(Solution *solution); + DTLZ5(std::string solutionType, int numberOfVariables = 12, int numberOfObjectives = 3); + void evaluate(Solution *solution); - virtual ~DTLZ5(); + virtual ~DTLZ5(); private: - double * fx_ ; - double * x_ ; - double * theta_ ; - private: - static const double PI ; + double * fx_ ; + double * x_ ; + double * theta_ ; +private: + static const double PI ; }; #endif /* __DTLZ5_H__ */ diff --git a/src/problems/DTLZ/DTLZ6.cpp b/src/problems/DTLZ/DTLZ6.cpp index 760cbe0..56c3bb7 100644 --- a/src/problems/DTLZ/DTLZ6.cpp +++ b/src/problems/DTLZ/DTLZ6.cpp @@ -22,91 +22,101 @@ const double DTLZ6::PI = 3.141592653589793; -DTLZ6::DTLZ6(string solutionType, int numberOfVariables, int numberOfObjectives) { - numberOfVariables_ = numberOfVariables; - numberOfObjectives_ = numberOfObjectives; - numberOfConstraints_ = 0; - problemName_ = "DTLZ6"; - - lowerLimit_ = new double[numberOfVariables_];//(double *)malloc(sizeof(double)*numberOfVariables); - if (lowerLimit_ == NULL) { - cout << "Impossible to reserve memory for storing the variable lower limits" << endl; - exit(-1); - } - - upperLimit_ = new double[numberOfVariables_];//(double *)malloc(sizeof(double)*numberOfVariables); - if (upperLimit_ == NULL) { - cout << "Impossible to reserve memory for storing the variable lower limits" << endl; - exit(-1); - } - - for (int i = 0; i < numberOfVariables_; i++) { - lowerLimit_[i] = 0.0; - upperLimit_[i] = 1.0; - } - - if (solutionType.compare("BinaryReal") == 0) - solutionType_ = new BinaryRealSolutionType(this) ; - else if (solutionType.compare("Real") == 0) { - solutionType_ = new RealSolutionType(this) ; - //cout << "Tipo seleccionado Real" << endl; - } - else if (solutionType.compare("ArrayReal") == 0) - solutionType_ = new ArrayRealSolutionType(this) ; - else { - cout << "Error: solution type " << solutionType << " invalid" << endl; - exit(-1) ; - } - - fx_ = new double[numberOfObjectives_] ; - x_ = new double[numberOfVariables_]; - theta_ = new double[numberOfObjectives_-1]; +DTLZ6::DTLZ6(std::string solutionType, int numberOfVariables, int numberOfObjectives) +{ + numberOfVariables_ = numberOfVariables; + numberOfObjectives_ = numberOfObjectives; + numberOfConstraints_ = 0; + problemName_ = "DTLZ6"; + + lowerLimit_ = snew double[numberOfVariables_];//(double *)malloc(sizeof(double)*numberOfVariables); + if (lowerLimit_ == nullptr) + { + std::cout << "Impossible to reserve memory for storing the variable lower limits" << std::endl; + exit(-1); + } + + upperLimit_ = snew double[numberOfVariables_];//(double *)malloc(sizeof(double)*numberOfVariables); + if (upperLimit_ == nullptr) + { + std::cout << "Impossible to reserve memory for storing the variable lower limits" << std::endl; + exit(-1); + } + + for (int i = 0; i < numberOfVariables_; i++) + { + lowerLimit_[i] = 0.0; + upperLimit_[i] = 1.0; + } + + if (solutionType.compare("BinaryReal") == 0) + solutionType_ = snew BinaryRealSolutionType(this) ; + else if (solutionType.compare("Real") == 0) + { + solutionType_ = snew RealSolutionType(this) ; + //std::cout << "Tipo seleccionado Real" << std::endl; + } + else if (solutionType.compare("ArrayReal") == 0) + solutionType_ = snew ArrayRealSolutionType(this) ; + else + { + std::cout << "Error: solution type " << solutionType << " invalid" << std::endl; + exit(-1) ; + } + + fx_ = snew double[numberOfObjectives_] ; + x_ = snew double[numberOfVariables_]; + theta_ = snew double[numberOfObjectives_-1]; } -DTLZ6::~DTLZ6() { - delete [] lowerLimit_ ; - delete [] upperLimit_ ; - delete solutionType_ ; - delete [] theta_ ; +DTLZ6::~DTLZ6() +{ + delete [] lowerLimit_ ; + delete [] upperLimit_ ; + delete solutionType_ ; + delete [] theta_ ; } /** * Evaluates a solution * @param solution The solution to evaluate */ -void DTLZ6::evaluate(Solution *solution) { - XReal * vars = new XReal(solution); - double g = 0.0; +void DTLZ6::evaluate(Solution *solution) +{ + XReal * vars = snew XReal(solution); + double g = 0.0; - int k = numberOfVariables_ - numberOfObjectives_ + 1; - double alpha = 100.0; + int k = numberOfVariables_ - numberOfObjectives_ + 1; + double alpha = 100.0; - for (int i = 0; i < numberOfVariables_; i++) - x_[i] = vars->getValue(i); + for (int i = 0; i < numberOfVariables_; i++) + x_[i] = vars->getValue(i); - for (int i = numberOfVariables_ - k; i < numberOfVariables_; i++) - g += pow(x_[i],0.1); + for (int i = numberOfVariables_ - k; i < numberOfVariables_; i++) + g += pow(x_[i],0.1); - double t = PI / (4.0 * (1.0 + g)); + double t = PI / (4.0 * (1.0 + g)); - theta_[0] = x_[0] * PI / 2.0; - for (int i = 1; i < (numberOfObjectives_-1); i++) - theta_[i] = t * (1.0 + 2.0 * g * x_[i]); + theta_[0] = x_[0] * PI / 2.0; + for (int i = 1; i < (numberOfObjectives_-1); i++) + theta_[i] = t * (1.0 + 2.0 * g * x_[i]); - for (int i = 0; i < numberOfObjectives_; i++) - fx_[i] = 1.0 + g; + for (int i = 0; i < numberOfObjectives_; i++) + fx_[i] = 1.0 + g; - for (int i = 0; i < numberOfObjectives_; i++){ - for (int j = 0; j < numberOfObjectives_ - (i + 1); j++) - fx_[i] *= cos(theta_[j]); - if (i != 0){ - int aux = numberOfObjectives_ - (i + 1); - fx_[i] *= sin(theta_[aux]); - } // if - } //for + for (int i = 0; i < numberOfObjectives_; i++) + { + for (int j = 0; j < numberOfObjectives_ - (i + 1); j++) + fx_[i] *= cos(theta_[j]); + if (i != 0) + { + int aux = numberOfObjectives_ - (i + 1); + fx_[i] *= sin(theta_[aux]); + } // if + } //for - for (int i = 0; i < numberOfObjectives_; i++) - solution->setObjective(i, fx_[i]); + for (int i = 0; i < numberOfObjectives_; i++) + solution->setObjective(i, fx_[i]); - delete vars ; + delete vars ; } // evaluate diff --git a/src/problems/DTLZ/DTLZ6.h b/src/problems/DTLZ/DTLZ6.h index 49153c3..8b72a7e 100644 --- a/src/problems/DTLZ/DTLZ6.h +++ b/src/problems/DTLZ/DTLZ6.h @@ -29,17 +29,18 @@ #include #include -class DTLZ6 : public Problem { +class DTLZ6 : public Problem +{ public: - DTLZ6(string solutionType, int numberOfVariables = 12, int numberOfObjectives = 2); - void evaluate(Solution *solution); + DTLZ6(std::string solutionType, int numberOfVariables = 12, int numberOfObjectives = 2); + void evaluate(Solution *solution); - virtual ~DTLZ6(); + virtual ~DTLZ6(); private: - double * fx_ ; - double * x_ ; - double * theta_ ; - static const double PI ; + double * fx_ ; + double * x_ ; + double * theta_ ; + static const double PI ; }; #endif /* __DTLZ6_H__ */ diff --git a/src/problems/DTLZ/DTLZ7.cpp b/src/problems/DTLZ/DTLZ7.cpp index 8fd4ed9..071308d 100644 --- a/src/problems/DTLZ/DTLZ7.cpp +++ b/src/problems/DTLZ/DTLZ7.cpp @@ -22,86 +22,95 @@ const double DTLZ7::PI = 3.141592653589793; -DTLZ7::DTLZ7(string solutionType, int numberOfVariables, int numberOfObjectives) { - numberOfVariables_ = numberOfVariables; - numberOfObjectives_ = numberOfObjectives; - numberOfConstraints_ = 0; - problemName_ = "DTLZ7"; - - lowerLimit_ = new double[numberOfVariables_];//(double *)malloc(sizeof(double)*numberOfVariables); - if (lowerLimit_ == NULL) { - cout << "Impossible to reserve memory for storing the variable lower limits" << endl; - exit(-1); - } - - upperLimit_ = new double[numberOfVariables_];//(double *)malloc(sizeof(double)*numberOfVariables); - if (upperLimit_ == NULL) { - cout << "Impossible to reserve memory for storing the variable lower limits" << endl; - exit(-1); - } - - for (int i = 0; i < numberOfVariables_; i++) { - lowerLimit_[i] = 0.0; - upperLimit_[i] = 1.0; - } - - if (solutionType.compare("BinaryReal") == 0) - solutionType_ = new BinaryRealSolutionType(this) ; - else if (solutionType.compare("Real") == 0) { - solutionType_ = new RealSolutionType(this) ; - //cout << "Tipo seleccionado Real" << endl; - } - else if (solutionType.compare("ArrayReal") == 0) - solutionType_ = new ArrayRealSolutionType(this) ; - else { - cout << "Error: solution type " << solutionType << " invalid" << endl; - exit(-1) ; - } - - fx_ = new double[numberOfObjectives_] ; - x_ = new double[numberOfVariables_]; +DTLZ7::DTLZ7(std::string solutionType, int numberOfVariables, int numberOfObjectives) +{ + numberOfVariables_ = numberOfVariables; + numberOfObjectives_ = numberOfObjectives; + numberOfConstraints_ = 0; + problemName_ = "DTLZ7"; + + lowerLimit_ = snew double[numberOfVariables_];//(double *)malloc(sizeof(double)*numberOfVariables); + if (lowerLimit_ == nullptr) + { + std::cout << "Impossible to reserve memory for storing the variable lower limits" << std::endl; + exit(-1); + } + + upperLimit_ = snew double[numberOfVariables_];//(double *)malloc(sizeof(double)*numberOfVariables); + if (upperLimit_ == nullptr) + { + std::cout << "Impossible to reserve memory for storing the variable lower limits" << std::endl; + exit(-1); + } + + for (int i = 0; i < numberOfVariables_; i++) + { + lowerLimit_[i] = 0.0; + upperLimit_[i] = 1.0; + } + + if (solutionType.compare("BinaryReal") == 0) + solutionType_ = snew BinaryRealSolutionType(this) ; + else if (solutionType.compare("Real") == 0) + { + solutionType_ = snew RealSolutionType(this) ; + //std::cout << "Tipo seleccionado Real" << std::endl; + } + else if (solutionType.compare("ArrayReal") == 0) + solutionType_ = snew ArrayRealSolutionType(this) ; + else + { + std::cout << "Error: solution type " << solutionType << " invalid" << std::endl; + exit(-1) ; + } + + fx_ = snew double[numberOfObjectives_] ; + x_ = snew double[numberOfVariables_]; } -DTLZ7::~DTLZ7() { - delete [] lowerLimit_ ; - delete [] upperLimit_ ; - delete solutionType_ ; +DTLZ7::~DTLZ7() +{ + delete [] lowerLimit_ ; + delete [] upperLimit_ ; + delete solutionType_ ; } /** * Evaluates a solution * @param solution The solution to evaluate */ -void DTLZ7::evaluate(Solution *solution) { - XReal * vars = new XReal(solution); - double g = 0.0; +void DTLZ7::evaluate(Solution *solution) +{ + XReal * vars = snew XReal(solution); + double g = 0.0; - int k = numberOfVariables_ - numberOfObjectives_ + 1; - double alpha = 100.0; + int k = numberOfVariables_ - numberOfObjectives_ + 1; + double alpha = 100.0; - for (int i = 0; i < numberOfVariables_; i++) - x_[i] = vars->getValue(i); + for (int i = 0; i < numberOfVariables_; i++) + x_[i] = vars->getValue(i); - for (int i = numberOfVariables_ - k; i < numberOfVariables_; i++) - g += x_[i] ; + for (int i = numberOfVariables_ - k; i < numberOfVariables_; i++) + g += x_[i] ; - g = 1 + (9.0 * g)/k ; + g = 1 + (9.0 * g)/k ; - for (int i = 0; i < numberOfObjectives_ - 1; i++) - fx_[i] = x_[i] ; + for (int i = 0; i < numberOfObjectives_ - 1; i++) + fx_[i] = x_[i] ; - double h = 0.0 ; - for (int i = 0; i < numberOfObjectives_ - 1; i++){ - h+=(fx_[i]/(1.0+g))*(1 + sin(3.0*PI*fx_[i])) ; - } //for + double h = 0.0 ; + for (int i = 0; i < numberOfObjectives_ - 1; i++) + { + h+=(fx_[i]/(1.0+g))*(1 + sin(3.0*PI*fx_[i])) ; + } //for - h = numberOfObjectives_ - h ; + h = numberOfObjectives_ - h ; - fx_[numberOfObjectives_ - 1] = (1+g)*h ; + fx_[numberOfObjectives_ - 1] = (1+g)*h ; - for (int i = 0; i < numberOfObjectives_; i++) - solution->setObjective(i, fx_[i]); + for (int i = 0; i < numberOfObjectives_; i++) + solution->setObjective(i, fx_[i]); - delete vars ; + delete vars ; } // evaluate diff --git a/src/problems/DTLZ/DTLZ7.h b/src/problems/DTLZ/DTLZ7.h index 01bd0d5..9d2ce0e 100644 --- a/src/problems/DTLZ/DTLZ7.h +++ b/src/problems/DTLZ/DTLZ7.h @@ -29,16 +29,17 @@ #include #include -class DTLZ7 : public Problem { +class DTLZ7 : public Problem +{ public: - DTLZ7(string solutionType, int numberOfVariables = 12, int numberOfObjectives = 3); - void evaluate(Solution *solution); + DTLZ7(string solutionType, int numberOfVariables = 12, int numberOfObjectives = 3); + void evaluate(Solution *solution); - virtual ~DTLZ7(); + virtual ~DTLZ7(); private: - double * fx_ ; - double * x_ ; - static const double PI ; + double * fx_ ; + double * x_ ; + static const double PI ; }; #endif /* __DTLZ7_H__ */ diff --git a/src/problems/DTLZ/DTLZ7.txt b/src/problems/DTLZ/DTLZ7.txt new file mode 100644 index 0000000..6bc2040 --- /dev/null +++ b/src/problems/DTLZ/DTLZ7.txt @@ -0,0 +1,1000 @@ +0.0000000000 4.0000000000 +0.0009738826 3.9990171786 +0.0021185454 3.9978391568 +0.0031014163 3.9968079417 +0.0033247671 3.9965710677 +0.0041389401 3.9956996467 +0.0042370907 3.9955937518 +0.0044078709 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Authors: // Antonio J. Nebro // Juan J. Durillo -// +// // Copyright (c) 2011 Antonio J. Nebro, Juan J. Durillo // // This program is free software: you can redistribute it and/or modify @@ -15,103 +15,119 @@ // but WITHOUT ANY WARRANTY; without even the implied warranty of // MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the // GNU Lesser General Public License for more details. -// +// // You should have received a copy of the GNU Lesser General Public License // along with this program. If not, see . #include - + /** * Class constructor */ -Fonseca::Fonseca(string solutionType) { - numberOfVariables_ = 3; - numberOfObjectives_ = 2; - numberOfConstraints_ = 0; - problemName_ = "Fonseca"; - - lowerLimit_ = new double[numberOfVariables_]; - if (lowerLimit_ == NULL) { - cout << "Fonseca::Fonseca. Error reserving memory for storing the array of lower limits" << endl; - } // if - - upperLimit_ = new double[numberOfVariables_]; - if (upperLimit_ == NULL) { - cout << "Fonseca::Fonseca. Error reserving memory for storing the array of upper limits" << endl; - exit(-1) ; - } // if - - for (int i = 0; i < numberOfVariables_; i++) { - lowerLimit_[i] = -4.0; - upperLimit_[i] = 4.0; - } // for - - if (solutionType.compare("BinaryReal") == 0) { - //cout << "Selected solution type: BinaryReal" << endl; - solutionType_ = new BinaryRealSolutionType(this) ; - } else if (solutionType.compare("Real") == 0) { - solutionType_ = new RealSolutionType(this) ; - //cout << "Selected solution type: Real" << endl; - } else if (solutionType.compare("ArrayReal") == 0) { - solutionType_ = new ArrayRealSolutionType(this) ; - } else { - cout << "Error: solution type " << solutionType << " invalid" << endl; - exit(-1) ; - } +Fonseca::Fonseca(std::string solutionType) +{ + numberOfVariables_ = 3; + numberOfObjectives_ = 2; + numberOfConstraints_ = 0; + problemName_ = "Fonseca"; + + lowerLimit_ = snew double[numberOfVariables_]; + if (lowerLimit_ == nullptr) + { + std::cout << "Fonseca::Fonseca. Error reserving memory for storing the array of lower limits" << std::endl; + } // if + + upperLimit_ = snew double[numberOfVariables_]; + if (upperLimit_ == nullptr) + { + std::cout << "Fonseca::Fonseca. Error reserving memory for storing the array of upper limits" << std::endl; + exit(-1) ; + } // if + + for (int i = 0; i < numberOfVariables_; i++) + { + lowerLimit_[i] = -4.0; + upperLimit_[i] = 4.0; + } // for + + if (solutionType.compare("BinaryReal") == 0) + { + //std::cout << "Selected solution type: BinaryReal" << std::endl; + solutionType_ = snew BinaryRealSolutionType(this) ; + } + else if (solutionType.compare("Real") == 0) + { + solutionType_ = snew RealSolutionType(this) ; + //std::cout << "Selected solution type: Real" << std::endl; + } + else if (solutionType.compare("ArrayReal") == 0) + { + solutionType_ = snew ArrayRealSolutionType(this) ; + } + else + { + std::cout << "Error: solution type " << solutionType << " invalid" << std::endl; + exit(-1) ; + } } // Fonseca /** * Destructor */ -Fonseca::~Fonseca() { - delete [] lowerLimit_ ; - delete [] upperLimit_ ; - delete solutionType_ ; +Fonseca::~Fonseca() +{ + delete [] lowerLimit_ ; + delete [] upperLimit_ ; + delete solutionType_ ; } // ~Fonseca /** * Evaluates a solution */ -void Fonseca::evaluate(Solution *solution) { - double *fx; - double *x ; - Variable **variables = solution->getDecisionVariables(); - - fx = new double[numberOfObjectives_]; - if (fx == NULL) { - cout << "Fonseca::evaluate: Error reserving memory for the function values array" << endl; - exit(-1); - } // if - - x = new double[numberOfVariables_]; - if (x == NULL) { - cout << "Fonseca::evaluate: Error reserving memory for the variable values array" << endl; - exit(-1); - } // if - - for (int i = 0; i < numberOfVariables_; i++) - x[i] = variables[i]->getValue() ; - - double sum1 = 0.0 ; - for (int i = 0; i < numberOfVariables_; i++) - sum1 += pow(x[i] - (1.0/sqrt((double)numberOfVariables_)),2.0); - - double exp1 = exp((-1.0)*sum1); - fx[0] = 1 - exp1; - - double sum2 = 0.0; - for (int i = 0; i < numberOfVariables_; i++){ - sum2 += pow(x[i] + (1.0/sqrt((double)numberOfVariables_)),2.0); - } - double exp2 = exp((-1.0)*sum2); - fx[1] = 1 - exp2; - - solution->setObjective(0,fx[0]); - solution->setObjective(1,fx[1]); - - delete[]fx ; - delete[]x ; +void Fonseca::evaluate(Solution *solution) +{ + double *fx; + double *x ; + Variable **variables = solution->getDecisionVariables(); + + fx = snew double[numberOfObjectives_]; + if (fx == nullptr) + { + std::cout << "Fonseca::evaluate: Error reserving memory for the function values array" << std::endl; + exit(-1); + } // if + + x = snew double[numberOfVariables_]; + if (x == nullptr) + { + std::cout << "Fonseca::evaluate: Error reserving memory for the variable values array" << std::endl; + exit(-1); + } // if + + for (int i = 0; i < numberOfVariables_; i++) + x[i] = variables[i]->getValue() ; + + double sum1 = 0.0 ; + for (int i = 0; i < numberOfVariables_; i++) + sum1 += pow(x[i] - (1.0/sqrt((double)numberOfVariables_)),2.0); + + double exp1 = exp((-1.0)*sum1); + fx[0] = 1 - exp1; + + double sum2 = 0.0; + for (int i = 0; i < numberOfVariables_; i++) + { + sum2 += pow(x[i] + (1.0/sqrt((double)numberOfVariables_)),2.0); + } + double exp2 = exp((-1.0)*sum2); + fx[1] = 1 - exp2; + + solution->setObjective(0,fx[0]); + solution->setObjective(1,fx[1]); + + delete[]fx ; + delete[]x ; } // evaluate diff --git a/src/problems/Fonseca.h b/src/problems/Fonseca.h index 811ebd9..fdaacf3 100644 --- a/src/problems/Fonseca.h +++ b/src/problems/Fonseca.h @@ -3,7 +3,7 @@ // Authors: // Antonio J. Nebro // Juan J. Durillo -// +// // Copyright (c) 2011 Antonio J. Nebro, Juan J. Durillo // // This program is free software: you can redistribute it and/or modify @@ -15,7 +15,7 @@ // but WITHOUT ANY WARRANTY; without even the implied warranty of // MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the // GNU Lesser General Public License for more details. -// +// // You should have received a copy of the GNU Lesser General Public License // along with this program. If not, see . @@ -33,11 +33,12 @@ * @class Fonseca * @brief Class representing problem Fonseca **/ -class Fonseca : public Problem { +class Fonseca : public Problem +{ public: - Fonseca(string solutionType); - ~Fonseca(); - void evaluate(Solution *solution); + Fonseca(std::string solutionType); + ~Fonseca(); + void evaluate(Solution *solution); }; #endif diff --git a/src/problems/Kursawe.cpp b/src/problems/Kursawe.cpp index ca8be1e..8cdf2dd 100644 --- a/src/problems/Kursawe.cpp +++ b/src/problems/Kursawe.cpp @@ -36,51 +36,58 @@ * @param numberOfVariables Number of variables of the problem * @param solutionType The solution type must "Real", "BinaryReal, and "ArrayReal". */ -Kursawe::Kursawe(string solutionType, int numberOfVariables) { - numberOfVariables_ = numberOfVariables; - numberOfObjectives_ = 2; - numberOfConstraints_ = 0; - problemName_ = "Kursawe"; - - lowerLimit_ = new double[numberOfVariables_]; - if (lowerLimit_ == NULL) { - cout << "Impossible to reserve memory for storing the variable lower limits" << endl; - exit(-1); - } - - upperLimit_ = new double[numberOfVariables_]; - if (upperLimit_ == NULL) { - cout << "Impossible to reserve memory for storing the variable lower limits" << endl; - exit(-1); - } - - for (int i = 0; i < numberOfVariables_; i++) { - lowerLimit_[i] = -5.0; - upperLimit_[i] = 5.0; - } - - if (solutionType.compare("BinaryReal") == 0) - solutionType_ = new BinaryRealSolutionType(this) ; - else if (solutionType.compare("Real") == 0) { - solutionType_ = new RealSolutionType(this) ; - //cout << "Tipo seleccionado Real" << endl; - } - else if (solutionType.compare("ArrayReal") == 0) - solutionType_ = new ArrayRealSolutionType(this) ; - else { - cout << "Error: solution type " << solutionType << " invalid" << endl; - exit(-1) ; - } +Kursawe::Kursawe(std::string solutionType, int numberOfVariables) +{ + numberOfVariables_ = numberOfVariables; + numberOfObjectives_ = 2; + numberOfConstraints_ = 0; + problemName_ = "Kursawe"; + + lowerLimit_ = snew double[numberOfVariables_]; + if (lowerLimit_ == nullptr) + { + std::cout << "Impossible to reserve memory for storing the variable lower limits" << std::endl; + exit(-1); + } + + upperLimit_ = snew double[numberOfVariables_]; + if (upperLimit_ == nullptr) + { + std::cout << "Impossible to reserve memory for storing the variable lower limits" << std::endl; + exit(-1); + } + + for (int i = 0; i < numberOfVariables_; i++) + { + lowerLimit_[i] = -5.0; + upperLimit_[i] = 5.0; + } + + if (solutionType.compare("BinaryReal") == 0) + solutionType_ = snew BinaryRealSolutionType(this) ; + else if (solutionType.compare("Real") == 0) + { + solutionType_ = snew RealSolutionType(this) ; + //std::cout << "Tipo seleccionado Real" << std::endl; + } + else if (solutionType.compare("ArrayReal") == 0) + solutionType_ = snew ArrayRealSolutionType(this) ; + else + { + std::cout << "Error: solution type " << solutionType << " invalid" << std::endl; + exit(-1) ; + } } // Kursawe /** * Destructor */ -Kursawe::~Kursawe() { - delete [] lowerLimit_ ; - delete [] upperLimit_ ; - delete solutionType_ ; +Kursawe::~Kursawe() +{ + delete [] lowerLimit_ ; + delete [] upperLimit_ ; + delete solutionType_ ; } // ~Kursawe @@ -88,43 +95,48 @@ Kursawe::~Kursawe() { * Evaluates a solution * @param solution The solution to evaluate */ -void Kursawe::evaluate(Solution *solution) { - - XReal * vars = new XReal(solution); - - double aux, xi, xj; // auxiliary variables - double * fx = new double[2]; // function values - if (fx == NULL) { - cout << "Error grave: Impossible to reserve memory while evaluating the problem" << endl; - exit(-1); - } - - double * x = new double[numberOfVariables_]; - for (int i = 0 ; i < numberOfVariables_; i++) { - x[i] = vars->getValue(i) ; - } - - fx[0] = 0.0 ; - for (int var = 0; var < numberOfVariables_ - 1; var++) { - xi = x[var] * x[var]; - xj = x[var+1] * x[var+1] ; - aux = (-0.2) * sqrt(xi + xj); - fx[0] += (-10.0) * exp(aux); - } // for - - fx[1] = 0.0; - - for (int var = 0; var < numberOfVariables_ ; var++) { - fx[1] += pow(fabs(x[var]), 0.8) + - 5.0 * sin(pow(x[var], 3.0)); - } // for - - solution->setObjective(0,fx[0]); - solution->setObjective(1,fx[1]); - - delete [] fx; - delete [] x; - delete vars; +void Kursawe::evaluate(Solution *solution) +{ + + XReal * vars = snew XReal(solution); + + double aux, xi, xj; // auxiliary variables + double * fx = snew double[2]; // function values + if (fx == nullptr) + { + std::cout << "Error grave: Impossible to reserve memory while evaluating the problem" << std::endl; + exit(-1); + } + + double * x = snew double[numberOfVariables_]; + for (int i = 0 ; i < numberOfVariables_; i++) + { + x[i] = vars->getValue(i) ; + } + + fx[0] = 0.0 ; + for (int var = 0; var < numberOfVariables_ - 1; var++) + { + xi = x[var] * x[var]; + xj = x[var+1] * x[var+1] ; + aux = (-0.2) * sqrt(xi + xj); + fx[0] += (-10.0) * exp(aux); + } // for + + fx[1] = 0.0; + + for (int var = 0; var < numberOfVariables_ ; var++) + { + fx[1] += pow(fabs(x[var]), 0.8) + + 5.0 * sin(pow(x[var], 3.0)); + } // for + + solution->setObjective(0,fx[0]); + solution->setObjective(1,fx[1]); + + delete [] fx; + delete [] x; + delete vars; } // evaluate diff --git a/src/problems/Kursawe.h b/src/problems/Kursawe.h index 840971c..0d34a8d 100644 --- a/src/problems/Kursawe.h +++ b/src/problems/Kursawe.h @@ -31,17 +31,18 @@ #include #include -//using namespace std; +// /** * Class representing problem Kursawe */ -class Kursawe : public Problem { +class Kursawe : public Problem +{ public: - Kursawe(string solutionType, int numberOfVariables = 3); - ~Kursawe(); - void evaluate(Solution *solution); + Kursawe(std::string solutionType, int numberOfVariables = 3); + ~Kursawe(); + void evaluate(Solution *solution); }; #endif diff --git a/src/problems/LZ09/CMakeLists.txt b/src/problems/LZ09/CMakeLists.txt new file mode 100644 index 0000000..294ec59 --- /dev/null +++ b/src/problems/LZ09/CMakeLists.txt @@ -0,0 +1,3 @@ +file(GLOB SOURCES "*.cpp" "*.h") +ListToString(SOURCES ";" ${SOURCES}) +LIST_APPEND("${SOURCES}") \ No newline at end of file diff --git a/src/problems/LZ09/LZ09.cpp b/src/problems/LZ09/LZ09.cpp index a3c8e63..689ba32 100644 --- a/src/problems/LZ09/LZ09.cpp +++ b/src/problems/LZ09/LZ09.cpp @@ -23,68 +23,81 @@ /** * Constructor */ -LZ09::LZ09(int nvar, int nobj, int ptype, int dtype, int ltype) { - nvar_ = nvar ; - nobj_ = nobj ; - ltype_ = ltype ; - dtype_ = dtype ; - ptype_ = ptype ; +LZ09::LZ09(int nvar, int nobj, int ptype, int dtype, int ltype) +{ + nvar_ = nvar ; + nobj_ = nobj ; + ltype_ = ltype ; + dtype_ = dtype ; + ptype_ = ptype ; } // LZ09::LZ09 /** * Alpha function */ -void LZ09::alphaFunction(double *alpha, vector * x, int dim, int type) { - if (dim == 2) { - if (type == 21) { - alpha[0] = x->at(0); - alpha[1] = 1 - sqrt(x->at(0)); - } - - if (type == 22) { - alpha[0] = x->at(0); - alpha[1] = 1 - x->at(0) * x->at(0); - } - - if (type == 23) { - alpha[0] = x->at(0); - alpha[1] = 1 - sqrt(alpha[0]) - alpha[0] - * sin(10 * alpha[0] * alpha[0] * 3.141596); - } - - if (type == 24) { - alpha[0] = x->at(0); - alpha[1] = 1 - x->at(0) - 0.05 * sin(4 * 3.141596 * x->at(0)); - } - } else { - if (type == 31) { - alpha[0] = cos(x->at(0) * 3.141596 / 2) * cos(x->at(1) * 3.141596 / 2); - alpha[1] = cos(x->at(0) * 3.141596 / 2) * sin(x->at(1) * 3.141596 / 2); - alpha[2] = sin(x->at(0) * 3.141596 / 2); - } - - if (type == 32) { - alpha[0] = 1 - cos(x->at(0) * 3.141596 / 2) - * cos(x->at(1) * 3.141596 / 2); - alpha[1] = 1 - cos(x->at(0) * 3.141596 / 2) - * sin(x->at(1) * 3.141596 / 2); - alpha[2] = 1 - sin(x->at(0) * 3.141596 / 2); - } - - if (type == 33) { - alpha[0] = x->at(0); - alpha[1] = x->at(1); - alpha[2] = 3 - - (sin(3 * 3.141596 * x->at(0)) + sin(3 * 3.141596 * x->at(1))) - 2 - * (x->at(0) + x->at(1)); - } - - if (type == 34) { - alpha[0] = x->at(0) * x->at(1); - alpha[1] = x->at(0) * (1 - x->at(1)); - alpha[2] = (1 - x->at(0)); - } - } +void LZ09::alphaFunction(double *alpha, VectorOfDouble * x, int dim, int type) +{ + if (dim == 2) + { + if (type == 21) + { + alpha[0] = (*x)[0]; + alpha[1] = 1 - sqrt((*x)[0]); + } + + if (type == 22) + { + alpha[0] = (*x)[0]; + alpha[1] = 1 - (*x)[0] * (*x)[0]; + } + + if (type == 23) + { + alpha[0] = (*x)[0]; + alpha[1] = 1 - sqrt(alpha[0]) - alpha[0] + * sin(10 * alpha[0] * alpha[0] * 3.141596); + } + + if (type == 24) + { + alpha[0] = (*x)[0]; + alpha[1] = 1 - (*x)[0] - 0.05 * sin(4 * 3.141596 * (*x)[0]); + } + } + else + { + if (type == 31) + { + alpha[0] = cos((*x)[0] * 3.141596 / 2) * cos(x->at(1) * 3.141596 / 2); + alpha[1] = cos((*x)[0] * 3.141596 / 2) * sin(x->at(1) * 3.141596 / 2); + alpha[2] = sin((*x)[0] * 3.141596 / 2); + } + + if (type == 32) + { + alpha[0] = 1 - cos((*x)[0] * 3.141596 / 2) + * cos(x->at(1) * 3.141596 / 2); + alpha[1] = 1 - cos((*x)[0] * 3.141596 / 2) + * sin(x->at(1) * 3.141596 / 2); + alpha[2] = 1 - sin((*x)[0] * 3.141596 / 2); + } + + if (type == 33) + { + alpha[0] = (*x)[0]; + alpha[1] = x->at(1); + alpha[2] = 3 + - (sin(3 * 3.141596 * (*x)[0]) + sin(3 * 3.141596 * x->at(1))) - 2 + * ((*x)[0] + x->at(1)); + } + + if (type == 34) + { + alpha[0] = (*x)[0] * x->at(1); + alpha[1] = (*x)[0] * (1 - x->at(1)); + alpha[2] = (1 - (*x)[0]); + } + } } /** @@ -92,245 +105,272 @@ void LZ09::alphaFunction(double *alpha, vector * x, int dim, int type) { */ -double LZ09::betaFunction(vector * x, int type) { - - double beta; - beta = 0; - - int dim = x->size() ; - - if (dim == 0) - beta = 0; - - if (type == 1) { - beta = 0; - for (int i = 0; i < dim; i++) { - beta += x->at(i) * x->at(i); - } - beta = 2.0 * beta / dim; - } - - if (type == 2) { - beta = 0; - for (int i = 0; i < dim; i++) { - beta += sqrt(i + 1) * x->at(i) * x->at(i); - } - beta = 2.0 * beta / dim; - } - - if (type == 3) { - double sum = 0, xx; - for (int i = 0; i < dim; i++) { - xx = 2 * x->at(i); - sum += (xx * xx - cos(4 * 3.141596 * xx) + 1); - } - beta = 2.0 * sum / dim; - } - - if (type == 4) { - double sum = 0, prod = 1, xx; - for (int i = 0; i < dim; i++) { - xx = 2 * x->at(i); - sum += xx * xx; - prod *= cos(10 * 3.141596 * xx / sqrt(i + 1)); - } - beta = 2.0 * (sum - 2 * prod + 2) / dim; - } - return beta; +double LZ09::betaFunction(VectorOfDouble * x, int type) +{ + + double beta; + beta = 0; + + int dim = x->size() ; + + if (dim == 0) + beta = 0; + + if (type == 1) + { + beta = 0; + for (int i = 0; i < dim; i++) + { + beta += x->at(i) * x->at(i); + } + beta = 2.0 * beta / dim; + } + + if (type == 2) + { + beta = 0; + for (int i = 0; i < dim; i++) + { + beta += sqrt(i + 1) * x->at(i) * x->at(i); + } + beta = 2.0 * beta / dim; + } + + if (type == 3) + { + double sum = 0, xx; + for (int i = 0; i < dim; i++) + { + xx = 2 * x->at(i); + sum += (xx * xx - cos(4 * 3.141596 * xx) + 1); + } + beta = 2.0 * sum / dim; + } + + if (type == 4) + { + double sum = 0, prod = 1, xx; + for (int i = 0; i < dim; i++) + { + xx = 2 * x->at(i); + sum += xx * xx; + prod *= cos(10 * 3.141596 * xx / sqrt(i + 1)); + } + beta = 2.0 * (sum - 2 * prod + 2) / dim; + } + return beta; } -double LZ09::psfunc2(double x, double t1, int dim, int type, int css) { - double beta; - beta = 0.0; - - dim++; - - if(type==21){ - double xy = 2*(x - 0.5); - beta = xy - pow(t1, 0.5*(nvar_ + 3*dim - 8)/(nvar_ - 2)); - } - - if(type==22){ - double theta = 6*3.141596*t1 + dim*3.141596/nvar_; - double xy = 2*(x - 0.5); - beta = xy - sin(theta); - } - - if(type==23){ - double theta = 6*3.141596*t1 + dim*3.141596/nvar_; - double ra = 0.8*t1; - double xy = 2*(x - 0.5); - if(css==1) - beta = xy - ra*cos(theta); - else{ - beta = xy - ra*sin(theta); - } - } - - if(type==24){ - double theta = 6*3.141596*t1 + dim*3.141596/nvar_; - double xy = 2*(x - 0.5); - double ra = 0.8*t1; - if(css==1) - beta = xy - ra*cos(theta/3); - else{ - beta = xy - ra*sin(theta); - } - } - - if(type==25){ - double rho = 0.8; - double phi = 3.141596*t1; - double theta = 6*3.141596*t1 + dim*3.141596/nvar_; - double xy = 2*(x - 0.5); - if(css==1) - beta = xy - rho*sin(phi)*sin(theta); - else if(css==2) - beta = xy - rho*sin(phi)*cos(theta); - else - beta = xy - rho*cos(phi); - } - - if(type==26){ - double theta = 6*3.141596*t1 + dim*3.141596/nvar_; - double ra = 0.3*t1*(t1*cos(4*theta) + 2); - double xy = 2*(x - 0.5); - if(css==1) - beta = xy - ra*cos(theta); - else{ - beta = xy - ra*sin(theta); - } - } - - return beta; +double LZ09::psfunc2(double x, double t1, int dim, int type, int css) +{ + double beta; + beta = 0.0; + + dim++; + + if(type==21) + { + double xy = 2*(x - 0.5); + beta = xy - pow(t1, 0.5*(nvar_ + 3*dim - 8)/(nvar_ - 2)); + } + + if(type==22) + { + double theta = 6*3.141596*t1 + dim*3.141596/nvar_; + double xy = 2*(x - 0.5); + beta = xy - sin(theta); + } + + if(type==23) + { + double theta = 6*3.141596*t1 + dim*3.141596/nvar_; + double ra = 0.8*t1; + double xy = 2*(x - 0.5); + if(css==1) + beta = xy - ra*cos(theta); + else + { + beta = xy - ra*sin(theta); + } + } + + if(type==24) + { + double theta = 6*3.141596*t1 + dim*3.141596/nvar_; + double xy = 2*(x - 0.5); + double ra = 0.8*t1; + if(css==1) + beta = xy - ra*cos(theta/3); + else + { + beta = xy - ra*sin(theta); + } + } + + if(type==25) + { + double rho = 0.8; + double phi = 3.141596*t1; + double theta = 6*3.141596*t1 + dim*3.141596/nvar_; + double xy = 2*(x - 0.5); + if(css==1) + beta = xy - rho*sin(phi)*sin(theta); + else if(css==2) + beta = xy - rho*sin(phi)*cos(theta); + else + beta = xy - rho*cos(phi); + } + + if(type==26) + { + double theta = 6*3.141596*t1 + dim*3.141596/nvar_; + double ra = 0.3*t1*(t1*cos(4*theta) + 2); + double xy = 2*(x - 0.5); + if(css==1) + beta = xy - ra*cos(theta); + else + { + beta = xy - ra*sin(theta); + } + } + + return beta; } -double LZ09::psfunc3(double x, double t1, double t2, int dim, int type){ - // type: the type of curve - // css: the class of index - double beta; - beta = 0.0 ; - - dim++; - - if(type==31){ - double xy = 4*(x - 0.5); - double rate = 1.0*dim/nvar_; - beta = xy - 4*(t1*t1*rate + t2*(1.0-rate)) + 2; - } - - if(type==32){ - double theta = 2*3.141596*t1 + dim*3.141596/nvar_; - double xy = 4*(x - 0.5); - beta = xy - 2*t2*sin(theta); - } - - return beta; +double LZ09::psfunc3(double x, double t1, double t2, int dim, int type) +{ + // type: the type of curve + // css: the class of index + double beta; + beta = 0.0 ; + + dim++; + + if(type==31) + { + double xy = 4*(x - 0.5); + double rate = 1.0*dim/nvar_; + beta = xy - 4*(t1*t1*rate + t2*(1.0-rate)) + 2; + } + + if(type==32) + { + double theta = 2*3.141596*t1 + dim*3.141596/nvar_; + double xy = 4*(x - 0.5); + beta = xy - 2*t2*sin(theta); + } + + return beta; } -void LZ09::objective(vector *x_var, vector *y_obj) { - // 2-objective case - if(nobj_==2) - { - if(ltype_==21||ltype_==22||ltype_==23||ltype_==24||ltype_==26) - { - double g = 0, h = 0, a, b; - vector aa ; // *aa = new vector(); - vector bb ; // *bb = new vector(); - for(int n=1;nat(n),x_var->at(0),n,ltype_,1); // linkage - aa.push_back(a); - } - else - { - b = psfunc2(x_var->at(n),x_var->at(0),n,ltype_,2); - bb.push_back(b); - } - - } - - g = betaFunction(&aa, dtype_); - h = betaFunction(&bb, dtype_); - - double alpha[2] ; - alphaFunction(alpha,x_var,2,ptype_); // shape function - y_obj->at(0) = alpha[0] + h; - y_obj->at(1) = alpha[1] + g; - aa.clear(); - bb.clear(); - } - - if(ltype_==25) - { - double g = 0, h = 0, a, b; - double e = 0, c; - vector aa ; //= new Vector() ; - vector bb ; //= new Vector() ; - for(int n=1;nat(n),x_var->at(0),n,ltype_,1); - aa.push_back(a); - } - else if(n%3==1) - { - b = psfunc2(x_var->at(n),x_var->at(0),n,ltype_,2); - bb.push_back(b); - } - else{ - c = psfunc2(x_var->at(n),x_var->at(0),n,ltype_,3); - if(n%2==0) aa.push_back(c); - else bb.push_back(c); - } - } - g = betaFunction(&aa,dtype_); // distance function - h = betaFunction(&bb,dtype_); - - //double * alpha = new double[2]; - double alpha[2] ; - alphaFunction(alpha,x_var,2,ptype_); // shape function - y_obj->at(0) = alpha[0] + h; - y_obj->at(1) = alpha[1] + g; - aa.clear(); - bb.clear(); - } - } - - - // 3-objective case - if(nobj_==3) - { - if(ltype_==31||ltype_==32) - { - double g = 0, h = 0, e = 0, a; - vector aa ; - vector bb ; - vector cc ; - for(int n=2;nat(n),x_var->at(0),x_var->at(1),n,ltype_); - if(n%3==0) aa.push_back(a); - else if(n%3==1) bb.push_back(a); - else cc.push_back(a); - } - - g = betaFunction(&aa,dtype_); - h = betaFunction(&bb,dtype_); - e = betaFunction(&cc,dtype_); - - //double * alpha = new double[3]; - double alpha[3] ; - alphaFunction(alpha,x_var,3,ptype_); // shape function - y_obj->at(0) = alpha[0] + h; - y_obj->at(1) = alpha[1] + g; - y_obj->at(2) = alpha[2] + e; - aa.clear(); - bb.clear(); - cc.clear(); - } - } +void LZ09::objective(VectorOfDouble *x_var, std::vector *y_obj) +{ + // 2-objective case + if(nobj_==2) + { + if(ltype_==21||ltype_==22||ltype_==23||ltype_==24||ltype_==26) + { + double g = 0, h = 0, a, b; + std::vector aa ; // *aa = new vector(); + std::vector bb ; // *bb = new vector(); + for(int n=1; nat(n),x_var->at(0),n,ltype_,1); // linkage + aa.push_back(a); + } + else + { + b = psfunc2(x_var->at(n),x_var->at(0),n,ltype_,2); + bb.push_back(b); + } + + } + + g = betaFunction(&aa, dtype_); + h = betaFunction(&bb, dtype_); + + double alpha[2] ; + alphaFunction(alpha,x_var,2,ptype_); // shape function + y_obj->at(0) = alpha[0] + h; + y_obj->at(1) = alpha[1] + g; + aa.clear(); + bb.clear(); + } + + if(ltype_==25) + { + double g = 0, h = 0, a, b; + double e = 0, c; + std::vector aa ; //= new Vector() ; + std::vector bb ; //= new Vector() ; + for(int n=1; nat(n),x_var->at(0),n,ltype_,1); + aa.push_back(a); + } + else if(n%3==1) + { + b = psfunc2(x_var->at(n),x_var->at(0),n,ltype_,2); + bb.push_back(b); + } + else + { + c = psfunc2(x_var->at(n),x_var->at(0),n,ltype_,3); + if(n%2==0) aa.push_back(c); + else bb.push_back(c); + } + } + g = betaFunction(&aa,dtype_); // distance function + h = betaFunction(&bb,dtype_); + + //double * alpha = snew double[2]; + double alpha[2] ; + alphaFunction(alpha,x_var,2,ptype_); // shape function + y_obj->at(0) = alpha[0] + h; + y_obj->at(1) = alpha[1] + g; + aa.clear(); + bb.clear(); + } + } + + + // 3-objective case + if(nobj_==3) + { + if(ltype_==31||ltype_==32) + { + double g = 0, h = 0, e = 0, a; + std::vector aa ; + std::vector bb ; + std::vector cc ; + for(int n=2; nat(n),x_var->at(0),x_var->at(1),n,ltype_); + if(n%3==0) aa.push_back(a); + else if(n%3==1) bb.push_back(a); + else cc.push_back(a); + } + + g = betaFunction(&aa,dtype_); + h = betaFunction(&bb,dtype_); + e = betaFunction(&cc,dtype_); + + //double * alpha = snew double[3]; + double alpha[3] ; + alphaFunction(alpha,x_var,3,ptype_); // shape function + y_obj->at(0) = alpha[0] + h; + y_obj->at(1) = alpha[1] + g; + y_obj->at(2) = alpha[2] + e; + aa.clear(); + bb.clear(); + cc.clear(); + } + } } diff --git a/src/problems/LZ09/LZ09.h b/src/problems/LZ09/LZ09.h index a30ae2c..ca23ba6 100644 --- a/src/problems/LZ09/LZ09.h +++ b/src/problems/LZ09/LZ09.h @@ -21,27 +21,28 @@ #ifndef __LZ09_H__ #define __LZ09_H__ +#include "JMetalHeader.h" #include #include -#include -using namespace std; +using namespace JMetal; -class LZ09 { +class LZ09 +{ private: - int nvar_ ; - int nobj_ ; - int ltype_ ; - int dtype_ ; - int ptype_ ; + int nvar_ ; + int nobj_ ; + int ltype_ ; + int dtype_ ; + int ptype_ ; public: - LZ09 (int nvar, int nobj, int ptype, int dtype, int ltype) ; - void alphaFunction(double *alpha, vector *x, int dim, int type) ; - double betaFunction(vector * x, int type) ; - double psfunc2(double x, double t1, int dim, int type, int css) ; - double psfunc3(double x, double t1, double t2, int dim, int type) ; - void objective(vector * x_var, vector * y_obj) ; + LZ09 (int nvar, int nobj, int ptype, int dtype, int ltype) ; + void alphaFunction(double *alpha, VectorOfDouble *x, int dim, int type) ; + double betaFunction(VectorOfDouble * x, int type) ; + double psfunc2(double x, double t1, int dim, int type, int css) ; + double psfunc3(double x, double t1, double t2, int dim, int type) ; + void objective(VectorOfDouble * x_var, std::vector * y_obj) ; }; diff --git a/src/problems/LZ09/LZ09_F1.cpp b/src/problems/LZ09/LZ09_F1.cpp index e8feec5..6e6f94c 100644 --- a/src/problems/LZ09/LZ09_F1.cpp +++ b/src/problems/LZ09/LZ09_F1.cpp @@ -23,82 +23,92 @@ /** * Constructor */ -LZ09_F1::LZ09_F1(string solutionType, int ptype, int dtype, int ltype) { - numberOfVariables_ = 10; - numberOfObjectives_ = 2; - numberOfConstraints_= 0; - problemName_ = "LZ09_F1"; - - LZ09_ = new LZ09(numberOfVariables_, - numberOfObjectives_, - ptype, - dtype, - ltype) ; +LZ09_F1::LZ09_F1(std::string solutionType, int ptype, int dtype, int ltype) +{ + numberOfVariables_ = 10; + numberOfObjectives_ = 2; + numberOfConstraints_= 0; + problemName_ = "LZ09_F1"; - lowerLimit_ = new double[numberOfVariables_]; - if (lowerLimit_ == NULL) { - cout << "LZ09_F1::LZ09_F1: Error reserving memory for storing the " - << "variable lower limits" << endl; - exit(-1); - } + LZ09_ = snew LZ09(numberOfVariables_, + numberOfObjectives_, + ptype, + dtype, + ltype) ; - upperLimit_ = new double[numberOfVariables_]; - if (upperLimit_ == NULL) { - cout << "LZ09_F1::LZ09_F1: Error reserving memory for storing the " - << "variable lower limits" << endl; - exit(-1); - } + lowerLimit_ = snew double[numberOfVariables_]; + if (lowerLimit_ == nullptr) + { + std::cout << "LZ09_F1::LZ09_F1: Error reserving memory for storing the " + << "variable lower limits" << std::endl; + exit(-1); + } - for (int i = 0; i < numberOfVariables_; i++) { - lowerLimit_[i] = 0.0; - upperLimit_[i] = 1.0; - } - - if (solutionType.compare("BinaryReal") == 0) - solutionType_ = new BinaryRealSolutionType(this) ; - else if (solutionType.compare("Real") == 0) { - solutionType_ = new RealSolutionType(this) ; - } - else if (solutionType.compare("ArrayReal") == 0) - solutionType_ = new ArrayRealSolutionType(this) ; - else { - cout << "LZ09_F1::LZ09_F1: solution type " << solutionType << " invalid" << endl; - exit(-1) ; - } - - fx_ = new double[numberOfObjectives_] ; - x_ = new double[numberOfVariables_]; + upperLimit_ = snew double[numberOfVariables_]; + if (upperLimit_ == nullptr) + { + std::cout << "LZ09_F1::LZ09_F1: Error reserving memory for storing the " + << "variable lower limits" << std::endl; + exit(-1); + } + + for (int i = 0; i < numberOfVariables_; i++) + { + lowerLimit_[i] = 0.0; + upperLimit_[i] = 1.0; + } + + if (solutionType.compare("BinaryReal") == 0) + solutionType_ = snew BinaryRealSolutionType(this) ; + else if (solutionType.compare("Real") == 0) + { + solutionType_ = snew RealSolutionType(this) ; + } + else if (solutionType.compare("ArrayReal") == 0) + solutionType_ = snew ArrayRealSolutionType(this) ; + else + { + std::cout << "LZ09_F1::LZ09_F1: solution type " << solutionType << " invalid" << std::endl; + exit(-1) ; + } + + fx_ = snew double[numberOfObjectives_] ; + x_ = snew double[numberOfVariables_]; } // LZ09_F1::LZ09_F1 /** * Destructor */ -LZ09_F1::~LZ09_F1 () { - delete [] lowerLimit_ ; - delete [] upperLimit_ ; - delete solutionType_ ; - delete LZ09_ ; +LZ09_F1::~LZ09_F1 () +{ + delete [] lowerLimit_ ; + delete [] upperLimit_ ; + delete solutionType_ ; + delete LZ09_ ; } -void LZ09_F1::evaluate(Solution * solution) { - XReal * vars = new XReal(solution); - - vector * x = new vector(numberOfVariables_) ; - vector * y = new vector(numberOfObjectives_); +void LZ09_F1::evaluate(Solution * solution) +{ + XReal * vars = snew XReal(solution); + + VectorOfDouble * x = snew VectorOfDouble(numberOfVariables_) ; + VectorOfDouble * y = snew VectorOfDouble(numberOfObjectives_); + + for (int i = 0; i < numberOfVariables_; i++) + { + x->at(i) = vars->getValue(i); + } // for + for (int i = 0; i < numberOfObjectives_; i++) + { + y->at(i) = 0.0 ; + } // for - for (int i = 0; i < numberOfVariables_; i++) { - x->at(i) = vars->getValue(i); - } // for - for (int i = 0; i < numberOfObjectives_; i++) { - y->at(i) = 0.0 ; - } // for + LZ09_->objective(x, y) ; - LZ09_->objective(x, y) ; + for (int i = 0; i < numberOfObjectives_; i++) + solution->setObjective(i, y->at(i)); - for (int i = 0; i < numberOfObjectives_; i++) - solution->setObjective(i, y->at(i)); - - delete x; - delete y; - delete vars; + delete x; + delete y; + delete vars; } diff --git a/src/problems/LZ09/LZ09_F1.h b/src/problems/LZ09/LZ09_F1.h index 77eb236..b5e3fc7 100644 --- a/src/problems/LZ09/LZ09_F1.h +++ b/src/problems/LZ09/LZ09_F1.h @@ -31,16 +31,17 @@ #include #include -class LZ09_F1 : public Problem { +class LZ09_F1 : public Problem +{ public: - LZ09_F1(string solutionType, int ptype=21, int dtype=1, int ltype=21); - void evaluate(Solution *solution); + LZ09_F1(std::string solutionType, int ptype=21, int dtype=1, int ltype=21); + void evaluate(Solution *solution); - virtual ~LZ09_F1(); + virtual ~LZ09_F1(); private: - LZ09 * LZ09_ ; - double * fx_ ; - double * x_ ; + LZ09 * LZ09_ ; + double * fx_ ; + double * x_ ; }; #endif /* __LZ09_F1_H__ */ diff --git a/src/problems/LZ09/LZ09_F2.cpp b/src/problems/LZ09/LZ09_F2.cpp index a1577ea..9c6e7ea 100644 --- a/src/problems/LZ09/LZ09_F2.cpp +++ b/src/problems/LZ09/LZ09_F2.cpp @@ -23,84 +23,94 @@ /** * Constructor */ -LZ09_F2::LZ09_F2(string solutionType, int ptype, int dtype, int ltype) { - numberOfVariables_ = 30; - numberOfObjectives_ = 2; - numberOfConstraints_= 0; - problemName_ = "LZ09_F2"; +LZ09_F2::LZ09_F2(std::string solutionType, int ptype, int dtype, int ltype) +{ + numberOfVariables_ = 30; + numberOfObjectives_ = 2; + numberOfConstraints_= 0; + problemName_ = "LZ09_F2"; - LZ09_ = new LZ09(numberOfVariables_, - numberOfObjectives_, - ptype, - dtype, - ltype) ; + LZ09_ = snew LZ09(numberOfVariables_, + numberOfObjectives_, + ptype, + dtype, + ltype) ; - lowerLimit_ = new double[numberOfVariables_]; - if (lowerLimit_ == NULL) { - cout << "LZ09_F2::LZ09_F2: Error reserving memory for storing the " - << "variable lower limits" << endl; - exit(-1); - } + lowerLimit_ = snew double[numberOfVariables_]; + if (lowerLimit_ == nullptr) + { + std::cout << "LZ09_F2::LZ09_F2: Error reserving memory for storing the " + << "variable lower limits" << std::endl; + exit(-1); + } - upperLimit_ = new double[numberOfVariables_]; - if (upperLimit_ == NULL) { - cout << "LZ09_F2::LZ09_F2: Error reserving memory for storing the " - << "variable lower limits" << endl; - exit(-1); - } + upperLimit_ = snew double[numberOfVariables_]; + if (upperLimit_ == nullptr) + { + std::cout << "LZ09_F2::LZ09_F2: Error reserving memory for storing the " + << "variable lower limits" << std::endl; + exit(-1); + } - lowerLimit_[0] = 0.0; - upperLimit_[0] = 1.0; - for (int i = 1; i < numberOfVariables_; i++) { - lowerLimit_[i] = -1.0; - upperLimit_[i] = 1.0; - } + lowerLimit_[0] = 0.0; + upperLimit_[0] = 1.0; + for (int i = 1; i < numberOfVariables_; i++) + { + lowerLimit_[i] = -1.0; + upperLimit_[i] = 1.0; + } - if (solutionType.compare("BinaryReal") == 0) - solutionType_ = new BinaryRealSolutionType(this) ; - else if (solutionType.compare("Real") == 0) { - solutionType_ = new RealSolutionType(this) ; - } - else if (solutionType.compare("ArrayReal") == 0) - solutionType_ = new ArrayRealSolutionType(this) ; - else { - cout << "LZ09_F2::LZ09_F2: solution type " << solutionType << " invalid" << endl; - exit(-1) ; - } + if (solutionType.compare("BinaryReal") == 0) + solutionType_ = snew BinaryRealSolutionType(this) ; + else if (solutionType.compare("Real") == 0) + { + solutionType_ = snew RealSolutionType(this) ; + } + else if (solutionType.compare("ArrayReal") == 0) + solutionType_ = snew ArrayRealSolutionType(this) ; + else + { + std::cout << "LZ09_F2::LZ09_F2: solution type " << solutionType << " invalid" << std::endl; + exit(-1) ; + } - fx_ = new double[numberOfObjectives_] ; - x_ = new double[numberOfVariables_]; + fx_ = snew double[numberOfObjectives_] ; + x_ = snew double[numberOfVariables_]; } // LZ09_F2::LZ09_F2 /** * Destructor */ -LZ09_F2::~LZ09_F2 () { - delete [] lowerLimit_ ; - delete [] upperLimit_ ; - delete solutionType_ ; - delete LZ09_ ; +LZ09_F2::~LZ09_F2 () +{ + delete [] lowerLimit_ ; + delete [] upperLimit_ ; + delete solutionType_ ; + delete LZ09_ ; } -void LZ09_F2::evaluate(Solution * solution) { - XReal * vars = new XReal(solution); +void LZ09_F2::evaluate(Solution * solution) +{ + XReal * vars = snew XReal(solution); - vector * x = new vector(numberOfVariables_) ; - vector * y = new vector(numberOfObjectives_); + VectorOfDouble * x = snew VectorOfDouble(numberOfVariables_) ; + VectorOfDouble * y = snew VectorOfDouble(numberOfObjectives_); - for (int i = 0; i < numberOfVariables_; i++) { - x->at(i) = vars->getValue(i); - } // for - for (int i = 0; i < numberOfObjectives_; i++) { - y->at(i) = 0.0 ; - } // for + for (int i = 0; i < numberOfVariables_; i++) + { + x->at(i) = vars->getValue(i); + } // for + for (int i = 0; i < numberOfObjectives_; i++) + { + y->at(i) = 0.0 ; + } // for - LZ09_->objective(x, y) ; + LZ09_->objective(x, y) ; - for (int i = 0; i < numberOfObjectives_; i++) - solution->setObjective(i, y->at(i)); - - delete x; - delete y; - delete vars; + for (int i = 0; i < numberOfObjectives_; i++) + solution->setObjective(i, y->at(i)); + + delete x; + delete y; + delete vars; } diff --git a/src/problems/LZ09/LZ09_F2.h b/src/problems/LZ09/LZ09_F2.h index 2628624..3b84471 100644 --- a/src/problems/LZ09/LZ09_F2.h +++ b/src/problems/LZ09/LZ09_F2.h @@ -31,16 +31,17 @@ #include #include -class LZ09_F2 : public Problem { +class LZ09_F2 : public Problem +{ public: - LZ09_F2(string solutionType, int ptype=21, int dtype=1, int ltype=22); - void evaluate(Solution *solution); + LZ09_F2(std::string solutionType, int ptype=21, int dtype=1, int ltype=22); + void evaluate(Solution *solution); - virtual ~LZ09_F2(); + virtual ~LZ09_F2(); private: - LZ09 * LZ09_ ; - double * fx_ ; - double * x_ ; + LZ09 * LZ09_ ; + double * fx_ ; + double * x_ ; }; #endif /* __LZ09_F2_H__ */ diff --git a/src/problems/LZ09/LZ09_F3.cpp b/src/problems/LZ09/LZ09_F3.cpp index d595ca4..e194dcd 100644 --- a/src/problems/LZ09/LZ09_F3.cpp +++ b/src/problems/LZ09/LZ09_F3.cpp @@ -23,84 +23,94 @@ /** * Constructor */ -LZ09_F3::LZ09_F3(string solutionType, int ptype, int dtype, int ltype) { - numberOfVariables_ = 30; - numberOfObjectives_ = 2; - numberOfConstraints_= 0; - problemName_ = "LZ09_F3"; +LZ09_F3::LZ09_F3(std::string solutionType, int ptype, int dtype, int ltype) +{ + numberOfVariables_ = 30; + numberOfObjectives_ = 2; + numberOfConstraints_= 0; + problemName_ = "LZ09_F3"; - LZ09_ = new LZ09(numberOfVariables_, - numberOfObjectives_, - ptype, - dtype, - ltype) ; + LZ09_ = snew LZ09(numberOfVariables_, + numberOfObjectives_, + ptype, + dtype, + ltype) ; - lowerLimit_ = new double[numberOfVariables_]; - if (lowerLimit_ == NULL) { - cout << "LZ09_F3::LZ09_F3: Error reserving memory for storing the " - << "variable lower limits" << endl; - exit(-1); - } + lowerLimit_ = snew double[numberOfVariables_]; + if (lowerLimit_ == nullptr) + { + std::cout << "LZ09_F3::LZ09_F3: Error reserving memory for storing the " + << "variable lower limits" << std::endl; + exit(-1); + } - upperLimit_ = new double[numberOfVariables_]; - if (upperLimit_ == NULL) { - cout << "LZ09_F3::LZ09_F3: Error reserving memory for storing the " - << "variable lower limits" << endl; - exit(-1); - } + upperLimit_ = snew double[numberOfVariables_]; + if (upperLimit_ == nullptr) + { + std::cout << "LZ09_F3::LZ09_F3: Error reserving memory for storing the " + << "variable lower limits" << std::endl; + exit(-1); + } - lowerLimit_[0] = 0.0; - upperLimit_[0] = 1.0; - for (int i = 1; i < numberOfVariables_; i++) { - lowerLimit_[i] = -1.0; - upperLimit_[i] = 1.0; - } + lowerLimit_[0] = 0.0; + upperLimit_[0] = 1.0; + for (int i = 1; i < numberOfVariables_; i++) + { + lowerLimit_[i] = -1.0; + upperLimit_[i] = 1.0; + } - if (solutionType.compare("BinaryReal") == 0) - solutionType_ = new BinaryRealSolutionType(this) ; - else if (solutionType.compare("Real") == 0) { - solutionType_ = new RealSolutionType(this) ; - } - else if (solutionType.compare("ArrayReal") == 0) - solutionType_ = new ArrayRealSolutionType(this) ; - else { - cout << "LZ09_F3::LZ09_F3: solution type " << solutionType << " invalid" << endl; - exit(-1) ; - } + if (solutionType.compare("BinaryReal") == 0) + solutionType_ = snew BinaryRealSolutionType(this) ; + else if (solutionType.compare("Real") == 0) + { + solutionType_ = snew RealSolutionType(this) ; + } + else if (solutionType.compare("ArrayReal") == 0) + solutionType_ = snew ArrayRealSolutionType(this) ; + else + { + std::cout << "LZ09_F3::LZ09_F3: solution type " << solutionType << " invalid" << std::endl; + exit(-1) ; + } - fx_ = new double[numberOfObjectives_] ; - x_ = new double[numberOfVariables_]; + fx_ = snew double[numberOfObjectives_] ; + x_ = snew double[numberOfVariables_]; } // LZ09_F3::LZ09_F3 /** * Destructor */ -LZ09_F3::~LZ09_F3 () { - delete [] lowerLimit_ ; - delete [] upperLimit_ ; - delete solutionType_ ; - delete LZ09_ ; +LZ09_F3::~LZ09_F3 () +{ + delete [] lowerLimit_ ; + delete [] upperLimit_ ; + delete solutionType_ ; + delete LZ09_ ; } -void LZ09_F3::evaluate(Solution * solution) { - XReal * vars = new XReal(solution); +void LZ09_F3::evaluate(Solution * solution) +{ + XReal * vars = snew XReal(solution); - vector * x = new vector(numberOfVariables_) ; - vector * y = new vector(numberOfObjectives_); + VectorOfDouble * x = snew VectorOfDouble(numberOfVariables_) ; + VectorOfDouble * y = snew VectorOfDouble(numberOfObjectives_); - for (int i = 0; i < numberOfVariables_; i++) { - x->at(i) = vars->getValue(i); - } // for - for (int i = 0; i < numberOfObjectives_; i++) { - y->at(i) = 0.0 ; - } // for + for (int i = 0; i < numberOfVariables_; i++) + { + x->at(i) = vars->getValue(i); + } // for + for (int i = 0; i < numberOfObjectives_; i++) + { + y->at(i) = 0.0 ; + } // for - LZ09_->objective(x, y) ; + LZ09_->objective(x, y) ; - for (int i = 0; i < numberOfObjectives_; i++) - solution->setObjective(i, y->at(i)); - - delete x; - delete y; - delete vars; + for (int i = 0; i < numberOfObjectives_; i++) + solution->setObjective(i, y->at(i)); + + delete x; + delete y; + delete vars; } diff --git a/src/problems/LZ09/LZ09_F3.h b/src/problems/LZ09/LZ09_F3.h index 1f20042..76e6a27 100644 --- a/src/problems/LZ09/LZ09_F3.h +++ b/src/problems/LZ09/LZ09_F3.h @@ -31,16 +31,17 @@ #include #include -class LZ09_F3 : public Problem { +class LZ09_F3 : public Problem +{ public: - LZ09_F3(string solutionType, int ptype=21, int dtype=1, int ltype=23); - void evaluate(Solution *solution); + LZ09_F3(std::string solutionType, int ptype=21, int dtype=1, int ltype=23); + void evaluate(Solution *solution); - virtual ~LZ09_F3(); + virtual ~LZ09_F3(); private: - LZ09 * LZ09_ ; - double * fx_ ; - double * x_ ; + LZ09 * LZ09_ ; + double * fx_ ; + double * x_ ; }; #endif /* __LZ09_F3_H__ */ diff --git a/src/problems/LZ09/LZ09_F4.cpp b/src/problems/LZ09/LZ09_F4.cpp index aa34899..ae71f97 100644 --- a/src/problems/LZ09/LZ09_F4.cpp +++ b/src/problems/LZ09/LZ09_F4.cpp @@ -23,84 +23,94 @@ /** * Constructor */ -LZ09_F4::LZ09_F4(string solutionType, int ptype, int dtype, int ltype) { - numberOfVariables_ = 30; - numberOfObjectives_ = 2; - numberOfConstraints_= 0; - problemName_ = "LZ09_F4"; +LZ09_F4::LZ09_F4(std::string solutionType, int ptype, int dtype, int ltype) +{ + numberOfVariables_ = 30; + numberOfObjectives_ = 2; + numberOfConstraints_= 0; + problemName_ = "LZ09_F4"; - LZ09_ = new LZ09(numberOfVariables_, - numberOfObjectives_, - ptype, - dtype, - ltype) ; + LZ09_ = snew LZ09(numberOfVariables_, + numberOfObjectives_, + ptype, + dtype, + ltype) ; - lowerLimit_ = new double[numberOfVariables_]; - if (lowerLimit_ == NULL) { - cout << "LZ09_F4::LZ09_F4: Error reserving memory for storing the " - << "variable lower limits" << endl; - exit(-1); - } + lowerLimit_ = snew double[numberOfVariables_]; + if (lowerLimit_ == nullptr) + { + std::cout << "LZ09_F4::LZ09_F4: Error reserving memory for storing the " + << "variable lower limits" << std::endl; + exit(-1); + } - upperLimit_ = new double[numberOfVariables_]; - if (upperLimit_ == NULL) { - cout << "LZ09_F4::LZ09_F4: Error reserving memory for storing the " - << "variable lower limits" << endl; - exit(-1); - } + upperLimit_ = snew double[numberOfVariables_]; + if (upperLimit_ == nullptr) + { + std::cout << "LZ09_F4::LZ09_F4: Error reserving memory for storing the " + << "variable lower limits" << std::endl; + exit(-1); + } - lowerLimit_[0] = 0.0; - upperLimit_[0] = 1.0; - for (int i = 1; i < numberOfVariables_; i++) { - lowerLimit_[i] = -1.0; - upperLimit_[i] = 1.0; - } + lowerLimit_[0] = 0.0; + upperLimit_[0] = 1.0; + for (int i = 1; i < numberOfVariables_; i++) + { + lowerLimit_[i] = -1.0; + upperLimit_[i] = 1.0; + } - if (solutionType.compare("BinaryReal") == 0) - solutionType_ = new BinaryRealSolutionType(this) ; - else if (solutionType.compare("Real") == 0) { - solutionType_ = new RealSolutionType(this) ; - } - else if (solutionType.compare("ArrayReal") == 0) - solutionType_ = new ArrayRealSolutionType(this) ; - else { - cout << "LZ09_F4::LZ09_F4: solution type " << solutionType << " invalid" << endl; - exit(-1) ; - } + if (solutionType.compare("BinaryReal") == 0) + solutionType_ = snew BinaryRealSolutionType(this) ; + else if (solutionType.compare("Real") == 0) + { + solutionType_ = snew RealSolutionType(this) ; + } + else if (solutionType.compare("ArrayReal") == 0) + solutionType_ = snew ArrayRealSolutionType(this) ; + else + { + std::cout << "LZ09_F4::LZ09_F4: solution type " << solutionType << " invalid" << std::endl; + exit(-1) ; + } - fx_ = new double[numberOfObjectives_] ; - x_ = new double[numberOfVariables_]; + fx_ = snew double[numberOfObjectives_] ; + x_ = snew double[numberOfVariables_]; } // LZ09_F4::LZ09_F4 /** * Destructor */ -LZ09_F4::~LZ09_F4 () { - delete [] lowerLimit_ ; - delete [] upperLimit_ ; - delete solutionType_ ; - delete LZ09_ ; +LZ09_F4::~LZ09_F4 () +{ + delete [] lowerLimit_ ; + delete [] upperLimit_ ; + delete solutionType_ ; + delete LZ09_ ; } -void LZ09_F4::evaluate(Solution * solution) { - XReal * vars = new XReal(solution); +void LZ09_F4::evaluate(Solution * solution) +{ + XReal * vars = snew XReal(solution); - vector * x = new vector(numberOfVariables_) ; - vector * y = new vector(numberOfObjectives_); + VectorOfDouble * x = snew VectorOfDouble(numberOfVariables_) ; + VectorOfDouble * y = snew VectorOfDouble(numberOfObjectives_); - for (int i = 0; i < numberOfVariables_; i++) { - x->at(i) = vars->getValue(i); - } // for - for (int i = 0; i < numberOfObjectives_; i++) { - y->at(i) = 0.0 ; - } // for + for (int i = 0; i < numberOfVariables_; i++) + { + x->at(i) = vars->getValue(i); + } // for + for (int i = 0; i < numberOfObjectives_; i++) + { + y->at(i) = 0.0 ; + } // for - LZ09_->objective(x, y) ; + LZ09_->objective(x, y) ; - for (int i = 0; i < numberOfObjectives_; i++) - solution->setObjective(i, y->at(i)); - - delete x; - delete y; - delete vars; + for (int i = 0; i < numberOfObjectives_; i++) + solution->setObjective(i, y->at(i)); + + delete x; + delete y; + delete vars; } diff --git a/src/problems/LZ09/LZ09_F4.h b/src/problems/LZ09/LZ09_F4.h index 6efc2fe..99b9c82 100644 --- a/src/problems/LZ09/LZ09_F4.h +++ b/src/problems/LZ09/LZ09_F4.h @@ -31,16 +31,17 @@ #include #include -class LZ09_F4 : public Problem { +class LZ09_F4 : public Problem +{ public: - LZ09_F4(string solutionType, int ptype=21, int dtype=1, int ltype=24); - void evaluate(Solution *solution); + LZ09_F4(std::string solutionType, int ptype=21, int dtype=1, int ltype=24); + void evaluate(Solution *solution); - virtual ~LZ09_F4(); + virtual ~LZ09_F4(); private: - LZ09 * LZ09_ ; - double * fx_ ; - double * x_ ; + LZ09 * LZ09_ ; + double * fx_ ; + double * x_ ; }; #endif /* __LZ09_F4_H__ */ diff --git a/src/problems/LZ09/LZ09_F5.cpp b/src/problems/LZ09/LZ09_F5.cpp index 210afab..59ae8f3 100644 --- a/src/problems/LZ09/LZ09_F5.cpp +++ b/src/problems/LZ09/LZ09_F5.cpp @@ -23,84 +23,94 @@ /** * Constructor */ -LZ09_F5::LZ09_F5(string solutionType, int ptype, int dtype, int ltype) { - numberOfVariables_ = 30; - numberOfObjectives_ = 2; - numberOfConstraints_= 0; - problemName_ = "LZ09_F5"; +LZ09_F5::LZ09_F5(std::string solutionType, int ptype, int dtype, int ltype) +{ + numberOfVariables_ = 30; + numberOfObjectives_ = 2; + numberOfConstraints_= 0; + problemName_ = "LZ09_F5"; - LZ09_ = new LZ09(numberOfVariables_, - numberOfObjectives_, - ptype, - dtype, - ltype) ; + LZ09_ = snew LZ09(numberOfVariables_, + numberOfObjectives_, + ptype, + dtype, + ltype) ; - lowerLimit_ = new double[numberOfVariables_]; - if (lowerLimit_ == NULL) { - cout << "LZ09_F5::LZ09_F5: Error reserving memory for storing the " - << "variable lower limits" << endl; - exit(-1); - } + lowerLimit_ = snew double[numberOfVariables_]; + if (lowerLimit_ == nullptr) + { + std::cout << "LZ09_F5::LZ09_F5: Error reserving memory for storing the " + << "variable lower limits" << std::endl; + exit(-1); + } - upperLimit_ = new double[numberOfVariables_]; - if (upperLimit_ == NULL) { - cout << "LZ09_F5::LZ09_F5: Error reserving memory for storing the " - << "variable lower limits" << endl; - exit(-1); - } + upperLimit_ = snew double[numberOfVariables_]; + if (upperLimit_ == nullptr) + { + std::cout << "LZ09_F5::LZ09_F5: Error reserving memory for storing the " + << "variable lower limits" << std::endl; + exit(-1); + } - lowerLimit_[0] = 0.0; - upperLimit_[0] = 1.0; - for (int i = 1; i < numberOfVariables_; i++) { - lowerLimit_[i] = -1.0; - upperLimit_[i] = 1.0; - } + lowerLimit_[0] = 0.0; + upperLimit_[0] = 1.0; + for (int i = 1; i < numberOfVariables_; i++) + { + lowerLimit_[i] = -1.0; + upperLimit_[i] = 1.0; + } - if (solutionType.compare("BinaryReal") == 0) - solutionType_ = new BinaryRealSolutionType(this) ; - else if (solutionType.compare("Real") == 0) { - solutionType_ = new RealSolutionType(this) ; - } - else if (solutionType.compare("ArrayReal") == 0) - solutionType_ = new ArrayRealSolutionType(this) ; - else { - cout << "LZ09_F5::LZ09_F5: solution type " << solutionType << " invalid" << endl; - exit(-1) ; - } + if (solutionType.compare("BinaryReal") == 0) + solutionType_ = snew BinaryRealSolutionType(this) ; + else if (solutionType.compare("Real") == 0) + { + solutionType_ = snew RealSolutionType(this) ; + } + else if (solutionType.compare("ArrayReal") == 0) + solutionType_ = snew ArrayRealSolutionType(this) ; + else + { + std::cout << "LZ09_F5::LZ09_F5: solution type " << solutionType << " invalid" << std::endl; + exit(-1) ; + } - fx_ = new double[numberOfObjectives_] ; - x_ = new double[numberOfVariables_]; + fx_ = snew double[numberOfObjectives_] ; + x_ = snew double[numberOfVariables_]; } // LZ09_F5::LZ09_F5 /** * Destructor */ -LZ09_F5::~LZ09_F5 () { - delete [] lowerLimit_ ; - delete [] upperLimit_ ; - delete solutionType_ ; - delete LZ09_ ; +LZ09_F5::~LZ09_F5 () +{ + delete [] lowerLimit_ ; + delete [] upperLimit_ ; + delete solutionType_ ; + delete LZ09_ ; } -void LZ09_F5::evaluate(Solution * solution) { - XReal * vars = new XReal(solution); +void LZ09_F5::evaluate(Solution * solution) +{ + XReal * vars = snew XReal(solution); - vector * x = new vector(numberOfVariables_) ; - vector * y = new vector(numberOfObjectives_); + VectorOfDouble * x = snew VectorOfDouble(numberOfVariables_) ; + VectorOfDouble * y = snew VectorOfDouble(numberOfObjectives_); - for (int i = 0; i < numberOfVariables_; i++) { - x->at(i) = vars->getValue(i); - } // for - for (int i = 0; i < numberOfObjectives_; i++) { - y->at(i) = 0.0 ; - } // for + for (int i = 0; i < numberOfVariables_; i++) + { + x->at(i) = vars->getValue(i); + } // for + for (int i = 0; i < numberOfObjectives_; i++) + { + y->at(i) = 0.0 ; + } // for - LZ09_->objective(x, y) ; + LZ09_->objective(x, y) ; - for (int i = 0; i < numberOfObjectives_; i++) - solution->setObjective(i, y->at(i)); - - delete x; - delete y; - delete vars; + for (int i = 0; i < numberOfObjectives_; i++) + solution->setObjective(i, y->at(i)); + + delete x; + delete y; + delete vars; } diff --git a/src/problems/LZ09/LZ09_F5.h b/src/problems/LZ09/LZ09_F5.h index f81e839..1f3a5ab 100644 --- a/src/problems/LZ09/LZ09_F5.h +++ b/src/problems/LZ09/LZ09_F5.h @@ -31,16 +31,17 @@ #include #include -class LZ09_F5 : public Problem { +class LZ09_F5 : public Problem +{ public: - LZ09_F5(string solutionType, int ptype=21, int dtype=1, int ltype=26); - void evaluate(Solution *solution); + LZ09_F5(std::string solutionType, int ptype=21, int dtype=1, int ltype=26); + void evaluate(Solution *solution); - virtual ~LZ09_F5(); + virtual ~LZ09_F5(); private: - LZ09 * LZ09_ ; - double * fx_ ; - double * x_ ; + LZ09 * LZ09_ ; + double * fx_ ; + double * x_ ; }; #endif /* __LZ09_F5_H__ */ diff --git a/src/problems/LZ09/LZ09_F6.cpp b/src/problems/LZ09/LZ09_F6.cpp index d444689..bb75ef1 100644 --- a/src/problems/LZ09/LZ09_F6.cpp +++ b/src/problems/LZ09/LZ09_F6.cpp @@ -23,84 +23,94 @@ /** * Constructor */ -LZ09_F6::LZ09_F6(string solutionType, int ptype, int dtype, int ltype) { - numberOfVariables_ = 10; - numberOfObjectives_ = 3; - numberOfConstraints_= 0; - problemName_ = "LZ09_F6"; +LZ09_F6::LZ09_F6(std::string solutionType, int ptype, int dtype, int ltype) +{ + numberOfVariables_ = 10; + numberOfObjectives_ = 3; + numberOfConstraints_= 0; + problemName_ = "LZ09_F6"; - LZ09_ = new LZ09(numberOfVariables_, - numberOfObjectives_, - ptype, - dtype, - ltype) ; + LZ09_ = snew LZ09(numberOfVariables_, + numberOfObjectives_, + ptype, + dtype, + ltype) ; - lowerLimit_ = new double[numberOfVariables_]; - if (lowerLimit_ == NULL) { - cout << "LZ09_F6::LZ09_F6: Error reserving memory for storing the " - << "variable lower limits" << endl; - exit(-1); - } + lowerLimit_ = snew double[numberOfVariables_]; + if (lowerLimit_ == nullptr) + { + std::cout << "LZ09_F6::LZ09_F6: Error reserving memory for storing the " + << "variable lower limits" << std::endl; + exit(-1); + } - upperLimit_ = new double[numberOfVariables_]; - if (upperLimit_ == NULL) { - cout << "LZ09_F6::LZ09_F6: Error reserving memory for storing the " - << "variable lower limits" << endl; - exit(-1); - } + upperLimit_ = snew double[numberOfVariables_]; + if (upperLimit_ == nullptr) + { + std::cout << "LZ09_F6::LZ09_F6: Error reserving memory for storing the " + << "variable lower limits" << std::endl; + exit(-1); + } - lowerLimit_[0] = 0.0; - upperLimit_[0] = 1.0; - for (int i = 1; i < numberOfVariables_; i++) { - lowerLimit_[i] = -1.0; - upperLimit_[i] = 1.0; - } + lowerLimit_[0] = 0.0; + upperLimit_[0] = 1.0; + for (int i = 1; i < numberOfVariables_; i++) + { + lowerLimit_[i] = -1.0; + upperLimit_[i] = 1.0; + } - if (solutionType.compare("BinaryReal") == 0) - solutionType_ = new BinaryRealSolutionType(this) ; - else if (solutionType.compare("Real") == 0) { - solutionType_ = new RealSolutionType(this) ; - } - else if (solutionType.compare("ArrayReal") == 0) - solutionType_ = new ArrayRealSolutionType(this) ; - else { - cout << "LZ09_F6::LZ09_F6: solution type " << solutionType << " invalid" << endl; - exit(-1) ; - } + if (solutionType.compare("BinaryReal") == 0) + solutionType_ = snew BinaryRealSolutionType(this) ; + else if (solutionType.compare("Real") == 0) + { + solutionType_ = snew RealSolutionType(this) ; + } + else if (solutionType.compare("ArrayReal") == 0) + solutionType_ = snew ArrayRealSolutionType(this) ; + else + { + std::cout << "LZ09_F6::LZ09_F6: solution type " << solutionType << " invalid" << std::endl; + exit(-1) ; + } - fx_ = new double[numberOfObjectives_] ; - x_ = new double[numberOfVariables_]; + fx_ = snew double[numberOfObjectives_] ; + x_ = snew double[numberOfVariables_]; } // LZ09_F6::LZ09_F6 /** * Destructor */ -LZ09_F6::~LZ09_F6 () { - delete [] lowerLimit_ ; - delete [] upperLimit_ ; - delete solutionType_ ; - delete LZ09_ ; +LZ09_F6::~LZ09_F6 () +{ + delete [] lowerLimit_ ; + delete [] upperLimit_ ; + delete solutionType_ ; + delete LZ09_ ; } -void LZ09_F6::evaluate(Solution * solution) { - XReal * vars = new XReal(solution); +void LZ09_F6::evaluate(Solution * solution) +{ + XReal * vars = snew XReal(solution); - vector * x = new vector(numberOfVariables_) ; - vector * y = new vector(numberOfObjectives_); + VectorOfDouble * x = snew VectorOfDouble(numberOfVariables_) ; + VectorOfDouble * y = snew VectorOfDouble(numberOfObjectives_); - for (int i = 0; i < numberOfVariables_; i++) { - x->at(i) = vars->getValue(i); - } // for - for (int i = 0; i < numberOfObjectives_; i++) { - y->at(i) = 0.0 ; - } // for + for (int i = 0; i < numberOfVariables_; i++) + { + x->at(i) = vars->getValue(i); + } // for + for (int i = 0; i < numberOfObjectives_; i++) + { + y->at(i) = 0.0 ; + } // for - LZ09_->objective(x, y) ; + LZ09_->objective(x, y) ; - for (int i = 0; i < numberOfObjectives_; i++) - solution->setObjective(i, y->at(i)); - - delete x; - delete y; - delete vars; + for (int i = 0; i < numberOfObjectives_; i++) + solution->setObjective(i, y->at(i)); + + delete x; + delete y; + delete vars; } diff --git a/src/problems/LZ09/LZ09_F6.h b/src/problems/LZ09/LZ09_F6.h index d63a8f6..350ac70 100644 --- a/src/problems/LZ09/LZ09_F6.h +++ b/src/problems/LZ09/LZ09_F6.h @@ -31,16 +31,17 @@ #include #include -class LZ09_F6 : public Problem { +class LZ09_F6 : public Problem +{ public: - LZ09_F6(string solutionType, int ptype=31, int dtype=1, int ltype=32); - void evaluate(Solution *solution); + LZ09_F6(std::string solutionType, int ptype=31, int dtype=1, int ltype=32); + void evaluate(Solution *solution); - virtual ~LZ09_F6(); + virtual ~LZ09_F6(); private: - LZ09 * LZ09_ ; - double * fx_ ; - double * x_ ; + LZ09 * LZ09_ ; + double * fx_ ; + double * x_ ; }; #endif /* __LZ09_F6_H__ */ diff --git a/src/problems/LZ09/LZ09_F7.cpp b/src/problems/LZ09/LZ09_F7.cpp index 139cac9..c32fb2e 100644 --- a/src/problems/LZ09/LZ09_F7.cpp +++ b/src/problems/LZ09/LZ09_F7.cpp @@ -23,84 +23,94 @@ /** * Constructor */ -LZ09_F7::LZ09_F7(string solutionType, int ptype, int dtype, int ltype) { - numberOfVariables_ = 10; - numberOfObjectives_ = 2; - numberOfConstraints_= 0; - problemName_ = "LZ09_F7"; +LZ09_F7::LZ09_F7(std::string solutionType, int ptype, int dtype, int ltype) +{ + numberOfVariables_ = 10; + numberOfObjectives_ = 2; + numberOfConstraints_= 0; + problemName_ = "LZ09_F7"; - LZ09_ = new LZ09(numberOfVariables_, - numberOfObjectives_, - ptype, - dtype, - ltype) ; + LZ09_ = snew LZ09(numberOfVariables_, + numberOfObjectives_, + ptype, + dtype, + ltype) ; - lowerLimit_ = new double[numberOfVariables_]; - if (lowerLimit_ == NULL) { - cout << "LZ09_F7::LZ09_F7: Error reserving memory for storing the " - << "variable lower limits" << endl; - exit(-1); - } + lowerLimit_ = snew double[numberOfVariables_]; + if (lowerLimit_ == nullptr) + { + std::cout << "LZ09_F7::LZ09_F7: Error reserving memory for storing the " + << "variable lower limits" << std::endl; + exit(-1); + } - upperLimit_ = new double[numberOfVariables_]; - if (upperLimit_ == NULL) { - cout << "LZ09_F7::LZ09_F7: Error reserving memory for storing the " - << "variable lower limits" << endl; - exit(-1); - } + upperLimit_ = snew double[numberOfVariables_]; + if (upperLimit_ == nullptr) + { + std::cout << "LZ09_F7::LZ09_F7: Error reserving memory for storing the " + << "variable lower limits" << std::endl; + exit(-1); + } - lowerLimit_[0] = 0.0; - upperLimit_[0] = 1.0; - for (int i = 1; i < numberOfVariables_; i++) { - lowerLimit_[i] = -1.0; - upperLimit_[i] = 1.0; - } + lowerLimit_[0] = 0.0; + upperLimit_[0] = 1.0; + for (int i = 1; i < numberOfVariables_; i++) + { + lowerLimit_[i] = -1.0; + upperLimit_[i] = 1.0; + } - if (solutionType.compare("BinaryReal") == 0) - solutionType_ = new BinaryRealSolutionType(this) ; - else if (solutionType.compare("Real") == 0) { - solutionType_ = new RealSolutionType(this) ; - } - else if (solutionType.compare("ArrayReal") == 0) - solutionType_ = new ArrayRealSolutionType(this) ; - else { - cout << "LZ09_F7::LZ09_F7: solution type " << solutionType << " invalid" << endl; - exit(-1) ; - } + if (solutionType.compare("BinaryReal") == 0) + solutionType_ = snew BinaryRealSolutionType(this) ; + else if (solutionType.compare("Real") == 0) + { + solutionType_ = snew RealSolutionType(this) ; + } + else if (solutionType.compare("ArrayReal") == 0) + solutionType_ = snew ArrayRealSolutionType(this) ; + else + { + std::cout << "LZ09_F7::LZ09_F7: solution type " << solutionType << " invalid" << std::endl; + exit(-1) ; + } - fx_ = new double[numberOfObjectives_] ; - x_ = new double[numberOfVariables_]; + fx_ = snew double[numberOfObjectives_] ; + x_ = snew double[numberOfVariables_]; } // LZ09_F7::LZ09_F7 /** * Destructor */ -LZ09_F7::~LZ09_F7 () { - delete [] lowerLimit_ ; - delete [] upperLimit_ ; - delete solutionType_ ; - delete LZ09_ ; +LZ09_F7::~LZ09_F7 () +{ + delete [] lowerLimit_ ; + delete [] upperLimit_ ; + delete solutionType_ ; + delete LZ09_ ; } -void LZ09_F7::evaluate(Solution * solution) { - XReal * vars = new XReal(solution); +void LZ09_F7::evaluate(Solution * solution) +{ + XReal * vars = snew XReal(solution); - vector * x = new vector(numberOfVariables_) ; - vector * y = new vector(numberOfObjectives_); + VectorOfDouble * x = snew VectorOfDouble(numberOfVariables_) ; + VectorOfDouble * y = snew VectorOfDouble(numberOfObjectives_); - for (int i = 0; i < numberOfVariables_; i++) { - x->at(i) = vars->getValue(i); - } // for - for (int i = 0; i < numberOfObjectives_; i++) { - y->at(i) = 0.0 ; - } // for + for (int i = 0; i < numberOfVariables_; i++) + { + x->at(i) = vars->getValue(i); + } // for + for (int i = 0; i < numberOfObjectives_; i++) + { + y->at(i) = 0.0 ; + } // for - LZ09_->objective(x, y) ; + LZ09_->objective(x, y) ; - for (int i = 0; i < numberOfObjectives_; i++) - solution->setObjective(i, y->at(i)); - - delete x; - delete y; - delete vars; + for (int i = 0; i < numberOfObjectives_; i++) + solution->setObjective(i, y->at(i)); + + delete x; + delete y; + delete vars; } diff --git a/src/problems/LZ09/LZ09_F7.h b/src/problems/LZ09/LZ09_F7.h index bbcefcf..49a7c1b 100644 --- a/src/problems/LZ09/LZ09_F7.h +++ b/src/problems/LZ09/LZ09_F7.h @@ -31,16 +31,17 @@ #include #include -class LZ09_F7 : public Problem { +class LZ09_F7 : public Problem +{ public: - LZ09_F7(string solutionType, int ptype=21, int dtype=3, int ltype=21); - void evaluate(Solution *solution); + LZ09_F7(std::string solutionType, int ptype=21, int dtype=3, int ltype=21); + void evaluate(Solution *solution); - virtual ~LZ09_F7(); + virtual ~LZ09_F7(); private: - LZ09 * LZ09_ ; - double * fx_ ; - double * x_ ; + LZ09 * LZ09_ ; + double * fx_ ; + double * x_ ; }; #endif /* __LZ09_F7_H__ */ diff --git a/src/problems/LZ09/LZ09_F8.cpp b/src/problems/LZ09/LZ09_F8.cpp index 94eff24..f1e5372 100644 --- a/src/problems/LZ09/LZ09_F8.cpp +++ b/src/problems/LZ09/LZ09_F8.cpp @@ -23,84 +23,94 @@ /** * Constructor */ -LZ09_F8::LZ09_F8(string solutionType, int ptype, int dtype, int ltype) { - numberOfVariables_ = 10; - numberOfObjectives_ = 2; - numberOfConstraints_= 0; - problemName_ = "LZ09_F8"; +LZ09_F8::LZ09_F8(std::string solutionType, int ptype, int dtype, int ltype) +{ + numberOfVariables_ = 10; + numberOfObjectives_ = 2; + numberOfConstraints_= 0; + problemName_ = "LZ09_F8"; - LZ09_ = new LZ09(numberOfVariables_, - numberOfObjectives_, - ptype, - dtype, - ltype) ; + LZ09_ = snew LZ09(numberOfVariables_, + numberOfObjectives_, + ptype, + dtype, + ltype) ; - lowerLimit_ = new double[numberOfVariables_]; - if (lowerLimit_ == NULL) { - cout << "LZ09_F8::LZ09_F8: Error reserving memory for storing the " - << "variable lower limits" << endl; - exit(-1); - } + lowerLimit_ = snew double[numberOfVariables_]; + if (lowerLimit_ == nullptr) + { + std::cout << "LZ09_F8::LZ09_F8: Error reserving memory for storing the " + << "variable lower limits" << std::endl; + exit(-1); + } - upperLimit_ = new double[numberOfVariables_]; - if (upperLimit_ == NULL) { - cout << "LZ09_F8::LZ09_F8: Error reserving memory for storing the " - << "variable lower limits" << endl; - exit(-1); - } + upperLimit_ = snew double[numberOfVariables_]; + if (upperLimit_ == nullptr) + { + std::cout << "LZ09_F8::LZ09_F8: Error reserving memory for storing the " + << "variable lower limits" << std::endl; + exit(-1); + } - lowerLimit_[0] = 0.0; - upperLimit_[0] = 1.0; - for (int i = 1; i < numberOfVariables_; i++) { - lowerLimit_[i] = -1.0; - upperLimit_[i] = 1.0; - } + lowerLimit_[0] = 0.0; + upperLimit_[0] = 1.0; + for (int i = 1; i < numberOfVariables_; i++) + { + lowerLimit_[i] = -1.0; + upperLimit_[i] = 1.0; + } - if (solutionType.compare("BinaryReal") == 0) - solutionType_ = new BinaryRealSolutionType(this) ; - else if (solutionType.compare("Real") == 0) { - solutionType_ = new RealSolutionType(this) ; - } - else if (solutionType.compare("ArrayReal") == 0) - solutionType_ = new ArrayRealSolutionType(this) ; - else { - cout << "LZ09_F8::LZ09_F8: solution type " << solutionType << " invalid" << endl; - exit(-1) ; - } + if (solutionType.compare("BinaryReal") == 0) + solutionType_ = snew BinaryRealSolutionType(this) ; + else if (solutionType.compare("Real") == 0) + { + solutionType_ = snew RealSolutionType(this) ; + } + else if (solutionType.compare("ArrayReal") == 0) + solutionType_ = snew ArrayRealSolutionType(this) ; + else + { + std::cout << "LZ09_F8::LZ09_F8: solution type " << solutionType << " invalid" << std::endl; + exit(-1) ; + } - fx_ = new double[numberOfObjectives_] ; - x_ = new double[numberOfVariables_]; + fx_ = snew double[numberOfObjectives_] ; + x_ = snew double[numberOfVariables_]; } // LZ09_F8::LZ09_F8 /** * Destructor */ -LZ09_F8::~LZ09_F8 () { - delete [] lowerLimit_ ; - delete [] upperLimit_ ; - delete solutionType_ ; - delete LZ09_ ; +LZ09_F8::~LZ09_F8 () +{ + delete [] lowerLimit_ ; + delete [] upperLimit_ ; + delete solutionType_ ; + delete LZ09_ ; } -void LZ09_F8::evaluate(Solution * solution) { - XReal * vars = new XReal(solution); +void LZ09_F8::evaluate(Solution * solution) +{ + XReal * vars = snew XReal(solution); - vector * x = new vector(numberOfVariables_) ; - vector * y = new vector(numberOfObjectives_); + VectorOfDouble * x = snew VectorOfDouble(numberOfVariables_) ; + VectorOfDouble * y = snew VectorOfDouble(numberOfObjectives_); - for (int i = 0; i < numberOfVariables_; i++) { - x->at(i) = vars->getValue(i); - } // for - for (int i = 0; i < numberOfObjectives_; i++) { - y->at(i) = 0.0 ; - } // for + for (int i = 0; i < numberOfVariables_; i++) + { + x->at(i) = vars->getValue(i); + } // for + for (int i = 0; i < numberOfObjectives_; i++) + { + y->at(i) = 0.0 ; + } // for - LZ09_->objective(x, y) ; + LZ09_->objective(x, y) ; - for (int i = 0; i < numberOfObjectives_; i++) - solution->setObjective(i, y->at(i)); - - delete x; - delete y; - delete vars; + for (int i = 0; i < numberOfObjectives_; i++) + solution->setObjective(i, y->at(i)); + + delete x; + delete y; + delete vars; } diff --git a/src/problems/LZ09/LZ09_F8.h b/src/problems/LZ09/LZ09_F8.h index 73faea8..198cd4e 100644 --- a/src/problems/LZ09/LZ09_F8.h +++ b/src/problems/LZ09/LZ09_F8.h @@ -31,16 +31,17 @@ #include #include -class LZ09_F8 : public Problem { +class LZ09_F8 : public Problem +{ public: - LZ09_F8(string solutionType, int ptype=21, int dtype=4, int ltype=21); - void evaluate(Solution *solution); + LZ09_F8(std::string solutionType, int ptype=21, int dtype=4, int ltype=21); + void evaluate(Solution *solution); - virtual ~LZ09_F8(); + virtual ~LZ09_F8(); private: - LZ09 * LZ09_ ; - double * fx_ ; - double * x_ ; + LZ09 * LZ09_ ; + double * fx_ ; + double * x_ ; }; #endif /* __LZ09_F8_H__ */ diff --git a/src/problems/LZ09/LZ09_F9.cpp b/src/problems/LZ09/LZ09_F9.cpp index eb1c4a4..f3c67cf 100644 --- a/src/problems/LZ09/LZ09_F9.cpp +++ b/src/problems/LZ09/LZ09_F9.cpp @@ -23,85 +23,95 @@ /** * Constructor */ -LZ09_F9::LZ09_F9(string solutionType, int ptype, int dtype, int ltype) { - numberOfVariables_ = 30; - numberOfObjectives_ = 2; - numberOfConstraints_= 0; - problemName_ = "LZ09_F9"; - - LZ09_ = new LZ09(numberOfVariables_, - numberOfObjectives_, - ptype, - dtype, - ltype) ; - - lowerLimit_ = new double[numberOfVariables_]; - if (lowerLimit_ == NULL) { - cout << "LZ09_F9::LZ09_F9: Error reserving memory for storing the " - << "variable lower limits" << endl; - exit(-1); - } - - upperLimit_ = new double[numberOfVariables_]; - if (upperLimit_ == NULL) { - cout << "LZ09_F9::LZ09_F9: Error reserving memory for storing the " - << "variable lower limits" << endl; - exit(-1); - } - - lowerLimit_[0] = 0.0; - upperLimit_[0] = 1.0; - for (int i = 1; i < numberOfVariables_; i++) { - lowerLimit_[i] = -1.0; - upperLimit_[i] = 1.0; - } - - if (solutionType.compare("BinaryReal") == 0) - solutionType_ = new BinaryRealSolutionType(this) ; - else if (solutionType.compare("Real") == 0) { - solutionType_ = new RealSolutionType(this) ; - } - else if (solutionType.compare("ArrayReal") == 0) - solutionType_ = new ArrayRealSolutionType(this) ; - else { - cout << "LZ09_F9::LZ09_F9: solution type " << solutionType << " invalid" << endl; - exit(-1) ; - } - - fx_ = new double[numberOfObjectives_] ; - x_ = new double[numberOfVariables_]; +LZ09_F9::LZ09_F9(std::string solutionType, int ptype, int dtype, int ltype) +{ + numberOfVariables_ = 30; + numberOfObjectives_ = 2; + numberOfConstraints_= 0; + problemName_ = "LZ09_F9"; + + LZ09_ = snew LZ09(numberOfVariables_, + numberOfObjectives_, + ptype, + dtype, + ltype) ; + + lowerLimit_ = snew double[numberOfVariables_]; + if (lowerLimit_ == nullptr) + { + std::cout << "LZ09_F9::LZ09_F9: Error reserving memory for storing the " + << "variable lower limits" << std::endl; + exit(-1); + } + + upperLimit_ = snew double[numberOfVariables_]; + if (upperLimit_ == nullptr) + { + std::cout << "LZ09_F9::LZ09_F9: Error reserving memory for storing the " + << "variable lower limits" << std::endl; + exit(-1); + } + + lowerLimit_[0] = 0.0; + upperLimit_[0] = 1.0; + for (int i = 1; i < numberOfVariables_; i++) + { + lowerLimit_[i] = -1.0; + upperLimit_[i] = 1.0; + } + + if (solutionType.compare("BinaryReal") == 0) + solutionType_ = snew BinaryRealSolutionType(this) ; + else if (solutionType.compare("Real") == 0) + { + solutionType_ = snew RealSolutionType(this) ; + } + else if (solutionType.compare("ArrayReal") == 0) + solutionType_ = snew ArrayRealSolutionType(this) ; + else + { + std::cout << "LZ09_F9::LZ09_F9: solution type " << solutionType << " invalid" << std::endl; + exit(-1) ; + } + + fx_ = snew double[numberOfObjectives_] ; + x_ = snew double[numberOfVariables_]; } // LZ09_F9::LZ09_F9 /** * Destructor */ -LZ09_F9::~LZ09_F9 () { - delete [] lowerLimit_ ; - delete [] upperLimit_ ; - delete solutionType_ ; - delete LZ09_ ; +LZ09_F9::~LZ09_F9 () +{ + delete [] lowerLimit_ ; + delete [] upperLimit_ ; + delete solutionType_ ; + delete LZ09_ ; } -void LZ09_F9::evaluate(Solution * solution) { - XReal * vars = new XReal(solution); +void LZ09_F9::evaluate(Solution * solution) +{ + XReal * vars = snew XReal(solution); + + VectorOfDouble * x = snew VectorOfDouble(numberOfVariables_) ; + VectorOfDouble * y = snew VectorOfDouble(numberOfObjectives_); + + for (int i = 0; i < numberOfVariables_; i++) + { + x->at(i) = vars->getValue(i); + } // for + for (int i = 0; i < numberOfObjectives_; i++) + { + y->at(i) = 0.0 ; + } // for - vector * x = new vector(numberOfVariables_) ; - vector * y = new vector(numberOfObjectives_); + LZ09_->objective(x, y) ; - for (int i = 0; i < numberOfVariables_; i++) { - x->at(i) = vars->getValue(i); - } // for - for (int i = 0; i < numberOfObjectives_; i++) { - y->at(i) = 0.0 ; - } // for + for (int i = 0; i < numberOfObjectives_; i++) + solution->setObjective(i, y->at(i)); - LZ09_->objective(x, y) ; + delete x; + delete y; + delete vars; - for (int i = 0; i < numberOfObjectives_; i++) - solution->setObjective(i, y->at(i)); - - delete x; - delete y; - delete vars; - } diff --git a/src/problems/LZ09/LZ09_F9.h b/src/problems/LZ09/LZ09_F9.h index 54b355f..62a9bd2 100644 --- a/src/problems/LZ09/LZ09_F9.h +++ b/src/problems/LZ09/LZ09_F9.h @@ -31,16 +31,17 @@ #include #include -class LZ09_F9 : public Problem { +class LZ09_F9 : public Problem +{ public: - LZ09_F9(string solutionType, int ptype=22, int dtype=1, int ltype=22); - void evaluate(Solution *solution); + LZ09_F9(string solutionType, int ptype=22, int dtype=1, int ltype=22); + void evaluate(Solution *solution); - virtual ~LZ09_F9(); + virtual ~LZ09_F9(); private: - LZ09 * LZ09_ ; - double * fx_ ; - double * x_ ; + LZ09 * LZ09_ ; + double * fx_ ; + double * x_ ; }; #endif /* __LZ09_F9_H__ */ diff --git a/src/problems/ProblemFactory.cpp b/src/problems/ProblemFactory.cpp index 6a0a805..842330d 100644 --- a/src/problems/ProblemFactory.cpp +++ b/src/problems/ProblemFactory.cpp @@ -26,8 +26,9 @@ * Problem factory * @param name : Name of the problem */ -Problem * ProblemFactory::getProblem(char * name) { - return getProblem(name, 0, NULL); +Problem * ProblemFactory::getProblem(char * name) +{ + return getProblem(name, 0, nullptr); } @@ -37,19 +38,26 @@ Problem * ProblemFactory::getProblem(char * name) { * @param argc : Number of arguments * @param argv : Array of arguments */ -Problem * ProblemFactory::getProblem(int argc, char ** argv) { - if (argc==2) { - return getProblem(argv[1], 0, NULL); - } else if (argc>2) { - char * argv1 = argv[1]; - for (int i=0; i2) + { + char * argv1 = argv[1]; + for (int i=0; i #include -class ProblemFactory { +class ProblemFactory +{ public: - static Problem * getProblem(char * name); - static Problem * getProblem(int argc, char ** argv); - static Problem * getProblem(char * name, int argc, char ** argv); + static Problem * getProblem(char * name); + static Problem * getProblem(int argc, char ** argv); + static Problem * getProblem(char * name, int argc, char ** argv); }; #endif // __PROBLEM_FACTORY__ diff --git a/src/problems/SIGA/BarrosF1F2.cpp b/src/problems/SIGA/BarrosF1F2.cpp new file mode 100644 index 0000000..1df1e2c --- /dev/null +++ b/src/problems/SIGA/BarrosF1F2.cpp @@ -0,0 +1,123 @@ +// BarrosF1F2.cpp +// +// Authors: +// Sérgio Vieira +// +// Copyright (c) 2011 Antonio J. Nebro, Juan J. Durillo +// +// This program is free software: you can redistribute it and/or modify +// it under the terms of the GNU Lesser General Public License as published by +// the Free Software Foundation, either version 3 of the License, or +// (at your option) any later version. +// +// This program is distributed in the hope that it will be useful, +// but WITHOUT ANY WARRANTY; without even the implied warranty of +// MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the +// GNU Lesser General Public License for more details. +// +// You should have received a copy of the GNU Lesser General Public License +// along with this program. If not, see . + +#include "BarrosF1F2.h" + +/** + * Class constructor + */ +BarrosF1F2::BarrosF1F2(std::string solutionType) +{ + numberOfVariables_ = 2; + numberOfObjectives_ = 2; + numberOfConstraints_ = 0; + problemName_ = "BarrosF1F2"; + + lowerLimit_ = snew double[numberOfVariables_]; + if (lowerLimit_ == nullptr) + { + std::cout << "BarrosF1F2::BarrosF1F2. Error reserving memory for storing the array of lower limits" << std::endl; + } // if + + upperLimit_ = snew double[numberOfVariables_]; + if (upperLimit_ == nullptr) + { + std::cout << "BarrosF1F2::BarrosF1F2. Error reserving memory for storing the array of upper limits" << std::endl; + exit(-1) ; + } // if + + for (int i = 0; i < numberOfVariables_; i++) + { + lowerLimit_[i] = -10.0; + upperLimit_[i] = 20.0; + } // for + + if (solutionType.compare("BinaryReal") == 0) + { + //std::cout << "Selected solution type: BinaryReal" << std::endl; + solutionType_ = snew BinaryRealSolutionType(this) ; + } + else if (solutionType.compare("Real") == 0) + { + solutionType_ = snew RealSolutionType(this) ; + //std::cout << "Selected solution type: Real" << std::endl; + } + else if (solutionType.compare("ArrayReal") == 0) + { + solutionType_ = snew ArrayRealSolutionType(this) ; + } + else + { + std::cout << "Error: solution type " << solutionType << " invalid" << std::endl; + exit(-1) ; + } +} // BarrosF1F2 + + +/** + * Destructor + */ +BarrosF1F2::~BarrosF1F2() +{ + delete [] lowerLimit_ ; + delete [] upperLimit_ ; + delete solutionType_ ; +} // ~BarrosF1F2 + + +/** + * Evaluates a solution + */ +void BarrosF1F2::evaluate(Solution *solution) +{ + double *fx = nullptr; + double *x = nullptr; + Variable **variables = solution->getDecisionVariables(); + + fx = snew double[numberOfObjectives_]; + if (fx == nullptr) + { + std::cout << "BarrosF1F2::evaluate: Error reserving memory for the function values array" << std::endl; + exit(-1); + } // if + + x = snew double[numberOfVariables_]; + if (x == nullptr) + { + std::cout << "BarrosF1F2::evaluate: Error reserving memory for the variable values array" << std::endl; + exit(-1); + } // if + + for (int i = 0; i < numberOfVariables_; i++) + { + x[i] = variables[i]->getValue() ; + } + fx[0] = x[0]; + double value1 = pow(x[0] - 4.0, 2.0); + double value2 = pow(x[1] - 4.0, 2.0); + double valueSqrt = sqrt(value1 + value2); + fx[1] = -20.0 * (sin(0.1 + valueSqrt) / (0.1 + valueSqrt)); + solution->setObjective(0,fx[0]); + solution->setObjective(1,fx[1]); + + delete[]fx ; + delete[]x ; +} // evaluate + diff --git a/src/problems/SIGA/BarrosF1F2.h b/src/problems/SIGA/BarrosF1F2.h new file mode 100644 index 0000000..cca92b7 --- /dev/null +++ b/src/problems/SIGA/BarrosF1F2.h @@ -0,0 +1,44 @@ +// BarrosF1F2.h +// +// Authors: +// Sérgio Vieira +// +// +// Copyright (c) 2011 Antonio J. Nebro, Juan J. Durillo +// +// This program is free software: you can redistribute it and/or modify +// it under the terms of the GNU Lesser General Public License as published by +// the Free Software Foundation, either version 3 of the License, or +// (at your option) any later version. +// +// This program is distributed in the hope that it will be useful, +// but WITHOUT ANY WARRANTY; without even the implied warranty of +// MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the +// GNU Lesser General Public License for more details. +// +// You should have received a copy of the GNU Lesser General Public License +// along with this program. If not, see . + +#ifndef __BARROS_F1_F2__ +#define __BARROS_F1_F2__ + +#include +#include +#include +#include +#include +#include + +/** + * @class Barros F1 F2 + * @brief Class representing problem Barros + **/ +class BarrosF1F2 : public Problem +{ +public: + BarrosF1F2(std::string solutionType); + ~BarrosF1F2(); + void evaluate(Solution *solution); +}; + +#endif /** __BARROS_F1_F2__ **/ diff --git a/src/problems/SIGA/BarrosF1F3.cpp b/src/problems/SIGA/BarrosF1F3.cpp new file mode 100644 index 0000000..86c87ef --- /dev/null +++ b/src/problems/SIGA/BarrosF1F3.cpp @@ -0,0 +1,66 @@ +//#include "BarrosF1_F3.h" +#include "BarrosF1F3.h" + +BarrosF1F3::BarrosF1F3(string solutionType, int numberOfVariables, int numberOfObjectives) +{ + numberOfVariables_ = numberOfVariables; + numberOfObjectives_ = numberOfObjectives; + numberOfConstraints_ = 0; + problemName_ = "BarrosF1F3"; + + lowerLimit_ = snew double[numberOfVariables_];//(double *)malloc(sizeof(double)*numberOfVariables); + if (lowerLimit_ == nullptr) + { + cout << "Impossible to reserve memory for storing the variable lower limits" << endl; + exit(-1); + } + + upperLimit_ = snew double[numberOfVariables_];//(double *)malloc(sizeof(double)*numberOfVariables); + if (upperLimit_ == nullptr) + { + cout << "Impossible to reserve memory for storing the variable lower limits" << endl; + exit(-1); + } + + for (int i = 0; i < numberOfVariables_; i++) + { + lowerLimit_[i] = 0.0; + upperLimit_[i] = 1.0; + } + + if (solutionType.compare("BinaryReal") == 0) + solutionType_ = snew BinaryRealSolutionType(this); + else if (solutionType.compare("Real") == 0) + { + solutionType_ = snew RealSolutionType(this); + //cout << "Tipo seleccionado Real" << endl; + } + else if (solutionType.compare("ArrayReal") == 0) + solutionType_ = snew ArrayRealSolutionType(this); + else + { + cout << "Error: solution type " << solutionType << " invalid" << endl; + exit(-1); + } +} + +void BarrosF1F3::evaluate(Solution * solution) +{ + XReal * vars = snew XReal(solution); + double x1 = vars->getValue(0); + double x2 = vars->getValue(1); + delete vars; + double f1 = x1; + double a = exp(-pow ( (x2 - 0.2) / 0.004, 2.0)); + double b = exp(-pow ( (x2 - 0.6) / 0.4, 2.0)); + double f3 = (2.0 - a - 0.8 * b) / x1; + solution->setObjective(0, f1); + solution->setObjective(1, f3); +} + +BarrosF1F3::~BarrosF1F3() +{ + delete[] lowerLimit_; + delete[] upperLimit_; + delete solutionType_; +} diff --git a/src/problems/SIGA/BarrosF1F3.h b/src/problems/SIGA/BarrosF1F3.h new file mode 100644 index 0000000..9dfb81f --- /dev/null +++ b/src/problems/SIGA/BarrosF1F3.h @@ -0,0 +1,23 @@ +#ifndef __BARROS_F1_F3_H__ +#define __BARROS_F1_F3_H__ + +#include +#include +#include +#include +#include +#include +#include +#include + +class BarrosF1F3 : public Problem +{ +public: + BarrosF1F3(string solutionType, int numberOfVariables = 2, int numberOfObjectives = 2); + void evaluate(Solution *solution); + + virtual ~BarrosF1F3(); + +}; + +#endif /* __BARROS_F1_F3_H__ */ diff --git a/src/problems/SIGA/BarrosF1F4.cpp b/src/problems/SIGA/BarrosF1F4.cpp new file mode 100644 index 0000000..9859d8b --- /dev/null +++ b/src/problems/SIGA/BarrosF1F4.cpp @@ -0,0 +1,70 @@ +#include "BarrosF1F4.h" + +BarrosF1F4::BarrosF1F4(string solutionType, int numberOfVariables, int numberOfObjectives) +{ + numberOfVariables_ = numberOfVariables; + numberOfObjectives_ = numberOfObjectives; + numberOfConstraints_ = 0; + problemName_ = "BarrosF1_F3"; + + lowerLimit_ = snew double[numberOfVariables_];//(double *)malloc(sizeof(double)*numberOfVariables); + if (lowerLimit_ == nullptr) + { + cout << "Impossible to reserve memory for storing the variable lower limits" << endl; + exit(-1); + } + + upperLimit_ = snew double[numberOfVariables_];//(double *)malloc(sizeof(double)*numberOfVariables); + if (upperLimit_ == nullptr) + { + cout << "Impossible to reserve memory for storing the variable lower limits" << endl; + exit(-1); + } + + for (int i = 0; i < numberOfVariables_; i++) + { + lowerLimit_[i] = 0.0; + upperLimit_[i] = 1.0; + } + + if (solutionType.compare("BinaryReal") == 0) + solutionType_ = snew BinaryRealSolutionType(this); + else if (solutionType.compare("Real") == 0) + { + solutionType_ = snew RealSolutionType(this); + //cout << "Tipo seleccionado Real" << endl; + } + else if (solutionType.compare("ArrayReal") == 0) + solutionType_ = snew ArrayRealSolutionType(this); + else + { + cout << "Error: solution type " << solutionType << " invalid" << endl; + exit(-1); + } +} + +void BarrosF1F4::evaluate(Solution * solution) +{ + XReal * vars = snew XReal(solution); + double x1 = vars->getValue(0); + double x2 = vars->getValue(1); + delete vars; + double f1 = x1; + double gmin = 1.0; + double gmax = 2.0; + double xmin = 0.0; + double xmax = 1.0; + double num = x2 - xmin; + double den = xmax - xmin; + double g = gmin + (gmax - gmin) * pow(num / den, 0.25); + double f4 = 1 - pow(x1 / g, 2); + solution->setObjective(0, f1); + solution->setObjective(1, f4); +} + +BarrosF1F4::~BarrosF1F4() +{ + delete[] lowerLimit_; + delete[] upperLimit_; + delete solutionType_; +} diff --git a/src/problems/SIGA/BarrosF1F4.h b/src/problems/SIGA/BarrosF1F4.h new file mode 100644 index 0000000..4b9a0da --- /dev/null +++ b/src/problems/SIGA/BarrosF1F4.h @@ -0,0 +1,21 @@ +#ifndef __BARROS_F1_F4_H__ +#define __BARROS_F1_F4_H__ + +#include +#include +#include +#include +#include +#include +#include +#include + +class BarrosF1F4 : public Problem +{ +public: + BarrosF1F4(string solutionType, int numberOfVariables = 2, int numberOfObjectives = 2); + void evaluate(Solution *solution); + virtual ~BarrosF1F4(); +}; + +#endif /* __BARROS_F1_F4_H__ */ diff --git a/src/problems/SIGA/BarrosF1F5.cpp b/src/problems/SIGA/BarrosF1F5.cpp new file mode 100644 index 0000000..9a81b1a --- /dev/null +++ b/src/problems/SIGA/BarrosF1F5.cpp @@ -0,0 +1,109 @@ +// BarrosF1F5.cpp +// +// Authors: +// Sérgio Vieira +// +// Copyright (c) 2011 Antonio J. Nebro, Juan J. Durillo +// +// This program is free software: you can redistribute it and/or modify +// it under the terms of the GNU Lesser General Public License as published by +// the Free Software Foundation, either version 3 of the License, or +// (at your option) any later version. +// +// This program is distributed in the hope that it will be useful, +// but WITHOUT ANY WARRANTY; without even the implied warranty of +// MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the +// GNU Lesser General Public License for more details. +// +// You should have received a copy of the GNU Lesser General Public License +// along with this program. If not, see . + +#include "BarrosF1F5.h" + +/** + * Class constructor + */ +BarrosF1F5::BarrosF1F5(std::string solutionType) +{ + numberOfVariables_ = 2; + numberOfObjectives_ = 2; + numberOfConstraints_ = 0; + problemName_ = "BarrosF1F5"; + + lowerLimit_ = snew double[numberOfVariables_]; + if (lowerLimit_ == nullptr) + { + std::cout << "BarrosF1F5::BarrosF1F5. Error reserving memory for storing the array of lower limits" << std::endl; + } // if + + upperLimit_ = snew double[numberOfVariables_]; + if (upperLimit_ == nullptr) + { + std::cout << "BarrosF1F5::BarrosF1F5. Error reserving memory for storing the array of upper limits" << std::endl; + exit(-1) ; + } // if + + for (int i = 0; i < numberOfVariables_; i++) + { + lowerLimit_[i] = 0.0; + upperLimit_[i] = 1.0; + } // for + + if (solutionType.compare("BinaryReal") == 0) + { + //std::cout << "Selected solution type: BinaryReal" << std::endl; + solutionType_ = snew BinaryRealSolutionType(this) ; + } + else if (solutionType.compare("Real") == 0) + { + solutionType_ = snew RealSolutionType(this) ; + //std::cout << "Selected solution type: Real" << std::endl; + } + else if (solutionType.compare("ArrayReal") == 0) + { + solutionType_ = snew ArrayRealSolutionType(this) ; + } + else + { + std::cout << "Error: solution type " << solutionType << " invalid" << std::endl; + exit(-1) ; + } +} // BarrosF1F5 + + +/** + * Destructor + */ +BarrosF1F5::~BarrosF1F5() +{ + delete [] lowerLimit_ ; + delete [] upperLimit_ ; + delete solutionType_ ; +} // ~BarrosF1F5 + + +/** + * Evaluates a solution + */ +void BarrosF1F5::evaluate(Solution *solution) +{ + VectorOfDouble fx(numberOfObjectives_); + VectorOfDouble x(numberOfVariables_); + Variable **variables = solution->getDecisionVariables(); + for (int i = 0; i < numberOfVariables_; i++) + { + x[i] = variables[i]->getValue() ; + } + fx[0] = x[0]; + double alpha = 2.0; + double q = 4.0; + double value1 = 1.0 + 10.0 * x[1]; + double value2 = x[0] / value1; + double value3 = 1.0 - pow(value2, alpha); + double value4 = -(value2 * sin(2.0 * PI * q * x[0])); + double value5 = value3 - value4; + fx[1] = value1 * value5; + solution->setObjective(0, fx[0]); + solution->setObjective(1, fx[1]); +} // evaluate + diff --git a/src/problems/SIGA/BarrosF1F5.h b/src/problems/SIGA/BarrosF1F5.h new file mode 100644 index 0000000..23d9b80 --- /dev/null +++ b/src/problems/SIGA/BarrosF1F5.h @@ -0,0 +1,46 @@ +// BarrosF1F2.h +// +// Authors: +// Sérgio Vieira +// +// +// Copyright (c) 2011 Antonio J. Nebro, Juan J. Durillo +// +// This program is free software: you can redistribute it and/or modify +// it under the terms of the GNU Lesser General Public License as published by +// the Free Software Foundation, either version 3 of the License, or +// (at your option) any later version. +// +// This program is distributed in the hope that it will be useful, +// but WITHOUT ANY WARRANTY; without even the implied warranty of +// MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the +// GNU Lesser General Public License for more details. +// +// You should have received a copy of the GNU Lesser General Public License +// along with this program. If not, see . + +#ifndef __BARROS_F1_F5__ +#define __BARROS_F1_F5__ + +#include +#include +#include +#include +#include +#include + +/** + * @class Barros F1 F5 + * @brief Class representing problem Barros + **/ +class BarrosF1F5 : public Problem +{ +protected: + const double PI = 3.141592653589793; +public: + BarrosF1F5(std::string solutionType); + ~BarrosF1F5(); + void evaluate(Solution *solution); +}; + +#endif /** __BARROS_F1_F2__ **/ diff --git a/src/problems/SIGA/BarrosF5F3.cpp b/src/problems/SIGA/BarrosF5F3.cpp new file mode 100644 index 0000000..e649093 --- /dev/null +++ b/src/problems/SIGA/BarrosF5F3.cpp @@ -0,0 +1,112 @@ +// BarrosF5F3.cpp +// +// Authors: +// Sérgio Vieira +// +// Copyright (c) 2011 Antonio J. Nebro, Juan J. Durillo +// +// This program is free software: you can redistribute it and/or modify +// it under the terms of the GNU Lesser General Public License as published by +// the Free Software Foundation, either version 3 of the License, or +// (at your option) any later version. +// +// This program is distributed in the hope that it will be useful, +// but WITHOUT ANY WARRANTY; without even the implied warranty of +// MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the +// GNU Lesser General Public License for more details. +// +// You should have received a copy of the GNU Lesser General Public License +// along with this program. If not, see . + +#include "BarrosF5F3.h" + +/** + * Class constructor + */ +BarrosF5F3::BarrosF5F3(std::string solutionType) +{ + numberOfVariables_ = 2; + numberOfObjectives_ = 2; + numberOfConstraints_ = 0; + problemName_ = "BarrosF5F3"; + + lowerLimit_ = snew double[numberOfVariables_]; + if (lowerLimit_ == nullptr) + { + std::cout << "BarrosF5F3::BarrosF5F3. Error reserving memory for storing the array of lower limits" << std::endl; + } // if + + upperLimit_ = snew double[numberOfVariables_]; + if (upperLimit_ == nullptr) + { + std::cout << "BarrosF5F3::BarrosF5F3. Error reserving memory for storing the array of upper limits" << std::endl; + exit(-1) ; + } // if + + for (int i = 0; i < numberOfVariables_; i++) + { + lowerLimit_[i] = 0.0; + upperLimit_[i] = 1.0; + } // for + + if (solutionType.compare("BinaryReal") == 0) + { + //std::cout << "Selected solution type: BinaryReal" << std::endl; + solutionType_ = snew BinaryRealSolutionType(this) ; + } + else if (solutionType.compare("Real") == 0) + { + solutionType_ = snew RealSolutionType(this) ; + //std::cout << "Selected solution type: Real" << std::endl; + } + else if (solutionType.compare("ArrayReal") == 0) + { + solutionType_ = snew ArrayRealSolutionType(this) ; + } + else + { + std::cout << "Error: solution type " << solutionType << " invalid" << std::endl; + exit(-1) ; + } +} // BarrosF5F3 + + +/** + * Destructor + */ +BarrosF5F3::~BarrosF5F3() +{ + delete [] lowerLimit_ ; + delete [] upperLimit_ ; + delete solutionType_ ; +} // ~BarrosF5F3 + + +/** + * Evaluates a solution + */ +void BarrosF5F3::evaluate(Solution *solution) +{ + VectorOfDouble fx(numberOfObjectives_); + VectorOfDouble x(numberOfVariables_); + Variable **variables = solution->getDecisionVariables(); + for (int i = 0; i < numberOfVariables_; i++) + { + x[i] = variables[i]->getValue(); + } + double alpha = 2.0; + double q = 4.0; + double value1 = 1.0 + 10.0 * x[1]; + double value2 = x[0] / value1; + double value3 = 1.0 - pow(value2, alpha); + double value4 = -(value2 * sin(2.0 * PI * q * x[0])); + double value5 = value3 - value4; + fx[0] = value1 * value5; + double a = exp(-pow((x[1] - 0.2) / 0.004, 2.0)); + double b = exp(-pow((x[1] - 0.6) / 0.4, 2.0)); + fx[1] = (2.0 - a - 0.8 * b) / x[0]; + solution->setObjective(0, fx[0]); + solution->setObjective(1, fx[1]); + +} // evaluate + diff --git a/src/problems/SIGA/BarrosF5F3.h b/src/problems/SIGA/BarrosF5F3.h new file mode 100644 index 0000000..d1c86ce --- /dev/null +++ b/src/problems/SIGA/BarrosF5F3.h @@ -0,0 +1,46 @@ +// BarrosF1F2.h +// +// Authors: +// Sérgio Vieira +// +// +// Copyright (c) 2011 Antonio J. Nebro, Juan J. Durillo +// +// This program is free software: you can redistribute it and/or modify +// it under the terms of the GNU Lesser General Public License as published by +// the Free Software Foundation, either version 3 of the License, or +// (at your option) any later version. +// +// This program is distributed in the hope that it will be useful, +// but WITHOUT ANY WARRANTY; without even the implied warranty of +// MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the +// GNU Lesser General Public License for more details. +// +// You should have received a copy of the GNU Lesser General Public License +// along with this program. If not, see . + +#ifndef __BARROS_F5_F3__ +#define __BARROS_F5_F3__ + +#include +#include +#include +#include +#include +#include + +/** + * @class Barros F5 F3 + * @brief Class representing problem Barros + **/ +class BarrosF5F3 : public Problem +{ +protected: + const double PI = 3.141592653589793; +public: + BarrosF5F3(std::string solutionType); + ~BarrosF5F3(); + void evaluate(Solution *solution); +}; + +#endif /** __BARROS_F5_F3__ **/ diff --git a/src/problems/SIGA/CMakeLists.txt b/src/problems/SIGA/CMakeLists.txt new file mode 100644 index 0000000..294ec59 --- /dev/null +++ b/src/problems/SIGA/CMakeLists.txt @@ -0,0 +1,3 @@ +file(GLOB SOURCES "*.cpp" "*.h") +ListToString(SOURCES ";" ${SOURCES}) +LIST_APPEND("${SOURCES}") \ No newline at end of file diff --git a/src/problems/SIGA/SIGARuleMetal.cpp b/src/problems/SIGA/SIGARuleMetal.cpp new file mode 100644 index 0000000..d129704 --- /dev/null +++ b/src/problems/SIGA/SIGARuleMetal.cpp @@ -0,0 +1,57 @@ +#include "SIGARuleMetal.h" + +SIGARuleMetal::SIGARuleMetal(std::function callback, string solutionType, int numberOfVariables, int numberOfObjectives) +{ + numberOfVariables_ = numberOfVariables; + numberOfObjectives_ = numberOfObjectives; + numberOfConstraints_ = 0; + callback_ = callback; + problemName_ = "SIGARule"; + + lowerLimit_ = snew double[numberOfVariables_];//(double *)malloc(sizeof(double)*numberOfVariables); + if (lowerLimit_ == nullptr) + { + cout << "Impossible to reserve memory for storing the variable lower limits" << endl; + exit(-1); + } + + upperLimit_ = snew double[numberOfVariables_];//(double *)malloc(sizeof(double)*numberOfVariables); + if (upperLimit_ == nullptr) + { + cout << "Impossible to reserve memory for storing the variable lower limits" << endl; + exit(-1); + } + + for (int i = 0; i < numberOfVariables_; i++) + { + lowerLimit_[i] = 0.0; + upperLimit_[i] = 1.0; + } + + if (solutionType.compare("BinaryReal") == 0) + solutionType_ = snew BinaryRealSolutionType(this); + else if (solutionType.compare("Real") == 0) + { + solutionType_ = snew RealSolutionType(this); + //cout << "Tipo seleccionado Real" << endl; + } + else if (solutionType.compare("ArrayReal") == 0) + solutionType_ = snew ArrayRealSolutionType(this); + else + { + cout << "Error: solution type " << solutionType << " invalid" << endl; + exit(-1); + } +} + +void SIGARuleMetal::evaluate(Solution * solution) +{ + callback_(solution); +} + +SIGARuleMetal::~SIGARuleMetal() +{ + delete[] lowerLimit_; + delete[] upperLimit_; + delete solutionType_; +} diff --git a/src/problems/SIGA/SIGARuleMetal.h b/src/problems/SIGA/SIGARuleMetal.h new file mode 100644 index 0000000..c20ca2c --- /dev/null +++ b/src/problems/SIGA/SIGARuleMetal.h @@ -0,0 +1,24 @@ +#ifndef __SIGA_RULE_METAL_H__ +#define __SIGA_RULE_METAL_H__ + +#include +#include +#include +#include +#include +#include +#include +#include + +class SIGARuleMetal : public Problem +{ +public: + SIGARuleMetal(std::function callback, string solutionType, int numberOfVariables, int numberOfObjectives); + void evaluate(Solution *solution); + + virtual ~SIGARuleMetal(); +private: + std::function callback_; +}; + +#endif /* __DTLZ1_H__ */ diff --git a/src/problems/SIGA/graficos/f1f3.svg b/src/problems/SIGA/graficos/f1f3.svg new file mode 100644 index 0000000..dd878f3 --- /dev/null +++ b/src/problems/SIGA/graficos/f1f3.svg @@ -0,0 +1,197 @@ + + + + +Gnuplot +Produced by GNUPLOT 4.6 patchlevel 3 + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + 0 + + + + + + + 2 + + + + + + + 4 + + + + + + + 6 + + + + + + + 8 + + + + + + + 10 + + + + + + + 12 + + + + + + + 14 + + + + + + + 0 + + + + + + + 0.2 + + + + + + + 0.4 + + + + + + + 0.6 + + + + + + + 0.8 + + + + + + + 1 + + + Function 3 + + + Function 1 + + + OMOPSO - It=100 PI=0.5 SIZE=100 ASIZE=50 + + + gnuplot_plot_1 + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + diff --git a/src/problems/SIGA/graficos/f1f4.svg b/src/problems/SIGA/graficos/f1f4.svg new file mode 100644 index 0000000..856f997 --- /dev/null +++ b/src/problems/SIGA/graficos/f1f4.svg @@ -0,0 +1,195 @@ + + + + +Gnuplot +Produced by GNUPLOT 4.6 patchlevel 3 + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + 0 + + + + + + + 0.2 + + + + + + + 0.4 + + + + + + + 0.6 + + + + + + + 0.8 + + + + + + + 1 + + + + + + + 1.2 + + + + + + + 0 + + + + + + + 0.2 + + + + + + + 0.4 + + + + + + + 0.6 + + + + + + + 0.8 + + + + + + + 1 + + + Function 4 + + + Function 1 + + + OMOPSO - It=100 PI=0.5 SIZE=100 ASIZE=50 + + + gnuplot_plot_1 + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + diff --git a/src/problems/SIGA/graficos/f1f5.svg b/src/problems/SIGA/graficos/f1f5.svg new file mode 100644 index 0000000..777a745 --- /dev/null +++ b/src/problems/SIGA/graficos/f1f5.svg @@ -0,0 +1,208 @@ + + + + +Gnuplot +Produced by GNUPLOT 4.6 patchlevel 3 + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + -0.6 + + + + + + + -0.4 + + + + + + + -0.2 + + + + + + + 0 + + + + + + + 0.2 + + + + + + + 0.4 + + + + + + + 0.6 + + + + + + + 0.8 + + + + + + + 1 + + + + + + + 1.2 + + + + + + + 0 + + + + + + + 0.2 + + + + + + + 0.4 + + + + + + + 0.6 + + + + + + + 0.8 + + + + + + + 1 + + + Function 5 + + + Function 1 + + + OMOPSO - It=100 PI=0.5 SIZE=100 ASIZE=50 + + + gnuplot_plot_1 + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + diff --git a/src/problems/SIGA/graficos/f5f3.svg b/src/problems/SIGA/graficos/f5f3.svg new file mode 100644 index 0000000..155260f --- /dev/null +++ b/src/problems/SIGA/graficos/f5f3.svg @@ -0,0 +1,203 @@ + + + + +Gnuplot +Produced by GNUPLOT 4.6 patchlevel 3 + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + -2 + + + + + + + -1 + + + + + + + 0 + + + + + + + 1 + + + + + + + 2 + + + + + + + 3 + + + + + + + 4 + + + + + + + -2 + + + + + + + -1 + + + + + + + 0 + + + + + + + 1 + + + + + + + 2 + + + + + + + 3 + + + + + + + 4 + + + Function 3 + + + Function 5 + + + OMOPSO - It=100 PI=0.5 SIZE=100 ASIZE=50 + + + gnuplot_plot_1 + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + diff --git a/src/problems/SIGA/graficos/genPlot.gnu b/src/problems/SIGA/graficos/genPlot.gnu new file mode 100644 index 0000000..cf5d0c4 --- /dev/null +++ b/src/problems/SIGA/graficos/genPlot.gnu @@ -0,0 +1,12 @@ +# Scale font and line width (dpi) by changing the size! It will always display stretched. +set terminal svg size 400,300 enhanced fname 'arial' fsize 10 butt solid +set output 'out.svg' + +# Key means label... +set xlabel 'Function 1' +set ylabel 'Function 3' +set xrange[0:1] +set yrange[0:15] +set grid +set title 'OMOPSO - It=100 PI=0.5 SIZE=100 ASIZE=50' +plot "data.txt" notitle \ No newline at end of file diff --git a/src/problems/SIGA/graficos/omopso_no_siga.svg b/src/problems/SIGA/graficos/omopso_no_siga.svg new file mode 100644 index 0000000..1b9df20 --- /dev/null +++ b/src/problems/SIGA/graficos/omopso_no_siga.svg @@ -0,0 +1,127 @@ + + + + +Gnuplot +Produced by GNUPLOT 4.6 patchlevel 3 + + + + + + + + + + + + + + + + + + + + + + + + + + 5e+09 + + + 5.2e+09 + + + 5.4e+09 + + + 5.6e+09 + + + 5.8e+09 + + + 6e+09 + + + 2.4e+08 + + + 2.5e+08 + + + 2.6e+08 + + + 2.7e+08 + + + 2.8e+08 + + + 2.9e+08 + + + 3e+08 + + + 3.1e+08 + + + Evaporação (m³) + + + Custo (R$) + + + OMOPSO - It=100 PI=0.5 SIZE=100 ASIZE=50 + + + gnuplot_plot_1 + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + diff --git a/src/problems/SIGA/graficos/omopso_no_siga_scala.svg b/src/problems/SIGA/graficos/omopso_no_siga_scala.svg new file mode 100644 index 0000000..f44a534 --- /dev/null +++ b/src/problems/SIGA/graficos/omopso_no_siga_scala.svg @@ -0,0 +1,127 @@ + + + + +Gnuplot +Produced by GNUPLOT 4.6 patchlevel 3 + + + + + + + + + + + + + + + + + + + + + + + + + + 5.00 + + + 5.20 + + + 5.40 + + + 5.60 + + + 5.80 + + + 6.00 + + + 2.20 + + + 2.40 + + + 2.60 + + + 2.80 + + + 3.00 + + + Evaporação (m³) + + + Custo (R$) + + + OMOPSO - It=100 PI=0.5 SIZE=100 ASIZE=50 + + + gnuplot_plot_1 + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + diff --git a/src/problems/Schaffer.cpp b/src/problems/Schaffer.cpp index 7d19652..3e29797 100644 --- a/src/problems/Schaffer.cpp +++ b/src/problems/Schaffer.cpp @@ -26,27 +26,31 @@ * Creates a new instance of the Schaffer problem. * @param solutionType The solution type must "Real", "BinaryReal, and "ArrayReal". */ -Schaffer::Schaffer(string solutionType) { - numberOfVariables_ = 1; - numberOfObjectives_ = 2; - numberOfConstraints_ = 0; - - lowerLimit_ = new double[numberOfVariables_]; - if (lowerLimit_ == NULL) { - cout << "Schaffer::Schaffer. Error reserving memory for storing the array of lower limits" << endl; - exit(-1) ; - } - - upperLimit_ = new double[numberOfVariables_]; - if (upperLimit_ == NULL) { - cout << "Schaffer::Schaffer. Error reserving memory for storing the array of upper limits" << endl; - exit(-1) ; - } - - int i ; - for (i = 0; i < numberOfVariables_; i++) { - lowerLimit_[i] = -10000.0; - upperLimit_[i] = 10000.0; +Schaffer::Schaffer(std::string solutionType) +{ + numberOfVariables_ = 1; + numberOfObjectives_ = 2; + numberOfConstraints_ = 0; + + lowerLimit_ = snew double[numberOfVariables_]; + if (lowerLimit_ == nullptr) + { + std::cout << "Schaffer::Schaffer. Error reserving memory for storing the array of lower limits" << std::endl; + exit(-1) ; + } + + upperLimit_ = snew double[numberOfVariables_]; + if (upperLimit_ == nullptr) + { + std::cout << "Schaffer::Schaffer. Error reserving memory for storing the array of upper limits" << std::endl; + exit(-1) ; + } + + int i ; + for (i = 0; i < numberOfVariables_; i++) + { + lowerLimit_[i] = -10000.0; + upperLimit_[i] = 10000.0; } // TO-DO: Solution type initialization @@ -57,10 +61,11 @@ Schaffer::Schaffer(string solutionType) { /** * Destructor */ -Schaffer::~Schaffer() { - delete [] lowerLimit_ ; - delete [] upperLimit_ ; - delete solutionType_ ; +Schaffer::~Schaffer() +{ + delete [] lowerLimit_ ; + delete [] upperLimit_ ; + delete solutionType_ ; } // ~Schaffer @@ -68,24 +73,26 @@ Schaffer::~Schaffer() { * Evaluates a solution * @param solution The solution to evaluate */ -void Schaffer::evaluate(Solution *solution) { +void Schaffer::evaluate(Solution *solution) +{ - double *fx; - Variable **variables = solution->getDecisionVariables(); + double *fx; + Variable **variables = solution->getDecisionVariables(); - fx = new double[numberOfObjectives_]; - if (fx == NULL) { - cout << "Schaffer::evaluate: Error reserving memory while evaluating the problem" << endl; + fx = snew double[numberOfObjectives_]; + if (fx == nullptr) + { + std::cout << "Schaffer::evaluate: Error reserving memory while evaluating the problem" << std::endl; exit(-1); - } + } - fx[0] = variables[0]->getValue() * variables[0]->getValue() ; - fx[1] = (variables[0]->getValue() - 2.0) * (variables[0]->getValue() - 2.0); + fx[0] = variables[0]->getValue() * variables[0]->getValue() ; + fx[1] = (variables[0]->getValue() - 2.0) * (variables[0]->getValue() - 2.0); - solution->setObjective(0,fx[0]); - solution->setObjective(1,fx[1]); + solution->setObjective(0,fx[0]); + solution->setObjective(1,fx[1]); - delete [] fx; + delete [] fx; } // evaluate diff --git a/src/problems/Schaffer.h b/src/problems/Schaffer.h index 95ae4e9..9f7a24f 100644 --- a/src/problems/Schaffer.h +++ b/src/problems/Schaffer.h @@ -31,12 +31,13 @@ * @class Schaffer * @brief Class representing problem Schaffer **/ -class Schaffer : public Problem { +class Schaffer : public Problem +{ public: - Schaffer(string solutionType); - ~Schaffer(); - void evaluate(Solution *solution); + Schaffer(std::string solutionType); + ~Schaffer(); + void evaluate(Solution *solution); }; #endif diff --git a/src/problems/Srinivas.cpp b/src/problems/Srinivas.cpp index 03648a6..0f4ddd9 100644 --- a/src/problems/Srinivas.cpp +++ b/src/problems/Srinivas.cpp @@ -3,7 +3,7 @@ // Authors: // Esteban López-Camacho // Antonio J. Nebro -// +// // Copyright (c) 2011 Antonio J. Nebro, Juan J. Durillo // // This program is free software: you can redistribute it and/or modify @@ -15,7 +15,7 @@ // but WITHOUT ANY WARRANTY; without even the implied warranty of // MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the // GNU Lesser General Public License for more details. -// +// // You should have received a copy of the GNU Lesser General Public License // along with this program. If not, see . @@ -26,47 +26,57 @@ * Creates a new instance of the Srinivas problem. * @param solutionType The solution type must "Real" or "BinaryReal */ -Srinivas::Srinivas(string solutionType) { - numberOfVariables_ = 2; - numberOfObjectives_ = 2; - numberOfConstraints_ = 2; - problemName_ = "Srinivas"; - - lowerLimit_ = new double[numberOfVariables_]; - if (lowerLimit_ == NULL) { - cout << "Srinivas::Srinivas. Error reserving memory for storing the array of lower limits" << endl; - exit(-1) ; - } - - upperLimit_ = new double[numberOfVariables_]; - if (upperLimit_ == NULL) { - cout << "Srinivas::Srinivas. Error reserving memory for storing the array of upper limits" << endl; - exit(-1) ; - } - - for (int var = 0; var < numberOfVariables_; var++){ - lowerLimit_[var] = -20.0; - upperLimit_[var] = 20.0; - } // for - - if (solutionType.compare("BinaryReal")==0) { - solutionType_ = new BinaryRealSolutionType(this); - } else if (solutionType.compare("Real")==0) { - solutionType_ = new RealSolutionType(this); - } else { - cout << "Error: solution type " << solutionType << " invalid" << endl; - exit(-1); - } +Srinivas::Srinivas(std::string solutionType) +{ + numberOfVariables_ = 2; + numberOfObjectives_ = 2; + numberOfConstraints_ = 2; + problemName_ = "Srinivas"; + + lowerLimit_ = snew double[numberOfVariables_]; + if (lowerLimit_ == nullptr) + { + std::cout << "Srinivas::Srinivas. Error reserving memory for storing the array of lower limits" << std::endl; + exit(-1) ; + } + + upperLimit_ = snew double[numberOfVariables_]; + if (upperLimit_ == nullptr) + { + std::cout << "Srinivas::Srinivas. Error reserving memory for storing the array of upper limits" << std::endl; + exit(-1) ; + } + + for (int var = 0; var < numberOfVariables_; var++) + { + lowerLimit_[var] = -20.0; + upperLimit_[var] = 20.0; + } // for + + if (solutionType.compare("BinaryReal")==0) + { + solutionType_ = new BinaryRealSolutionType(this); + } + else if (solutionType.compare("Real")==0) + { + solutionType_ = new RealSolutionType(this); + } + else + { + std::cout << "Error: solution type " << solutionType << " invalid" << std::endl; + exit(-1); + } } // Srinivas /** * Destructor */ -Srinivas::~Srinivas() { - delete [] lowerLimit_ ; - delete [] upperLimit_ ; - delete solutionType_ ; +Srinivas::~Srinivas() +{ + delete [] lowerLimit_ ; + delete [] upperLimit_ ; + delete solutionType_ ; } // ~Srinivas @@ -74,61 +84,67 @@ Srinivas::~Srinivas() { * Evaluates a solution * @param solution The solution to evaluate */ -void Srinivas::evaluate(Solution *solution) { - - Variable **variables = solution->getDecisionVariables(); - - double * fx = new double[numberOfObjectives_]; - if (fx == NULL) { - cout << "Srinivas::evaluate: Error reserving memory while evaluating the problem" << endl; +void Srinivas::evaluate(Solution *solution) +{ + + Variable **variables = solution->getDecisionVariables(); + + double * fx = snew double[numberOfObjectives_]; + if (fx == nullptr) + { + std::cout << "Srinivas::evaluate: Error reserving memory while evaluating the problem" << std::endl; exit(-1); - } - - double * x = new double[numberOfVariables_]; - if (x == NULL) { - cout << "Srinivas::evaluate: Error reserving memory for the variable values array" << endl; - exit(-1); - } // if - - double x1 = variables[0]->getValue(); - double x2 = variables[1]->getValue(); - - fx[0] = 2.0 + (x1-2.0)*(x1-2.0) + (x2-1.0)*(x2-1.0); - fx[1] = 9.0 * x1 - (x2-1.0)*(x2-1.0); - - solution->setObjective(0,fx[0]); - solution->setObjective(1,fx[1]); - - delete[]fx; - delete[]x; - + } + + double * x = snew double[numberOfVariables_]; + if (x == nullptr) + { + std::cout << "Srinivas::evaluate: Error reserving memory for the variable values array" << std::endl; + exit(-1); + } // if + + double x1 = variables[0]->getValue(); + double x2 = variables[1]->getValue(); + + fx[0] = 2.0 + (x1-2.0)*(x1-2.0) + (x2-1.0)*(x2-1.0); + fx[1] = 9.0 * x1 - (x2-1.0)*(x2-1.0); + + solution->setObjective(0,fx[0]); + solution->setObjective(1,fx[1]); + + delete[]fx; + delete[]x; + } // evaluate /** * Evaluates the constraint overhead of a solution * @param solution The solution */ -void Srinivas::evaluateConstraints(Solution *solution) { - - double * constraint = new double[this->getNumberOfConstraints()]; - - double x1 = solution->getDecisionVariables()[0]->getValue(); - double x2 = solution->getDecisionVariables()[1]->getValue(); - - constraint[0] = 1.0 - (x1*x1 + x2*x2)/225.0; - constraint[1] = (3.0*x2 - x1)/10.0 - 1.0; - - int number = 0; - double total = 0.0; - for (int i = 0; i < this->getNumberOfConstraints(); i++) { - if (constraint[i]<0.0){ - number++; - total+=constraint[i]; +void Srinivas::evaluateConstraints(Solution *solution) +{ + + double * constraint = snew double[this->getNumberOfConstraints()]; + + double x1 = solution->getDecisionVariables()[0]->getValue(); + double x2 = solution->getDecisionVariables()[1]->getValue(); + + constraint[0] = 1.0 - (x1*x1 + x2*x2)/225.0; + constraint[1] = (3.0*x2 - x1)/10.0 - 1.0; + + int number = 0; + double total = 0.0; + for (int i = 0; i < this->getNumberOfConstraints(); i++) + { + if (constraint[i]<0.0) + { + number++; + total+=constraint[i]; + } } - } - - solution->setOverallConstraintViolation(total); - solution->setNumberOfViolatedConstraints(number); - + + solution->setOverallConstraintViolation(total); + solution->setNumberOfViolatedConstraints(number); + delete [] constraint; } // evaluateConstraints diff --git a/src/problems/Srinivas.h b/src/problems/Srinivas.h index e06a999..4288b10 100644 --- a/src/problems/Srinivas.h +++ b/src/problems/Srinivas.h @@ -3,7 +3,7 @@ // Authors: // Esteban López-Camacho // Antonio J. Nebro -// +// // Copyright (c) 2011 Antonio J. Nebro, Juan J. Durillo // // This program is free software: you can redistribute it and/or modify @@ -15,7 +15,7 @@ // but WITHOUT ANY WARRANTY; without even the implied warranty of // MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the // GNU Lesser General Public License for more details. -// +// // You should have received a copy of the GNU Lesser General Public License // along with this program. If not, see . @@ -30,19 +30,20 @@ #include #include -using namespace std; + /** * @class Srinivas * @brief Class representing problem Srinivas **/ -class Srinivas : public Problem { - +class Srinivas : public Problem +{ + public: - Srinivas(string solutionType); - ~Srinivas(); - void evaluate(Solution *solution); - void evaluateConstraints(Solution * solution); + Srinivas(std::string solutionType); + ~Srinivas(); + void evaluate(Solution *solution); + void evaluateConstraints(Solution * solution); }; #endif /* __SRINIVAS__ */ diff --git a/src/problems/Tanaka.cpp b/src/problems/Tanaka.cpp index f029da6..ac36576 100644 --- a/src/problems/Tanaka.cpp +++ b/src/problems/Tanaka.cpp @@ -3,7 +3,7 @@ // Authors: // Esteban López-Camacho // Antonio J. Nebro -// +// // Copyright (c) 2011 Antonio J. Nebro, Juan J. Durillo // // This program is free software: you can redistribute it and/or modify @@ -15,7 +15,7 @@ // but WITHOUT ANY WARRANTY; without even the implied warranty of // MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the // GNU Lesser General Public License for more details. -// +// // You should have received a copy of the GNU Lesser General Public License // along with this program. If not, see . @@ -28,47 +28,57 @@ const double Tanaka::PI = 3.141592653589793; * Creates a new instance of the Tanaka problem. * @param solutionType The solution type must "Real" or "BinaryReal */ -Tanaka::Tanaka(string solutionType) { - numberOfVariables_ = 2; - numberOfObjectives_ = 2; - numberOfConstraints_ = 2; - problemName_ = "Tanaka"; - - lowerLimit_ = new double[numberOfVariables_]; - if (lowerLimit_ == NULL) { - cout << "Tanaka::Tanaka. Error reserving memory for storing the array of lower limits" << endl; - exit(-1) ; - } - - upperLimit_ = new double[numberOfVariables_]; - if (upperLimit_ == NULL) { - cout << "Tanaka::Tanaka. Error reserving memory for storing the array of upper limits" << endl; - exit(-1) ; - } - - for (int var = 0; var < numberOfVariables_; var++){ - lowerLimit_[var] = 10e-5; - upperLimit_[var] = PI; - } // for - - if (solutionType.compare("BinaryReal")==0) { - solutionType_ = new BinaryRealSolutionType(this); - } else if (solutionType.compare("Real")==0) { - solutionType_ = new RealSolutionType(this); - } else { - cout << "Error: solution type " << solutionType << " invalid" << endl; - exit(-1); - } +Tanaka::Tanaka(std::string solutionType) +{ + numberOfVariables_ = 2; + numberOfObjectives_ = 2; + numberOfConstraints_ = 2; + problemName_ = "Tanaka"; + + lowerLimit_ = snew double[numberOfVariables_]; + if (lowerLimit_ == nullptr) + { + std::cout << "Tanaka::Tanaka. Error reserving memory for storing the array of lower limits" << std::endl; + exit(-1) ; + } + + upperLimit_ = snew double[numberOfVariables_]; + if (upperLimit_ == nullptr) + { + std::cout << "Tanaka::Tanaka. Error reserving memory for storing the array of upper limits" << std::endl; + exit(-1) ; + } + + for (int var = 0; var < numberOfVariables_; var++) + { + lowerLimit_[var] = 10e-5; + upperLimit_[var] = PI; + } // for + + if (solutionType.compare("BinaryReal")==0) + { + solutionType_ = new BinaryRealSolutionType(this); + } + else if (solutionType.compare("Real")==0) + { + solutionType_ = new RealSolutionType(this); + } + else + { + std::cout << "Error: solution type " << solutionType << " invalid" << std::endl; + exit(-1); + } } // Tanaka /** * Destructor */ -Tanaka::~Tanaka() { - delete [] lowerLimit_ ; - delete [] upperLimit_ ; - delete solutionType_ ; +Tanaka::~Tanaka() +{ + delete [] lowerLimit_ ; + delete [] upperLimit_ ; + delete solutionType_ ; } // ~Tanaka @@ -76,53 +86,58 @@ Tanaka::~Tanaka() { * Evaluates a solution * @param solution The solution to evaluate */ -void Tanaka::evaluate(Solution *solution) { - - Variable **variables = solution->getDecisionVariables(); - - double * fx = new double[numberOfObjectives_]; - if (fx == NULL) { - cout << "Tanaka::evaluate: Error reserving memory while evaluating the problem" << endl; +void Tanaka::evaluate(Solution *solution) +{ + + Variable **variables = solution->getDecisionVariables(); + + double * fx = snew double[numberOfObjectives_]; + if (fx == nullptr) + { + std::cout << "Tanaka::evaluate: Error reserving memory while evaluating the problem" << std::endl; exit(-1); - } - - fx[0] = variables[0]->getValue(); - fx[1] = variables[1]->getValue(); - - solution->setObjective(0,fx[0]); - solution->setObjective(1,fx[1]); - - delete[]fx ; - + } + + fx[0] = variables[0]->getValue(); + fx[1] = variables[1]->getValue(); + + solution->setObjective(0,fx[0]); + solution->setObjective(1,fx[1]); + + delete[]fx ; + } // evaluate /** * Evaluates the constraint overhead of a solution * @param solution The solution */ -void Tanaka::evaluateConstraints(Solution *solution) { - - double * constraint = new double[this->getNumberOfConstraints()]; - - double x1 = solution->getDecisionVariables()[0]->getValue(); - double x2 = solution->getDecisionVariables()[1]->getValue(); - - constraint[0] = (x1*x1 + x2*x2 - 1.0 - 0.1*cos(16.0*atan(x1/x2))); - constraint[1] = - 2.0 * ( (x1-0.5)*(x1-0.5) + (x2-0.5)*(x2-0.5) - 0.5); - - int number = 0; - double total = 0.0; - for (int i = 0; i < this->getNumberOfConstraints(); i++) { - if (constraint[i]<0.0){ - number++; - total+=constraint[i]; +void Tanaka::evaluateConstraints(Solution *solution) +{ + + double * constraint = snew double[this->getNumberOfConstraints()]; + + double x1 = solution->getDecisionVariables()[0]->getValue(); + double x2 = solution->getDecisionVariables()[1]->getValue(); + + constraint[0] = (x1*x1 + x2*x2 - 1.0 - 0.1*cos(16.0*atan(x1/x2))); + constraint[1] = - 2.0 * ( (x1-0.5)*(x1-0.5) + (x2-0.5)*(x2-0.5) - 0.5); + + int number = 0; + double total = 0.0; + for (int i = 0; i < this->getNumberOfConstraints(); i++) + { + if (constraint[i]<0.0) + { + number++; + total+=constraint[i]; + } } - } - - delete [] constraint; - - solution->setOverallConstraintViolation(total); - solution->setNumberOfViolatedConstraints(number); - + + delete [] constraint; + + solution->setOverallConstraintViolation(total); + solution->setNumberOfViolatedConstraints(number); + } // evaluateConstraints diff --git a/src/problems/Tanaka.h b/src/problems/Tanaka.h index e122aba..c5aba6a 100644 --- a/src/problems/Tanaka.h +++ b/src/problems/Tanaka.h @@ -3,7 +3,7 @@ // Authors: // Esteban López-Camacho // Antonio J. Nebro -// +// // Copyright (c) 2011 Antonio J. Nebro, Juan J. Durillo // // This program is free software: you can redistribute it and/or modify @@ -15,7 +15,7 @@ // but WITHOUT ANY WARRANTY; without even the implied warranty of // MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the // GNU Lesser General Public License for more details. -// +// // You should have received a copy of the GNU Lesser General Public License // along with this program. If not, see . @@ -37,17 +37,18 @@ using namespace std; * @class Tanaka * @brief Class representing problem Tanaka **/ -class Tanaka : public Problem { +class Tanaka : public Problem +{ private: - static const double PI; - + static const double PI; + public: - Tanaka(string solutionType); - ~Tanaka(); - void evaluate(Solution *solution); - void evaluateConstraints(Solution * solution); - + Tanaka(string solutionType); + ~Tanaka(); + void evaluate(Solution *solution); + void evaluateConstraints(Solution * solution); + }; #endif /* __TANAKA__ */ diff --git a/src/problems/ZDT/CMakeLists.txt b/src/problems/ZDT/CMakeLists.txt new file mode 100644 index 0000000..294ec59 --- /dev/null +++ b/src/problems/ZDT/CMakeLists.txt @@ -0,0 +1,3 @@ +file(GLOB SOURCES "*.cpp" "*.h") +ListToString(SOURCES ";" ${SOURCES}) +LIST_APPEND("${SOURCES}") \ No newline at end of file diff --git a/src/problems/ZDT/ZDT1.cpp b/src/problems/ZDT/ZDT1.cpp index 3bda639..fdc649f 100644 --- a/src/problems/ZDT/ZDT1.cpp +++ b/src/problems/ZDT/ZDT1.cpp @@ -20,82 +20,92 @@ #include -ZDT1::ZDT1(string solutionType, int numberOfVariables) { - numberOfVariables_ = numberOfVariables; - numberOfObjectives_ = 2; - numberOfConstraints_ = 0; - problemName_ = "ZDT1"; +ZDT1::ZDT1(std::string solutionType, int numberOfVariables) +{ + numberOfVariables_ = numberOfVariables; + numberOfObjectives_ = 2; + numberOfConstraints_ = 0; + problemName_ = "ZDT1"; - lowerLimit_ = new double[numberOfVariables_];//(double *)malloc(sizeof(double)*numberOfVariables); - if (lowerLimit_ == NULL) { - cout << "Impossible to reserve memory for storing the variable lower limits" << endl; - exit(-1); - } + lowerLimit_ = snew double[numberOfVariables_];//(double *)malloc(sizeof(double)*numberOfVariables); + if (lowerLimit_ == nullptr) + { + std::cout << "Impossible to reserve memory for storing the variable lower limits" << std::endl; + exit(-1); + } - upperLimit_ = new double[numberOfVariables_];//(double *)malloc(sizeof(double)*numberOfVariables); - if (upperLimit_ == NULL) { - cout << "Impossible to reserve memory for storing the variable lower limits" << endl; - exit(-1); - } + upperLimit_ = snew double[numberOfVariables_];//(double *)malloc(sizeof(double)*numberOfVariables); + if (upperLimit_ == nullptr) + { + std::cout << "Impossible to reserve memory for storing the variable lower limits" << std::endl; + exit(-1); + } - for (int i = 0; i < numberOfVariables_; i++) { - lowerLimit_[i] = 0.0; - upperLimit_[i] = 1.0; - } + for (int i = 0; i < numberOfVariables_; i++) + { + lowerLimit_[i] = 0.0; + upperLimit_[i] = 1.0; + } - if (solutionType.compare("BinaryReal") == 0) - solutionType_ = new BinaryRealSolutionType(this) ; - else if (solutionType.compare("Real") == 0) { - solutionType_ = new RealSolutionType(this) ; - //cout << "Tipo seleccionado Real" << endl; - } - else if (solutionType.compare("ArrayReal") == 0) - solutionType_ = new ArrayRealSolutionType(this) ; - else { - cout << "Error: solution type " << solutionType << " invalid" << endl; - exit(-1) ; - } - fx_ = new double[numberOfObjectives_] ; + if (solutionType.compare("BinaryReal") == 0) + solutionType_ = new BinaryRealSolutionType(this) ; + else if (solutionType.compare("Real") == 0) + { + solutionType_ = new RealSolutionType(this) ; + //std::cout << "Tipo seleccionado Real" << std::endl; + } + else if (solutionType.compare("ArrayReal") == 0) + solutionType_ = new ArrayRealSolutionType(this) ; + else + { + std::cout << "Error: solution type " << solutionType << " invalid" << std::endl; + exit(-1) ; + } + fx_ = snew double[numberOfObjectives_] ; } -ZDT1::~ZDT1() { - delete [] lowerLimit_ ; - delete [] upperLimit_ ; - delete solutionType_ ; - delete [] fx_ ; +ZDT1::~ZDT1() +{ + delete [] lowerLimit_ ; + delete [] upperLimit_ ; + delete solutionType_ ; + delete [] fx_ ; } /** * Evaluates a solution * @param solution The solution to evaluate */ -void ZDT1::evaluate(Solution *solution) { - XReal * x = new XReal(solution); +void ZDT1::evaluate(Solution *solution) +{ + XReal * x = new XReal(solution); - fx_[0] = x->getValue(0) ; - double g = evalG(x) ; - double h = evalH(fx_[0], g) ; - fx_[1] = h * g ; + fx_[0] = x->getValue(0) ; + double g = evalG(x) ; + double h = evalH(fx_[0], g) ; + fx_[1] = h * g ; - solution->setObjective(0,fx_[0]); - solution->setObjective(1,fx_[1]); + solution->setObjective(0,fx_[0]); + solution->setObjective(1,fx_[1]); - delete x ; + delete x ; } // evaluate -double ZDT1::evalG(XReal * x) { - double g = 0.0 ; - for (int i = 1; i < x->getNumberOfDecisionVariables(); i++) - g += x->getValue(i) ; +double ZDT1::evalG(XReal * x) +{ + double g = 0.0 ; + for (int i = 1; i < x->getNumberOfDecisionVariables(); i++) + g += x->getValue(i) ; - double c = 9.0/(numberOfVariables_ - 1) ; - g = c * g ; - g = g + 1.0 ; - return g; + double c = 9.0/(numberOfVariables_ - 1) ; + g = c * g ; + g = g + 1.0 ; + return g; } -double ZDT1::evalH(double f, double g) { - double h = 0.0 ; - h = 1.0 - sqrt(f/g) ; - return h ; +double ZDT1::evalH(double f, double g) +{ + double h = 0.0 ; + h = 1.0 - sqrt(f/g) ; + return h ; } diff --git a/src/problems/ZDT/ZDT1.h b/src/problems/ZDT/ZDT1.h index 1696746..7cae8b3 100644 --- a/src/problems/ZDT/ZDT1.h +++ b/src/problems/ZDT/ZDT1.h @@ -29,17 +29,18 @@ #include #include -class ZDT1 : public Problem { +class ZDT1 : public Problem +{ private: - double evalG(XReal *x) ; - double evalH(double f, double g) ; - double * fx_ ; + double evalG(XReal *x) ; + double evalH(double f, double g) ; + double * fx_ ; public: - ZDT1(string solutionType, int numberOfVariables = 30); - void evaluate(Solution *solution); + ZDT1(std::string solutionType, int numberOfVariables = 30); + void evaluate(Solution *solution); - ~ZDT1(); + ~ZDT1(); }; #endif /* ZDT1_H_ */ diff --git a/src/problems/ZDT/ZDT1.txt b/src/problems/ZDT/ZDT1.txt new file mode 100644 index 0000000..d11058c --- /dev/null +++ b/src/problems/ZDT/ZDT1.txt @@ -0,0 +1,1000 @@ +0.0000000001 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0.0000000000 diff --git a/src/problems/ZDT/ZDT2.cpp b/src/problems/ZDT/ZDT2.cpp index c22a061..20dfd1e 100644 --- a/src/problems/ZDT/ZDT2.cpp +++ b/src/problems/ZDT/ZDT2.cpp @@ -20,84 +20,94 @@ #include -ZDT2::ZDT2(string solutionType, int numberOfVariables) { - numberOfVariables_ = numberOfVariables; - numberOfObjectives_ = 2; - numberOfConstraints_ = 0; - problemName_ = "ZDT2"; - - lowerLimit_ = new double[numberOfVariables_];//(double *)malloc(sizeof(double)*numberOfVariables); - if (lowerLimit_ == NULL) { - cout << "Impossible to reserve memory for storing the variable lower limits" << endl; - exit(-1); - } - - upperLimit_ = new double[numberOfVariables_];//(double *)malloc(sizeof(double)*numberOfVariables); - if (upperLimit_ == NULL) { - cout << "Impossible to reserve memory for storing the variable lower limits" << endl; - exit(-1); - } - - for (int i = 0; i < numberOfVariables_; i++) { - lowerLimit_[i] = 0.0; - upperLimit_[i] = 1.0; - } - - if (solutionType.compare("BinaryReal") == 0) - solutionType_ = new BinaryRealSolutionType(this) ; - else if (solutionType.compare("Real") == 0) { - solutionType_ = new RealSolutionType(this) ; - //cout << "Tipo seleccionado Real" << endl; - } - else if (solutionType.compare("ArrayReal") == 0) - solutionType_ = new ArrayRealSolutionType(this) ; - else { - cout << "Error: solution type " << solutionType << " invalid" << endl; - exit(-1) ; - } - fx_ = new double[numberOfObjectives_] ; +ZDT2::ZDT2(std::string solutionType, int numberOfVariables) +{ + numberOfVariables_ = numberOfVariables; + numberOfObjectives_ = 2; + numberOfConstraints_ = 0; + problemName_ = "ZDT2"; + + lowerLimit_ = snew double[numberOfVariables_];//(double *)malloc(sizeof(double)*numberOfVariables); + if (lowerLimit_ == nullptr) + { + std::cout << "Impossible to reserve memory for storing the variable lower limits" << std::endl; + exit(-1); + } + + upperLimit_ = snew double[numberOfVariables_];//(double *)malloc(sizeof(double)*numberOfVariables); + if (upperLimit_ == nullptr) + { + std::cout << "Impossible to reserve memory for storing the variable lower limits" << std::endl; + exit(-1); + } + + for (int i = 0; i < numberOfVariables_; i++) + { + lowerLimit_[i] = 0.0; + upperLimit_[i] = 1.0; + } + + if (solutionType.compare("BinaryReal") == 0) + solutionType_ = new BinaryRealSolutionType(this) ; + else if (solutionType.compare("Real") == 0) + { + solutionType_ = new RealSolutionType(this) ; + //std::cout << "Tipo seleccionado Real" << std::endl; + } + else if (solutionType.compare("ArrayReal") == 0) + solutionType_ = new ArrayRealSolutionType(this) ; + else + { + std::cout << "Error: solution type " << solutionType << " invalid" << std::endl; + exit(-1) ; + } + fx_ = snew double[numberOfObjectives_] ; } -ZDT2::~ZDT2() { - delete [] lowerLimit_ ; - delete [] upperLimit_ ; - delete solutionType_ ; - delete [] fx_ ; +ZDT2::~ZDT2() +{ + delete [] lowerLimit_ ; + delete [] upperLimit_ ; + delete solutionType_ ; + delete [] fx_ ; } /** * Evaluates a solution * @param solution The solution to evaluate */ -void ZDT2::evaluate(Solution *solution) { - XReal * x = new XReal(solution); +void ZDT2::evaluate(Solution *solution) +{ + XReal * x = new XReal(solution); - fx_[0] = x->getValue(0) ; - double g = evalG(x) ; - double h = evalH(fx_[0], g) ; - fx_[1] = h * g ; + fx_[0] = x->getValue(0) ; + double g = evalG(x) ; + double h = evalH(fx_[0], g) ; + fx_[1] = h * g ; - solution->setObjective(0,fx_[0]); - solution->setObjective(1,fx_[1]); + solution->setObjective(0,fx_[0]); + solution->setObjective(1,fx_[1]); - delete x ; + delete x ; } // evaluate -double ZDT2::evalG(XReal * x) { - double g = 0.0 ; - for (int i = 1; i < x->getNumberOfDecisionVariables(); i++) - g += x->getValue(i) ; +double ZDT2::evalG(XReal * x) +{ + double g = 0.0 ; + for (int i = 1; i < x->getNumberOfDecisionVariables(); i++) + g += x->getValue(i) ; - double c = 9.0/(numberOfVariables_ - 1) ; - g = c * g ; - g = g + 1.0 ; - return g; + double c = 9.0/(numberOfVariables_ - 1) ; + g = c * g ; + g = g + 1.0 ; + return g; } -double ZDT2::evalH(double f, double g) { - double h = 0.0 ; - h = 1.0 - pow(f/g, 2.0) ; - return h ; +double ZDT2::evalH(double f, double g) +{ + double h = 0.0 ; + h = 1.0 - pow(f/g, 2.0) ; + return h ; } diff --git a/src/problems/ZDT/ZDT2.h b/src/problems/ZDT/ZDT2.h index 31c6119..73801e2 100644 --- a/src/problems/ZDT/ZDT2.h +++ b/src/problems/ZDT/ZDT2.h @@ -30,17 +30,18 @@ #include -class ZDT2 : public Problem{ +class ZDT2 : public Problem +{ private: - double evalG(XReal *x) ; - double evalH(double f, double g) ; - double * fx_ ; + double evalG(XReal *x) ; + double evalH(double f, double g) ; + double * fx_ ; public: - ZDT2(string solutionType, int numberOfVariables = 30); - void evaluate(Solution *solution); + ZDT2(std::string solutionType, int numberOfVariables = 30); + void evaluate(Solution *solution); - virtual ~ZDT2(); + virtual ~ZDT2(); }; #endif /* __ZDT2_H__ */ diff --git 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0.0138609040 +0.9940402226 0.0118840359 +0.9950345858 0.0099061731 +0.9960284521 0.0079273226 +0.9970219902 0.0059471511 +0.9980151238 0.0039658127 +0.9990078085 0.0019833986 +1.0000000000 0.0000000000 diff --git a/src/problems/ZDT/ZDT3.cpp b/src/problems/ZDT/ZDT3.cpp index e6d7b46..d9725be 100644 --- a/src/problems/ZDT/ZDT3.cpp +++ b/src/problems/ZDT/ZDT3.cpp @@ -22,83 +22,93 @@ const double ZDT3::PI = 3.141592653589793; -ZDT3::ZDT3(string solutionType, int numberOfVariables) { - numberOfVariables_ = numberOfVariables; - numberOfObjectives_ = 2; - numberOfConstraints_ = 0; - problemName_ = "ZDT3"; - - lowerLimit_ = new double[numberOfVariables_];//(double *)malloc(sizeof(double)*numberOfVariables); - if (lowerLimit_ == NULL) { - cout << "Impossible to reserve memory for storing the variable lower limits" << endl; - exit(-1); - } - - upperLimit_ = new double[numberOfVariables_];//(double *)malloc(sizeof(double)*numberOfVariables); - if (upperLimit_ == NULL) { - cout << "Impossible to reserve memory for storing the variable lower limits" << endl; - exit(-1); - } - - for (int i = 0; i < numberOfVariables_; i++) { - lowerLimit_[i] = 0.0; - upperLimit_[i] = 1.0; - } - - if (solutionType.compare("BinaryReal") == 0) - solutionType_ = new BinaryRealSolutionType(this) ; - else if (solutionType.compare("Real") == 0) { - solutionType_ = new RealSolutionType(this) ; - //cout << "Tipo seleccionado Real" << endl; - } - else if (solutionType.compare("ArrayReal") == 0) - solutionType_ = new ArrayRealSolutionType(this) ; - else { - cout << "Error: solution type " << solutionType << " invalid" << endl; - exit(-1) ; - } - fx_ = new double[numberOfObjectives_] ; +ZDT3::ZDT3(std::string solutionType, int numberOfVariables) +{ + numberOfVariables_ = numberOfVariables; + numberOfObjectives_ = 2; + numberOfConstraints_ = 0; + problemName_ = "ZDT3"; + + lowerLimit_ = snew double[numberOfVariables_];//(double *)malloc(sizeof(double)*numberOfVariables); + if (lowerLimit_ == nullptr) + { + std::cout << "Impossible to reserve memory for storing the variable lower limits" << std::endl; + exit(-1); + } + + upperLimit_ = snew double[numberOfVariables_];//(double *)malloc(sizeof(double)*numberOfVariables); + if (upperLimit_ == nullptr) + { + std::cout << "Impossible to reserve memory for storing the variable lower limits" << std::endl; + exit(-1); + } + + for (int i = 0; i < numberOfVariables_; i++) + { + lowerLimit_[i] = 0.0; + upperLimit_[i] = 1.0; + } + + if (solutionType.compare("BinaryReal") == 0) + solutionType_ = new BinaryRealSolutionType(this) ; + else if (solutionType.compare("Real") == 0) + { + solutionType_ = new RealSolutionType(this) ; + //std::cout << "Tipo seleccionado Real" << std::endl; + } + else if (solutionType.compare("ArrayReal") == 0) + solutionType_ = new ArrayRealSolutionType(this) ; + else + { + std::cout << "Error: solution type " << solutionType << " invalid" << std::endl; + exit(-1) ; + } + fx_ = snew double[numberOfObjectives_] ; } -ZDT3::~ZDT3() { - delete [] lowerLimit_ ; - delete [] upperLimit_ ; - delete solutionType_ ; - delete [] fx_ ; +ZDT3::~ZDT3() +{ + delete [] lowerLimit_ ; + delete [] upperLimit_ ; + delete solutionType_ ; + delete [] fx_ ; } /** * Evaluates a solution * @param solution The solution to evaluate */ -void ZDT3::evaluate(Solution *solution) { - XReal * x = new XReal(solution); +void ZDT3::evaluate(Solution *solution) +{ + XReal * x = new XReal(solution); - fx_[0] = x->getValue(0) ; - double g = evalG(x) ; - double h = evalH(fx_[0], g) ; - fx_[1] = h * g ; + fx_[0] = x->getValue(0) ; + double g = evalG(x) ; + double h = evalH(fx_[0], g) ; + fx_[1] = h * g ; - solution->setObjective(0,fx_[0]); - solution->setObjective(1,fx_[1]); + solution->setObjective(0,fx_[0]); + solution->setObjective(1,fx_[1]); - delete x ; + delete x ; } // evaluate -double ZDT3::evalG(XReal * x) { - double g = 0.0 ; - for (int i = 1; i < x->getNumberOfDecisionVariables(); i++) - g += x->getValue(i) ; +double ZDT3::evalG(XReal * x) +{ + double g = 0.0 ; + for (int i = 1; i < x->getNumberOfDecisionVariables(); i++) + g += x->getValue(i) ; - double c = 9.0/(numberOfVariables_ - 1) ; - g = c * g ; - g = g + 1.0 ; - return g; + double c = 9.0/(numberOfVariables_ - 1) ; + g = c * g ; + g = g + 1.0 ; + return g; } -double ZDT3::evalH(double f, double g) { - double h = 0.0 ; - h = 1.0 - sqrt(f/g) - (f/g)*sin(10.0*PI*f); - return h ; +double ZDT3::evalH(double f, double g) +{ + double h = 0.0 ; + h = 1.0 - sqrt(f/g) - (f/g)*sin(10.0*PI*f); + return h ; } diff --git a/src/problems/ZDT/ZDT3.h b/src/problems/ZDT/ZDT3.h index 87ddd72..3b71c4b 100644 --- a/src/problems/ZDT/ZDT3.h +++ b/src/problems/ZDT/ZDT3.h @@ -31,17 +31,18 @@ #include -class ZDT3 : public Problem { +class ZDT3 : public Problem +{ private: - double evalG(XReal *x) ; - double evalH(double f, double g) ; - double * fx_ ; - static const double PI ; + double evalG(XReal *x) ; + double evalH(double f, double g) ; + double * fx_ ; + static const double PI ; public: - ZDT3(string solutionType, int numberOfVariables = 30); - void evaluate(Solution *solution); - virtual ~ZDT3(); + ZDT3(std::string solutionType, int numberOfVariables = 30); + void evaluate(Solution *solution); + virtual ~ZDT3(); }; #endif /* __ZDT3_H__ */ diff --git a/src/problems/ZDT/ZDT3.txt b/src/problems/ZDT/ZDT3.txt new file mode 100644 index 0000000..7cc4b0a --- /dev/null +++ b/src/problems/ZDT/ZDT3.txt @@ -0,0 +1,1000 @@ +0.0000000000 1.0000000000 +0.0001669867 0.9870767898 +0.0003556074 0.9811384730 +0.0005020830 0.9775848727 +0.0005936368 0.9756242656 +0.0008526856 0.9707763811 +0.0009594493 0.9689961054 +0.0015383844 0.9607034357 +0.0020570965 0.9545119258 +0.0026049104 0.9487487404 +0.0030767688 0.9442344352 +0.0034180675 0.9411694253 +0.0036717564 0.9389823762 +0.0038889639 0.9371644873 +0.0042634278 0.9341357353 +0.0045677159 0.9317619051 +0.0048025025 0.9299780777 +0.0049491266 0.9288835705 +0.0052231746 0.9268752322 +0.0056348254 0.9239422323 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b/src/problems/ZDT/ZDT4.cpp @@ -22,84 +22,94 @@ const double ZDT4::PI = 3.141592653589793; -ZDT4::ZDT4(string solutionType, int numberOfVariables) { - numberOfVariables_ = numberOfVariables; - numberOfObjectives_ = 2; - numberOfConstraints_ = 0; - problemName_ = "ZDT4"; - - lowerLimit_ = new double[numberOfVariables_];//(double *)malloc(sizeof(double)*numberOfVariables); - if (lowerLimit_ == NULL) { - cout << "Impossible to reserve memory for storing the variable lower limits" << endl; - exit(-1); - } - - upperLimit_ = new double[numberOfVariables_];//(double *)malloc(sizeof(double)*numberOfVariables); - if (upperLimit_ == NULL) { - cout << "Impossible to reserve memory for storing the variable lower limits" << endl; - exit(-1); - } - - lowerLimit_[0] = 0.0; - upperLimit_[0] = 1.0; - for (int i = 1; i < numberOfVariables_; i++) { - lowerLimit_[i] = -5.0; - upperLimit_[i] = 5.0; - } - - if (solutionType.compare("BinaryReal") == 0) - solutionType_ = new BinaryRealSolutionType(this) ; - else if (solutionType.compare("Real") == 0) { - solutionType_ = new RealSolutionType(this) ; - //cout << "Tipo seleccionado Real" << endl; - } - else if (solutionType.compare("ArrayReal") == 0) - solutionType_ = new ArrayRealSolutionType(this) ; - else { - cout << "Error: solution type " << solutionType << " invalid" << endl; - exit(-1) ; - } - fx_ = new double[numberOfObjectives_] ; +ZDT4::ZDT4(std::string solutionType, int numberOfVariables) +{ + numberOfVariables_ = numberOfVariables; + numberOfObjectives_ = 2; + numberOfConstraints_ = 0; + problemName_ = "ZDT4"; + + lowerLimit_ = snew double[numberOfVariables_];//(double *)malloc(sizeof(double)*numberOfVariables); + if (lowerLimit_ == nullptr) + { + std::cout << "Impossible to reserve memory for storing the variable lower limits" << std::endl; + exit(-1); + } + + upperLimit_ = snew double[numberOfVariables_];//(double *)malloc(sizeof(double)*numberOfVariables); + if (upperLimit_ == nullptr) + { + std::cout << "Impossible to reserve memory for storing the variable lower limits" << std::endl; + exit(-1); + } + + lowerLimit_[0] = 0.0; + upperLimit_[0] = 1.0; + for (int i = 1; i < numberOfVariables_; i++) + { + lowerLimit_[i] = -5.0; + upperLimit_[i] = 5.0; + } + + if (solutionType.compare("BinaryReal") == 0) + solutionType_ = new BinaryRealSolutionType(this) ; + else if (solutionType.compare("Real") == 0) + { + solutionType_ = new RealSolutionType(this) ; + //std::cout << "Tipo seleccionado Real" << std::endl; + } + else if (solutionType.compare("ArrayReal") == 0) + solutionType_ = new ArrayRealSolutionType(this) ; + else + { + std::cout << "Error: solution type " << solutionType << " invalid" << std::endl; + exit(-1) ; + } + fx_ = snew double[numberOfObjectives_] ; } -ZDT4::~ZDT4() { - delete [] lowerLimit_ ; - delete [] upperLimit_ ; - delete solutionType_ ; - delete [] fx_ ; +ZDT4::~ZDT4() +{ + delete [] lowerLimit_ ; + delete [] upperLimit_ ; + delete solutionType_ ; + delete [] fx_ ; } /** * Evaluates a solution * @param solution The solution to evaluate */ -void ZDT4::evaluate(Solution *solution) { - XReal * x = new XReal(solution); - double * fx = new double[numberOfObjectives_] ; +void ZDT4::evaluate(Solution *solution) +{ + XReal * x = new XReal(solution); + double * fx = snew double[numberOfObjectives_] ; - fx_[0] = x->getValue(0) ; - double g = evalG(x) ; - double h = evalH(fx_[0], g) ; - fx_[1] = h * g ; + fx_[0] = x->getValue(0) ; + double g = evalG(x) ; + double h = evalH(fx_[0], g) ; + fx_[1] = h * g ; - solution->setObjective(0,fx_[0]); - solution->setObjective(1,fx_[1]); + solution->setObjective(0,fx_[0]); + solution->setObjective(1,fx_[1]); - delete [] fx ; - delete x ; + delete [] fx ; + delete x ; } // evaluate -double ZDT4::evalG(XReal * x) { - double g = 0.0 ; - for (int i = 1; i < x->getNumberOfDecisionVariables(); i++) - g += pow(x->getValue(i), 2.0) - - 10.0 * cos(4.0 * PI * x->getValue(i)); +double ZDT4::evalG(XReal * x) +{ + double g = 0.0 ; + for (int i = 1; i < x->getNumberOfDecisionVariables(); i++) + g += pow(x->getValue(i), 2.0) - + 10.0 * cos(4.0 * PI * x->getValue(i)); - double c = 1.0 + 10.0 * (numberOfVariables_ - 1) ; - return g + c; + double c = 1.0 + 10.0 * (numberOfVariables_ - 1) ; + return g + c; } -double ZDT4::evalH(double f, double g) { - return 1.0 - sqrt(f/g) ; +double ZDT4::evalH(double f, double g) +{ + return 1.0 - sqrt(f/g) ; } diff --git a/src/problems/ZDT/ZDT4.h b/src/problems/ZDT/ZDT4.h index cb45a96..c7ee090 100644 --- a/src/problems/ZDT/ZDT4.h +++ b/src/problems/ZDT/ZDT4.h @@ -31,17 +31,18 @@ #include -class ZDT4 : public Problem { +class ZDT4 : public Problem +{ private: - double evalG(XReal *x) ; - double evalH(double f, double g) ; - double * fx_ ; - static const double PI ; + double evalG(XReal *x) ; + double evalH(double f, double g) ; + double * fx_ ; + static const double PI ; public: - ZDT4(string solutionType, int numberOfVariables = 10); - void evaluate(Solution *solution); - virtual ~ZDT4(); + ZDT4(std::string solutionType, int numberOfVariables = 10); + void evaluate(Solution *solution); + virtual ~ZDT4(); }; #endif /* __ZDT4_H__ */ diff --git a/src/problems/ZDT/ZDT4.txt b/src/problems/ZDT/ZDT4.txt new file mode 100644 index 0000000..d9aedde --- /dev/null +++ b/src/problems/ZDT/ZDT4.txt @@ -0,0 +1,1000 @@ +0.0000000001 0.9999894726 +0.0002105478 0.9854897362 +0.0006312647 0.9748750180 +0.0011630803 0.9658960376 +0.0017746306 0.9578736358 +0.0024505398 0.9504970728 +0.0031768967 0.9436360339 +0.0039503274 0.9371483698 +0.0047628349 0.9309867048 +0.0056133085 0.9250779837 +0.0064844270 0.9194740603 +0.0073825092 0.9140784704 +0.0083046512 0.9088701410 +0.0092513217 0.9038162085 +0.0102235345 0.8988885045 +0.0112037024 0.8941524567 +0.0122063005 0.8895178727 +0.0132289862 0.8849826699 +0.0142533197 0.8806127324 +0.0152866946 0.8763606266 +0.0163381500 0.8721792270 +0.0173920785 0.8681209701 +0.0184482339 0.8641757241 +0.0195148773 0.8603043403 +0.0205965083 0.8564851634 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+0.9879497292 0.0060433967 +0.9889528489 0.0055389153 +0.9899562232 0.0050345618 +0.9909597362 0.0045303942 +0.9919633539 0.0040264291 +0.9929672257 0.0035225915 +0.9939712250 0.0030189445 +0.9949754780 0.0025154247 +0.9959799285 0.0020120600 +0.9969846132 0.0015088317 +0.9979894950 0.0010057583 +0.9989946210 0.0005028159 +1.0000000000 0.0000000000 diff --git a/src/problems/ZDT/ZDT5.cpp b/src/problems/ZDT/ZDT5.cpp index ad71de1..9e6b73c 100644 --- a/src/problems/ZDT/ZDT5.cpp +++ b/src/problems/ZDT/ZDT5.cpp @@ -20,77 +20,89 @@ #include "ZDT5.h" -ZDT5::ZDT5(string solutionType, int numberOfVariables) { - cout << "Solutiontype: " << solutionType << endl ; - numberOfVariables_ = numberOfVariables; - numberOfObjectives_ = 2; - numberOfConstraints_ = 0; - problemName_ = "ZDT5"; - - cout << "Problem: " << problemName_ << endl ; - - length_ = new int[numberOfVariables_]; - length_[0] = 30; - for (int var = 1; var < numberOfVariables_; var++) { - length_[var] = 5; - } - - if (solutionType.compare("Binary") == 0) - solutionType_ = new BinarySolutionType(this) ; - else { - cout << "Error: solution type " << solutionType << " invalid" << endl; - exit(-1) ; - } - fx_ = new double[numberOfObjectives_] ; +ZDT5::ZDT5(std::string solutionType, int numberOfVariables) +{ + std::cout << "Solutiontype: " << solutionType << std::endl ; + numberOfVariables_ = numberOfVariables; + numberOfObjectives_ = 2; + numberOfConstraints_ = 0; + problemName_ = "ZDT5"; + + std::cout << "Problem: " << problemName_ << std::endl ; + + length_ = snew int[numberOfVariables_]; + length_[0] = 30; + for (int var = 1; var < numberOfVariables_; var++) + { + length_[var] = 5; + } + + if (solutionType.compare("Binary") == 0) + solutionType_ = new BinarySolutionType(this) ; + else + { + std::cout << "Error: solution type " << solutionType << " invalid" << std::endl; + exit(-1) ; + } + fx_ = snew double[numberOfObjectives_] ; } // ZDT5::ZDT5 -ZDT5::~ZDT5() { - delete [] length_ ; - delete [] fx_ ; +ZDT5::~ZDT5() +{ + delete [] length_ ; + delete [] fx_ ; } /** * Evaluates a solution * @param solution The solution to evaluate */ -void ZDT5::evaluate(Solution *solution) { - Binary * variable ; - int counter ; +void ZDT5::evaluate(Solution *solution) +{ + Binary * variable ; + int counter ; - variable = (Binary *)(solution->getDecisionVariables()[0]) ; + variable = (Binary *)(solution->getDecisionVariables()[0]) ; - fx_[0] = 1 + variable->cardinality(); + fx_[0] = 1 + variable->cardinality(); - double g = evalG(solution) ; - double h = evalH(fx_[0],g) ; - fx_[1] = h * g ; + double g = evalG(solution) ; + double h = evalH(fx_[0],g) ; + fx_[1] = h * g ; - solution->setObjective(0,fx_[0]); - solution->setObjective(1,fx_[1]); + solution->setObjective(0,fx_[0]); + solution->setObjective(1,fx_[1]); } // evaluate -double ZDT5::evalG(Solution * solution) { - double res = 0.0; - Binary * variable ; +double ZDT5::evalG(Solution * solution) +{ + double res = 0.0; + Binary * variable ; - for (int i = 1; i < numberOfVariables_; i++) { - variable = (Binary *)(solution->getDecisionVariables()[i]) ; - res += evalV(variable->cardinality()); - } + for (int i = 1; i < numberOfVariables_; i++) + { + variable = (Binary *)(solution->getDecisionVariables()[i]) ; + res += evalV(variable->cardinality()); + } - return res; + return res; } -double ZDT5::evalH(double f, double g) { - return 1 / f; +double ZDT5::evalH(double f, double g) +{ + return 1 / f; } -double ZDT5::evalV(double value) { - if (value < 5.0) { - return 2.0 + value; - } else { - return 1.0; - } +double ZDT5::evalV(double value) +{ + if (value < 5.0) + { + return 2.0 + value; + } + else + { + return 1.0; + } } diff --git a/src/problems/ZDT/ZDT5.h b/src/problems/ZDT/ZDT5.h index 2ca5806..9c1bca3 100644 --- a/src/problems/ZDT/ZDT5.h +++ b/src/problems/ZDT/ZDT5.h @@ -27,18 +27,19 @@ #include #include -class ZDT5 : public Problem { +class ZDT5 : public Problem +{ private: - double evalG(Solution *x) ; - double evalH(double f, double g) ; - double evalV(double) ; + double evalG(Solution *x) ; + double evalH(double f, double g) ; + double evalV(double) ; - double * fx_ ; + double * fx_ ; public: - ZDT5(string solutionType, int numberOfVariables = 11); - void evaluate(Solution *solution); + ZDT5(std::string solutionType, int numberOfVariables = 11); + void evaluate(Solution *solution); - virtual ~ZDT5(); + virtual ~ZDT5(); }; #endif /* __ZDT5_H__ */ diff --git a/src/problems/ZDT/ZDT6.cpp b/src/problems/ZDT/ZDT6.cpp index c6b6064..d9b53bc 100644 --- a/src/problems/ZDT/ZDT6.cpp +++ b/src/problems/ZDT/ZDT6.cpp @@ -22,83 +22,93 @@ const double ZDT6::PI = 3.141592653589793; -ZDT6::ZDT6(string solutionType, int numberOfVariables) { - numberOfVariables_ = numberOfVariables; - numberOfObjectives_ = 2; - numberOfConstraints_ = 0; - problemName_ = "ZDT6"; - - lowerLimit_ = new double[numberOfVariables_];//(double *)malloc(sizeof(double)*numberOfVariables); - if (lowerLimit_ == NULL) { - cout << "Impossible to reserve memory for storing the variable lower limits" << endl; - exit(-1); - } - - upperLimit_ = new double[numberOfVariables_];//(double *)malloc(sizeof(double)*numberOfVariables); - if (upperLimit_ == NULL) { - cout << "Impossible to reserve memory for storing the variable lower limits" << endl; - exit(-1); - } - - for (int i = 0; i < numberOfVariables_; i++) { - lowerLimit_[i] = 0.0; - upperLimit_[i] = 1.0; - } - - if (solutionType.compare("BinaryReal") == 0) - solutionType_ = new BinaryRealSolutionType(this) ; - else if (solutionType.compare("Real") == 0) { - solutionType_ = new RealSolutionType(this) ; - //cout << "Tipo seleccionado Real" << endl; - } - else if (solutionType.compare("ArrayReal") == 0) - solutionType_ = new ArrayRealSolutionType(this) ; - else { - cout << "Error: solution type " << solutionType << " invalid" << endl; - exit(-1) ; - } - fx_ = new double[numberOfObjectives_] ; +ZDT6::ZDT6(std::string solutionType, int numberOfVariables) +{ + numberOfVariables_ = numberOfVariables; + numberOfObjectives_ = 2; + numberOfConstraints_ = 0; + problemName_ = "ZDT6"; + + lowerLimit_ = snew double[numberOfVariables_];//(double *)malloc(sizeof(double)*numberOfVariables); + if (lowerLimit_ == nullptr) + { + std::cout << "Impossible to reserve memory for storing the variable lower limits" << std::endl; + exit(-1); + } + + upperLimit_ = snew double[numberOfVariables_];//(double *)malloc(sizeof(double)*numberOfVariables); + if (upperLimit_ == nullptr) + { + std::cout << "Impossible to reserve memory for storing the variable lower limits" << std::endl; + exit(-1); + } + + for (int i = 0; i < numberOfVariables_; i++) + { + lowerLimit_[i] = 0.0; + upperLimit_[i] = 1.0; + } + + if (solutionType.compare("BinaryReal") == 0) + solutionType_ = new BinaryRealSolutionType(this) ; + else if (solutionType.compare("Real") == 0) + { + solutionType_ = new RealSolutionType(this) ; + //std::cout << "Tipo seleccionado Real" << std::endl; + } + else if (solutionType.compare("ArrayReal") == 0) + solutionType_ = new ArrayRealSolutionType(this) ; + else + { + std::cout << "Error: solution type " << solutionType << " invalid" << std::endl; + exit(-1) ; + } + fx_ = snew double[numberOfObjectives_] ; } -ZDT6::~ZDT6() { - delete [] lowerLimit_ ; - delete [] upperLimit_ ; - delete solutionType_ ; - delete [] fx_ ; +ZDT6::~ZDT6() +{ + delete [] lowerLimit_ ; + delete [] upperLimit_ ; + delete solutionType_ ; + delete [] fx_ ; } /** * Evaluates a solution * @param solution The solution to evaluate */ -void ZDT6::evaluate(Solution *solution) { - XReal * x = new XReal(solution); +void ZDT6::evaluate(Solution *solution) +{ + XReal * x = new XReal(solution); - double x1 = x->getValue(0) ; - fx_[0] = 1.0 - exp(-4.0*x1) * pow(sin(6.0*PI*x1), 6.0) ; - double g = evalG(x) ; - double h = evalH(fx_[0], g) ; - fx_[1] = h * g ; + double x1 = x->getValue(0) ; + fx_[0] = 1.0 - exp(-4.0*x1) * pow(sin(6.0*PI*x1), 6.0) ; + double g = evalG(x) ; + double h = evalH(fx_[0], g) ; + fx_[1] = h * g ; - solution->setObjective(0,fx_[0]); - solution->setObjective(1,fx_[1]); + solution->setObjective(0,fx_[0]); + solution->setObjective(1,fx_[1]); - delete x ; + delete x ; } // evaluate -double ZDT6::evalG(XReal * x) { - double g = 0.0 ; - for (int i = 1; i < x->getNumberOfDecisionVariables(); i++) - g += x->getValue(i) ; - - g = g / (numberOfVariables_ - 1) ; - g = pow(g, 0.25) ; - g = 0.9 * g ; - g = g + 1.0 ; - return g; +double ZDT6::evalG(XReal * x) +{ + double g = 0.0 ; + for (int i = 1; i < x->getNumberOfDecisionVariables(); i++) + g += x->getValue(i) ; + + g = g / (numberOfVariables_ - 1) ; + g = pow(g, 0.25) ; + g = 0.9 * g ; + g = g + 1.0 ; + return g; } -double ZDT6::evalH(double f, double g) { - return 1.0 - pow((f/g), 2.0) ; +double ZDT6::evalH(double f, double g) +{ + return 1.0 - pow((f/g), 2.0) ; } diff --git a/src/problems/ZDT/ZDT6.h b/src/problems/ZDT/ZDT6.h index affd9be..3499c42 100644 --- a/src/problems/ZDT/ZDT6.h +++ b/src/problems/ZDT/ZDT6.h @@ -30,17 +30,18 @@ #include #include -class ZDT6 : public Problem { +class ZDT6 : public Problem +{ private: - double evalG(XReal *x) ; - double evalH(double f, double g) ; - double * fx_ ; - static const double PI ; + double evalG(XReal *x) ; + double evalH(double f, double g) ; + double * fx_ ; + static const double PI ; public: - ZDT6(string solutionType, int numberOfVariables = 10); - void evaluate(Solution *solution); - virtual ~ZDT6(); + ZDT6(string solutionType, int numberOfVariables = 10); + void evaluate(Solution *solution); + virtual ~ZDT6(); }; #endif /* __ZDT6_H__ */ diff --git a/src/problems/ZDT/ZDT6.txt b/src/problems/ZDT/ZDT6.txt new file mode 100644 index 0000000..71cf12c --- /dev/null +++ b/src/problems/ZDT/ZDT6.txt @@ -0,0 +1,1000 @@ +0.2807753191 0.9211652202 +0.2814990682 0.9207582746 +0.2822222294 0.9203506133 +0.2829444640 0.9199424303 +0.2836657932 0.9195337178 +0.2843873868 0.9191238143 +0.2851090310 0.9187128404 +0.2858297620 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a/src/problems/singleObjective/CEC2005Problem.cpp +++ b/src/problems/singleObjective/CEC2005Problem.cpp @@ -31,25 +31,27 @@ const double CEC2005Problem::PI = 3.141592653589793; * @param problemId CEC2005 problem id * @param numberOfVariables Number of variables of the problem */ -CEC2005Problem::CEC2005Problem(string solutionType, int problemID, int numberOfVariables) { - numberOfVariables_ = numberOfVariables ; - numberOfObjectives_ = 1; - numberOfConstraints_ = 0; +CEC2005Problem::CEC2005Problem(std::string solutionType, int problemID, int numberOfVariables) +{ + numberOfVariables_ = numberOfVariables ; + numberOfObjectives_ = 1; + numberOfConstraints_ = 0; - Benchmark * cec2005ProblemFactory = new Benchmark() ; - testFunction_ = cec2005ProblemFactory->testFunctionFactory(problemID, numberOfVariables) ; - delete cec2005ProblemFactory; + Benchmark * cec2005ProblemFactory = snew Benchmark() ; + testFunction_ = cec2005ProblemFactory->testFunctionFactory(problemID, numberOfVariables) ; + delete cec2005ProblemFactory; - problemName_ = "CEC2005: " + testFunction_->name(); + problemName_ = "CEC2005: " + testFunction_->name(); - upperLimit_ = new double[numberOfVariables_]; - lowerLimit_ = new double[numberOfVariables_]; + upperLimit_ = snew double[numberOfVariables_]; + lowerLimit_ = snew double[numberOfVariables_]; - double ulimit = 0 ; - double llimit = 0 ; + double ulimit = 0 ; + double llimit = 0 ; - switch (problemID) { + switch (problemID) + { case 1: case 2: case 3: @@ -57,17 +59,18 @@ CEC2005Problem::CEC2005Problem(string solutionType, int problemID, int numberOfV case 5: case 6: case 14: - ulimit = 100; - llimit = -100 ; - break ; + ulimit = 100; + llimit = -100 ; + break ; case 7: case 25: - ulimit = std::numeric_limits::max(); - llimit = -std::numeric_limits::max(); - break ; + ulimit = std::numeric_limits::max(); + llimit = -std::numeric_limits::max(); + break ; case 8: - ulimit = 32; llimit = -32 ; - break ; + ulimit = 32; + llimit = -32 ; + break ; case 9: case 10: case 15: @@ -80,32 +83,38 @@ CEC2005Problem::CEC2005Problem(string solutionType, int problemID, int numberOfV case 22: case 23: case 24: - ulimit = 5; llimit = -5 ; - break ; + ulimit = 5; + llimit = -5 ; + break ; case 11: - ulimit = 0.5; llimit = -0.5 ; - break ; + ulimit = 0.5; + llimit = -0.5 ; + break ; case 12: - ulimit = PI; llimit = -PI ; - break ; + ulimit = PI; + llimit = -PI ; + break ; case 13: - ulimit = 3; llimit = 1 ; - break ; - } - - for (int var = 0; var < numberOfVariables_; var++){ - lowerLimit_[var] = llimit ; - upperLimit_[var] = ulimit ; - } // for - - if (solutionType.compare("BinaryReal") == 0) - solutionType_ = new BinaryRealSolutionType(this) ; - else if (solutionType.compare("Real") == 0) - solutionType_ = new RealSolutionType(this) ; - else { - cout << "Error: solution type " << solutionType << " invalid" << endl; - exit(-1) ; - } // if + ulimit = 3; + llimit = 1 ; + break ; + } + + for (int var = 0; var < numberOfVariables_; var++) + { + lowerLimit_[var] = llimit ; + upperLimit_[var] = ulimit ; + } // for + + if (solutionType.compare("BinaryReal") == 0) + solutionType_ = snew BinaryRealSolutionType(this) ; + else if (solutionType.compare("Real") == 0) + solutionType_ = snew RealSolutionType(this) ; + else + { + std::cout << "Error: solution type " << solutionType << " invalid" << std::endl; + exit(-1) ; + } // if } // CEC2005Problem @@ -113,11 +122,12 @@ CEC2005Problem::CEC2005Problem(string solutionType, int problemID, int numberOfV /** * Destructor */ -CEC2005Problem::~CEC2005Problem() { - delete [] lowerLimit_ ; - delete [] upperLimit_ ; - delete solutionType_ ; - delete testFunction_; +CEC2005Problem::~CEC2005Problem() +{ + delete [] lowerLimit_ ; + delete [] upperLimit_ ; + delete solutionType_ ; + delete testFunction_; } // ~CEC2005Problem @@ -125,19 +135,21 @@ CEC2005Problem::~CEC2005Problem() { * Evaluates a solution * @param solution The solution to evaluate */ -void CEC2005Problem::evaluate(Solution *solution) { - Variable ** decisionVariables = solution->getDecisionVariables(); - double * x = new double[numberOfVariables_] ; +void CEC2005Problem::evaluate(Solution *solution) +{ + Variable ** decisionVariables = solution->getDecisionVariables(); + double * x = snew double[numberOfVariables_] ; - for (int i = 0 ; i < numberOfVariables_; i++) { - x[i] = decisionVariables[i]->getValue() ; - } + for (int i = 0 ; i < numberOfVariables_; i++) + { + x[i] = decisionVariables[i]->getValue() ; + } - double result ; - result = testFunction_->f(x) ; + double result ; + result = testFunction_->f(x) ; - delete [] x; + delete [] x; - solution->setObjective(0, result); + solution->setObjective(0, result); } // evaluate diff --git a/src/problems/singleObjective/CEC2005Problem.h b/src/problems/singleObjective/CEC2005Problem.h index f15fe31..224edb3 100644 --- a/src/problems/singleObjective/CEC2005Problem.h +++ b/src/problems/singleObjective/CEC2005Problem.h @@ -36,16 +36,17 @@ * @class CEC2005Problem * @brief Class representing all problems in CEC2005 **/ -class CEC2005Problem : public Problem { +class CEC2005Problem : public Problem +{ private: - TestFunc * testFunction_ ; - static const double PI; + TestFunc * testFunction_ ; + static const double PI; public: - CEC2005Problem(string solutionType, int problemID, int numberOfVariables = 10); - ~CEC2005Problem(); - void evaluate(Solution *solution); + CEC2005Problem(std::string solutionType, int problemID, int numberOfVariables = 10); + ~CEC2005Problem(); + void evaluate(Solution *solution); }; #endif /* __CEC_2005_PROBLEM__ */ diff --git a/src/problems/singleObjective/CMakeLists.txt b/src/problems/singleObjective/CMakeLists.txt new file mode 100644 index 0000000..59a3d9c --- /dev/null +++ b/src/problems/singleObjective/CMakeLists.txt @@ -0,0 +1,4 @@ +file(GLOB SOURCES "*.cpp" "*.h") +ListToString(SOURCES ";" ${SOURCES}) +LIST_APPEND("${SOURCES}") +add_subdirectory(cec2005Competition) \ No newline at end of file diff --git a/src/problems/singleObjective/Griewank.cpp b/src/problems/singleObjective/Griewank.cpp index 0b8d1f6..5d1aed7 100644 --- a/src/problems/singleObjective/Griewank.cpp +++ b/src/problems/singleObjective/Griewank.cpp @@ -2,7 +2,7 @@ // // Authors: // Esteban López-Camacho -// +// // Copyright (c) 2011 Antonio J. Nebro, Juan J. Durillo // // This program is free software: you can redistribute it and/or modify @@ -14,7 +14,7 @@ // but WITHOUT ANY WARRANTY; without even the implied warranty of // MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the // GNU Lesser General Public License for more details. -// +// // You should have received a copy of the GNU Lesser General Public License // along with this program. If not, see . @@ -28,47 +28,53 @@ * @param solutionType The solution type must "Real", "BinaryReal, and "ArrayReal". * @param numberOfVariables Number of variables of the problem */ -Griewank::Griewank(string solutionType, int numberOfVariables) { - numberOfVariables_ = numberOfVariables; - numberOfObjectives_ = 1; - numberOfConstraints_ = 0; - problemName_ = "Griewank"; - - lowerLimit_ = new double[numberOfVariables_]; - if (lowerLimit_ == NULL) { - cout << "Griewank::Griewank. Error reserving memory for storing the array of lower limits" << endl; - exit(-1) ; - } // if - - upperLimit_ = new double[numberOfVariables_]; - if (upperLimit_ == NULL) { - cout << "Griewank::Griewank. Error reserving memory for storing the array of upper limits" << endl; - exit(-1) ; - } // if - - for (int i = 0; i < numberOfVariables_; i++) { - lowerLimit_[i] = -600.0; - upperLimit_[i] = 600.0; - } // for - - if (solutionType.compare("BinaryReal") == 0) - solutionType_ = new BinaryRealSolutionType(this) ; - else if (solutionType.compare("Real") == 0) - solutionType_ = new RealSolutionType(this) ; - else { - cout << "Error: solution type " << solutionType << " invalid" << endl; - exit(-1) ; - } // if +Griewank::Griewank(std::string solutionType, int numberOfVariables) +{ + numberOfVariables_ = numberOfVariables; + numberOfObjectives_ = 1; + numberOfConstraints_ = 0; + problemName_ = "Griewank"; + + lowerLimit_ = snew double[numberOfVariables_]; + if (lowerLimit_ == nullptr) + { + std::cout << "Griewank::Griewank. Error reserving memory for storing the array of lower limits" << std::endl; + exit(-1) ; + } // if + + upperLimit_ = snew double[numberOfVariables_]; + if (upperLimit_ == nullptr) + { + std::cout << "Griewank::Griewank. Error reserving memory for storing the array of upper limits" << std::endl; + exit(-1) ; + } // if + + for (int i = 0; i < numberOfVariables_; i++) + { + lowerLimit_[i] = -600.0; + upperLimit_[i] = 600.0; + } // for + + if (solutionType.compare("BinaryReal") == 0) + solutionType_ = snew BinaryRealSolutionType(this) ; + else if (solutionType.compare("Real") == 0) + solutionType_ = snew RealSolutionType(this) ; + else + { + std::cout << "Error: solution type " << solutionType << " invalid" << std::endl; + exit(-1) ; + } // if } // Griewank /** * Destructor */ -Griewank::~Griewank() { - delete [] lowerLimit_ ; - delete [] upperLimit_ ; - delete solutionType_ ; +Griewank::~Griewank() +{ + delete [] lowerLimit_ ; + delete [] upperLimit_ ; + delete solutionType_ ; } // ~Griewank @@ -76,19 +82,21 @@ Griewank::~Griewank() { * Evaluates a solution * @param solution The solution to evaluate */ -void Griewank::evaluate(Solution *solution) { - Variable **decisionVariables = solution->getDecisionVariables(); - - double sum = 0.0 ; - double mult = 1.0 ; - double d = 4000.0 ; - - for (int var = 0; var < numberOfVariables_; var++) { - sum += decisionVariables[var]->getValue() * - decisionVariables[var]->getValue() ; - mult *= cos(decisionVariables[var]->getValue()/sqrt(var+1)) ; - } - - solution->setObjective(0, 1.0/d * sum - mult + 1.0) ; +void Griewank::evaluate(Solution *solution) +{ + Variable **decisionVariables = solution->getDecisionVariables(); + + double sum = 0.0 ; + double mult = 1.0 ; + double d = 4000.0 ; + + for (int var = 0; var < numberOfVariables_; var++) + { + sum += decisionVariables[var]->getValue() * + decisionVariables[var]->getValue() ; + mult *= cos(decisionVariables[var]->getValue()/sqrt(var+1)) ; + } + + solution->setObjective(0, 1.0/d * sum - mult + 1.0) ; } // evaluate diff --git a/src/problems/singleObjective/Griewank.h b/src/problems/singleObjective/Griewank.h index 653fdd9..824a5ab 100644 --- a/src/problems/singleObjective/Griewank.h +++ b/src/problems/singleObjective/Griewank.h @@ -2,7 +2,7 @@ // // Authors: // Esteban López-Camacho -// +// // Copyright (c) 2011 Antonio J. Nebro, Juan J. Durillo // // This program is free software: you can redistribute it and/or modify @@ -14,7 +14,7 @@ // but WITHOUT ANY WARRANTY; without even the implied warranty of // MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the // GNU Lesser General Public License for more details. -// +// // You should have received a copy of the GNU Lesser General Public License // along with this program. If not, see . @@ -31,12 +31,13 @@ * @class Griewank * @brief Class representing problem Griewank **/ -class Griewank : public Problem { - +class Griewank : public Problem +{ + public: - Griewank(string solutionType, int numberOfVariables = 10); - ~Griewank(); - void evaluate(Solution *solution); + Griewank(std::string solutionType, int numberOfVariables = 10); + ~Griewank(); + void evaluate(Solution *solution); }; #endif /* __GRIEWANK__ */ diff --git a/src/problems/singleObjective/OneMax.cpp b/src/problems/singleObjective/OneMax.cpp index 9c847e0..39b01b0 100644 --- a/src/problems/singleObjective/OneMax.cpp +++ b/src/problems/singleObjective/OneMax.cpp @@ -23,44 +23,48 @@ /** * Class constructor */ -OneMax::OneMax(int numberOfBits, int numberOfStrings) { - numberOfVariables_ = numberOfStrings; - numberOfObjectives_ = 1; - numberOfConstraints_ = 0; - problemName_ = "OneMax"; +OneMax::OneMax(int numberOfBits, int numberOfStrings) +{ + numberOfVariables_ = numberOfStrings; + numberOfObjectives_ = 1; + numberOfConstraints_ = 0; + problemName_ = "OneMax"; - solutionType_ = new BinarySolutionType(this) ; - length_ = new int[numberOfVariables_]; - for (int i = 0; i < numberOfVariables_; i++) - length_ [i] = numberOfBits ; + solutionType_ = new BinarySolutionType(this) ; + length_ = snew int[numberOfVariables_]; + for (int i = 0; i < numberOfVariables_; i++) + length_ [i] = numberOfBits ; } // OneMax -OneMax::~OneMax() { - delete []length_ ; - delete solutionType_; +OneMax::~OneMax() +{ + delete []length_ ; + delete solutionType_; } // ~OneMax - /** - * Evaluates a solution - * @param solution The solution to evaluate - */ -void OneMax::evaluate(Solution * solution) { - Binary * variable ; - int counter ; +/** + * Evaluates a solution + * @param solution The solution to evaluate + */ +void OneMax::evaluate(Solution * solution) +{ + Binary * variable ; + int counter ; - counter = 0 ; - for (int i = 0; i < numberOfVariables_ ; i++) { - variable = (Binary *)(solution->getDecisionVariables()[i]) ; - counter += variable->cardinality() ; - } - /* - variable = (Binary *)(solution->getDecisionVariables()[0]) ; - counter = 0 ; + counter = 0 ; + for (int i = 0; i < numberOfVariables_ ; i++) + { + variable = (Binary *)(solution->getDecisionVariables()[i]) ; + counter += variable->cardinality() ; + } + /* + variable = (Binary *)(solution->getDecisionVariables()[0]) ; + counter = 0 ; - for (int i = 0; i < variable->getNumberOfBits() ; i++) - if (variable->getIth(i) == true) - counter ++ ; - */ + for (int i = 0; i < variable->getNumberOfBits() ; i++) + if (variable->getIth(i) == true) + counter ++ ; + */ // OneMax is a maximization problem: multiply by -1 to minimize solution->setObjective(0, - 1.0*counter); } // evaluate diff --git a/src/problems/singleObjective/OneMax.h b/src/problems/singleObjective/OneMax.h index 3a0092e..49382fc 100644 --- a/src/problems/singleObjective/OneMax.h +++ b/src/problems/singleObjective/OneMax.h @@ -25,11 +25,12 @@ #include #include -class OneMax : public Problem { +class OneMax : public Problem +{ public: - OneMax(int numberOfBits, int numberOfStrings = 1); - ~OneMax(); - void evaluate(Solution *solution); + OneMax(int numberOfBits, int numberOfStrings = 1); + ~OneMax(); + void evaluate(Solution *solution); }; diff --git a/src/problems/singleObjective/Rastrigin.cpp b/src/problems/singleObjective/Rastrigin.cpp index 3987dd6..343b97c 100644 --- a/src/problems/singleObjective/Rastrigin.cpp +++ b/src/problems/singleObjective/Rastrigin.cpp @@ -3,7 +3,7 @@ // Authors: // Antonio J. Nebro // Esteban López-Camacho -// +// // Copyright (c) 2011 Antonio J. Nebro, Juan J. Durillo // // This program is free software: you can redistribute it and/or modify @@ -15,7 +15,7 @@ // but WITHOUT ANY WARRANTY; without even the implied warranty of // MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the // GNU Lesser General Public License for more details. -// +// // You should have received a copy of the GNU Lesser General Public License // along with this program. If not, see . @@ -29,41 +29,46 @@ const double Rastrigin::PI = 3.141592653589793; * @param solutionType The solution type must "Real", "BinaryReal, and "ArrayReal". * @param numberOfVariables Number of variables of the problem */ -Rastrigin::Rastrigin(string solutionType, int numberOfVariables) { - numberOfVariables_ = numberOfVariables; - numberOfObjectives_ = 1; - numberOfConstraints_ = 0; - problemName_ = "Rastrigin"; - - lowerLimit_ = new double[numberOfVariables_]; - if (lowerLimit_ == NULL) { - cout << "Rastrigin::Rastrigin. Error reserving memory for storing the array of lower limits" << endl; - exit(-1) ; - } - - upperLimit_ = new double[numberOfVariables_]; - if (upperLimit_ == NULL) { - cout << "Rastrigin::Rastrigin. Error reserving memory for storing the array of upper limits" << endl; - exit(-1) ; - } - - for (int i = 0; i < numberOfVariables_; i++) { - lowerLimit_[i] = -5.12; - upperLimit_[i] = 5.12; - } - - // TODO: Solution type initialization - solutionType_ = new RealSolutionType(this); +Rastrigin::Rastrigin(std::string solutionType, int numberOfVariables) +{ + numberOfVariables_ = numberOfVariables; + numberOfObjectives_ = 1; + numberOfConstraints_ = 0; + problemName_ = "Rastrigin"; + + lowerLimit_ = snew double[numberOfVariables_]; + if (lowerLimit_ == nullptr) + { + std::cout << "Rastrigin::Rastrigin. Error reserving memory for storing the array of lower limits" << std::endl; + exit(-1) ; + } + + upperLimit_ = snew double[numberOfVariables_]; + if (upperLimit_ == nullptr) + { + std::cout << "Rastrigin::Rastrigin. Error reserving memory for storing the array of upper limits" << std::endl; + exit(-1) ; + } + + for (int i = 0; i < numberOfVariables_; i++) + { + lowerLimit_[i] = -5.12; + upperLimit_[i] = 5.12; + } + + // TODO: Solution type initialization + solutionType_ = new RealSolutionType(this); } // Rastrigin /** * Destructor */ -Rastrigin::~Rastrigin() { - delete [] lowerLimit_ ; - delete [] upperLimit_ ; - delete solutionType_ ; +Rastrigin::~Rastrigin() +{ + delete [] lowerLimit_ ; + delete [] upperLimit_ ; + delete solutionType_ ; } // ~Rastrigin @@ -71,39 +76,43 @@ Rastrigin::~Rastrigin() { * Evaluates a solution * @param solution The solution to evaluate */ -void Rastrigin::evaluate(Solution *solution) { - //double fx [numberOfObjectives_] ; - //double x [numberOfVariables_]; - Variable **variables = solution->getDecisionVariables(); - - double * fx = new double[numberOfObjectives_]; //(double *)malloc(sizeof(double) * numberOfObjectives_); - if (fx == NULL) { - cout << "Rastrigin::evaluate: Error reserving memory while evaluating the problem" << endl; +void Rastrigin::evaluate(Solution *solution) +{ + //double fx [numberOfObjectives_] ; + //double x [numberOfVariables_]; + Variable **variables = solution->getDecisionVariables(); + + double * fx = snew double[numberOfObjectives_]; //(double *)malloc(sizeof(double) * numberOfObjectives_); + if (fx == nullptr) + { + std::cout << "Rastrigin::evaluate: Error reserving memory while evaluating the problem" << std::endl; exit(-1); - } - - double * x = new double[numberOfVariables_]; - if (x == NULL) { - cout << "Rastrigin::evaluate: Error reserving memory for the variable values array" << endl; - exit(-1); - } // if - - for (int i = 0; i < numberOfVariables_; i++) - x[i] = variables[i]->getValue() ; - - // First function - double result = 0.0 ; - double a = 10.0 ; - double w = 2*PI ; - - for (int i = 0; i < numberOfVariables_; i++) { - result += x[i]*x[i] - a*cos(w*x[i]) ; - } - - fx[0] = a*numberOfVariables_ + result ; - - solution->setObjective(0,fx[0]); - delete[]fx ; - delete[]x; + } + + double * x = snew double[numberOfVariables_]; + if (x == nullptr) + { + std::cout << "Rastrigin::evaluate: Error reserving memory for the variable values array" << std::endl; + exit(-1); + } // if + + for (int i = 0; i < numberOfVariables_; i++) + x[i] = variables[i]->getValue() ; + + // First function + double result = 0.0 ; + double a = 10.0 ; + double w = 2*PI ; + + for (int i = 0; i < numberOfVariables_; i++) + { + result += x[i]*x[i] - a*cos(w*x[i]) ; + } + + fx[0] = a*numberOfVariables_ + result ; + + solution->setObjective(0,fx[0]); + delete[]fx ; + delete[]x; } // evaluate diff --git a/src/problems/singleObjective/Rastrigin.h b/src/problems/singleObjective/Rastrigin.h index 4fc6c22..2fea952 100644 --- a/src/problems/singleObjective/Rastrigin.h +++ b/src/problems/singleObjective/Rastrigin.h @@ -3,7 +3,7 @@ // Authors: // Antonio J. Nebro // Esteban López-Camacho -// +// // Copyright (c) 2011 Antonio J. Nebro, Juan J. Durillo // // This program is free software: you can redistribute it and/or modify @@ -15,7 +15,7 @@ // but WITHOUT ANY WARRANTY; without even the implied warranty of // MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the // GNU Lesser General Public License for more details. -// +// // You should have received a copy of the GNU Lesser General Public License // along with this program. If not, see . @@ -31,16 +31,17 @@ * @class Rastrigin * @brief Class representing problem Rastrigin **/ -class Rastrigin : public Problem { - +class Rastrigin : public Problem +{ + public: - Rastrigin(string solutionType, int numberOfVariables = 10); - ~Rastrigin(); - void evaluate(Solution *solution); - + Rastrigin(std::string solutionType, int numberOfVariables = 10); + ~Rastrigin(); + void evaluate(Solution *solution); + private: - static const double PI; - + static const double PI; + }; #endif /* __RASTRIGIN__ */ diff --git a/src/problems/singleObjective/Rosenbrock.cpp b/src/problems/singleObjective/Rosenbrock.cpp index dabbfe9..4bc8b11 100644 --- a/src/problems/singleObjective/Rosenbrock.cpp +++ b/src/problems/singleObjective/Rosenbrock.cpp @@ -3,7 +3,7 @@ // Authors: // Antonio J. Nebro // Esteban López-Camacho -// +// // Copyright (c) 2011 Antonio J. Nebro, Juan J. Durillo // // This program is free software: you can redistribute it and/or modify @@ -15,7 +15,7 @@ // but WITHOUT ANY WARRANTY; without even the implied warranty of // MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the // GNU Lesser General Public License for more details. -// +// // You should have received a copy of the GNU Lesser General Public License // along with this program. If not, see . @@ -27,42 +27,47 @@ * @param solutionType The solution type must "Real", "BinaryReal, and "ArrayReal". * @param numberOfVariables Number of variables of the problem */ -Rosenbrock::Rosenbrock(string solutionType, int numberOfVariables) { - numberOfVariables_ = numberOfVariables; - numberOfObjectives_ = 1; - numberOfConstraints_ = 0; - problemName_ = "Rosenbrock"; - - lowerLimit_ = new double[numberOfVariables_]; - if (lowerLimit_ == NULL) { - cout << "Rosenbrock::Rosenbrock. Error reserving memory for storing the array of lower limits" << endl; - exit(-1) ; - } - - upperLimit_ = new double[numberOfVariables_]; - if (upperLimit_ == NULL) { - cout << "Rosenbrock::Rosenbrock. Error reserving memory for storing the array of upper limits" << endl; - exit(-1) ; - } - - int i ; - for (i = 0; i < numberOfVariables_; i++) { - lowerLimit_[i] = -5.12; - upperLimit_[i] = 5.12; +Rosenbrock::Rosenbrock(std::string solutionType, int numberOfVariables) +{ + numberOfVariables_ = numberOfVariables; + numberOfObjectives_ = 1; + numberOfConstraints_ = 0; + problemName_ = "Rosenbrock"; + + lowerLimit_ = snew double[numberOfVariables_]; + if (lowerLimit_ == nullptr) + { + std::cout << "Rosenbrock::Rosenbrock. Error reserving memory for storing the array of lower limits" << std::endl; + exit(-1) ; + } + + upperLimit_ = snew double[numberOfVariables_]; + if (upperLimit_ == nullptr) + { + std::cout << "Rosenbrock::Rosenbrock. Error reserving memory for storing the array of upper limits" << std::endl; + exit(-1) ; + } + + int i ; + for (i = 0; i < numberOfVariables_; i++) + { + lowerLimit_[i] = -5.12; + upperLimit_[i] = 5.12; } // TODO: Solution type initialization - solutionType_ = new RealSolutionType(this); + solutionType_ = new RealSolutionType(this); } // Rosenbrock /** * Destructor */ -Rosenbrock::~Rosenbrock() { - delete [] lowerLimit_ ; - delete [] upperLimit_ ; - delete solutionType_ ; +Rosenbrock::~Rosenbrock() +{ + delete [] lowerLimit_ ; + delete [] upperLimit_ ; + delete solutionType_ ; } // ~Rosenbrock @@ -70,35 +75,39 @@ Rosenbrock::~Rosenbrock() { * Evaluates a solution * @param solution The solution to evaluate */ -void Rosenbrock::evaluate(Solution *solution) { - //double fx [numberOfObjectives_] ; - //double x [numberOfVariables_]; - Variable **variables = solution->getDecisionVariables(); - - double * fx = new double[numberOfObjectives_]; //(double *)malloc(sizeof(double) * numberOfObjectives_); - if (fx == NULL) { - cout << "Rosenbrock::evaluate: Error reserving memory while evaluating the problem" << endl; +void Rosenbrock::evaluate(Solution *solution) +{ + //double fx [numberOfObjectives_] ; + //double x [numberOfVariables_]; + Variable **variables = solution->getDecisionVariables(); + + double * fx = snew double[numberOfObjectives_]; //(double *)malloc(sizeof(double) * numberOfObjectives_); + if (fx == nullptr) + { + std::cout << "Rosenbrock::evaluate: Error reserving memory while evaluating the problem" << std::endl; exit(-1); - } - - double * x = new double[numberOfVariables_]; - if (x == NULL) { - cout << "Rosenbrock::evaluate: Error reserving memory for the variable values array" << endl; - exit(-1); - } // if - - for (int i = 0; i < numberOfVariables_; i++) - x[i] = variables[i]->getValue() ; - - double sum = 0.0; - for (int var = 0; var < numberOfVariables_-1; var++) { - sum += 100.0 * (x[var+1]-x[var]*x[var])*(x[var+1]-x[var]*x[var]) +(x[var]-1)*(x[var]-1) ; - } - - fx[0] = sum ; - - solution->setObjective(0,fx[0]); - delete[]fx ; - delete[]x; + } + + double * x = snew double[numberOfVariables_]; + if (x == nullptr) + { + std::cout << "Rosenbrock::evaluate: Error reserving memory for the variable values array" << std::endl; + exit(-1); + } // if + + for (int i = 0; i < numberOfVariables_; i++) + x[i] = variables[i]->getValue() ; + + double sum = 0.0; + for (int var = 0; var < numberOfVariables_-1; var++) + { + sum += 100.0 * (x[var+1]-x[var]*x[var])*(x[var+1]-x[var]*x[var]) +(x[var]-1)*(x[var]-1) ; + } + + fx[0] = sum ; + + solution->setObjective(0,fx[0]); + delete[]fx ; + delete[]x; } // evaluate diff --git a/src/problems/singleObjective/Rosenbrock.h b/src/problems/singleObjective/Rosenbrock.h index 0ad35dd..a18d4a7 100644 --- a/src/problems/singleObjective/Rosenbrock.h +++ b/src/problems/singleObjective/Rosenbrock.h @@ -3,7 +3,7 @@ // Authors: // Antonio J. Nebro // Esteban López-Camacho -// +// // Copyright (c) 2011 Antonio J. Nebro, Juan J. Durillo // // This program is free software: you can redistribute it and/or modify @@ -15,7 +15,7 @@ // but WITHOUT ANY WARRANTY; without even the implied warranty of // MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the // GNU Lesser General Public License for more details. -// +// // You should have received a copy of the GNU Lesser General Public License // along with this program. If not, see . @@ -30,12 +30,13 @@ * @class Rosenbrock * @brief Class representing problem Rosenbrock **/ -class Rosenbrock : public Problem { - +class Rosenbrock : public Problem +{ + public: - Rosenbrock(string solutionType, int numberOfVariables = 10); - ~Rosenbrock(); - void evaluate(Solution *solution); + Rosenbrock(std::string solutionType, int numberOfVariables = 10); + ~Rosenbrock(); + void evaluate(Solution *solution); }; #endif diff --git a/src/problems/singleObjective/Sphere.cpp b/src/problems/singleObjective/Sphere.cpp index 5dc22f6..9ba7032 100644 --- a/src/problems/singleObjective/Sphere.cpp +++ b/src/problems/singleObjective/Sphere.cpp @@ -3,7 +3,7 @@ // Authors: // Antonio J. Nebro // Juan J. Durillo -// +// // Copyright (c) 2011 Antonio J. Nebro, Juan J. Durillo // // This program is free software: you can redistribute it and/or modify @@ -15,7 +15,7 @@ // but WITHOUT ANY WARRANTY; without even the implied warranty of // MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the // GNU Lesser General Public License for more details. -// +// // You should have received a copy of the GNU Lesser General Public License // along with this program. If not, see . @@ -27,42 +27,47 @@ * @param solutionType The solution type must "Real", "BinaryReal, and "ArrayReal". * @param numberOfVariables Number of variables of the problem */ -Sphere::Sphere(string solutionType, int numberOfVariables) { - numberOfVariables_ = numberOfVariables; - numberOfObjectives_ = 1; - numberOfConstraints_ = 0; - problemName_ = "Sphere"; - - lowerLimit_ = new double[numberOfVariables_]; - if (lowerLimit_ == NULL) { - cout << "Sphere::Sphere. Error reserving memory for storing the array of lower limits" << endl; - exit(-1) ; - } - - upperLimit_ = new double[numberOfVariables_]; - if (upperLimit_ == NULL) { - cout << "Sphere::Sphere. Error reserving memory for storing the array of upper limits" << endl; - exit(-1) ; - } - - int i ; - for (i = 0; i < numberOfVariables_; i++) { - lowerLimit_[i] = -5.12; - upperLimit_[i] = 5.12; +Sphere::Sphere(std::string solutionType, int numberOfVariables) +{ + numberOfVariables_ = numberOfVariables; + numberOfObjectives_ = 1; + numberOfConstraints_ = 0; + problemName_ = "Sphere"; + + lowerLimit_ = snew double[numberOfVariables_]; + if (lowerLimit_ == nullptr) + { + std::cout << "Sphere::Sphere. Error reserving memory for storing the array of lower limits" << std::endl; + exit(-1) ; + } + + upperLimit_ = snew double[numberOfVariables_]; + if (upperLimit_ == nullptr) + { + std::cout << "Sphere::Sphere. Error reserving memory for storing the array of upper limits" << std::endl; + exit(-1) ; + } + + int i ; + for (i = 0; i < numberOfVariables_; i++) + { + lowerLimit_[i] = -5.12; + upperLimit_[i] = 5.12; } // TODO: Solution type initialization - solutionType_ = new RealSolutionType(this); + solutionType_ = new RealSolutionType(this); } // Sphere /** * Destructor */ -Sphere::~Sphere() { - delete [] lowerLimit_ ; - delete [] upperLimit_ ; - delete solutionType_ ; +Sphere::~Sphere() +{ + delete [] lowerLimit_ ; + delete [] upperLimit_ ; + delete solutionType_ ; } // ~Sphere @@ -70,37 +75,41 @@ Sphere::~Sphere() { * Evaluates a solution * @param solution The solution to evaluate */ -void Sphere::evaluate(Solution *solution) { - //double fx [numberOfObjectives_] ; - //double x [numberOfVariables_]; - Variable **variables = solution->getDecisionVariables(); - - double * fx = new double[numberOfObjectives_]; //(double *)malloc(sizeof(double) * numberOfObjectives_); - if (fx == NULL) { - cout << "Sphere::evaluate: Error reserving memory while evaluating the problem" << endl; +void Sphere::evaluate(Solution *solution) +{ + //double fx [numberOfObjectives_] ; + //double x [numberOfVariables_]; + Variable **variables = solution->getDecisionVariables(); + + double * fx = snew double[numberOfObjectives_]; //(double *)malloc(sizeof(double) * numberOfObjectives_); + if (fx == nullptr) + { + std::cout << "Sphere::evaluate: Error reserving memory while evaluating the problem" << std::endl; exit(-1); - } - - double * x = new double[numberOfVariables_]; - if (x == NULL) { - cout << "Sphere::evaluate: Error reserving memory for the variable values array" << endl; - exit(-1); - } // if - - for (int i = 0; i < numberOfVariables_; i++) - x[i] = variables[i]->getValue() ; - - double sum = 0.0; - for (int var = 0; var < numberOfVariables_; var++) { - sum += pow(x[var], 2.0); - } - - - fx[0] = sum ; - - solution->setObjective(0,fx[0]); - delete[]fx ; - delete[]x; + } + + double * x = snew double[numberOfVariables_]; + if (x == nullptr) + { + std::cout << "Sphere::evaluate: Error reserving memory for the variable values array" << std::endl; + exit(-1); + } // if + + for (int i = 0; i < numberOfVariables_; i++) + x[i] = variables[i]->getValue() ; + + double sum = 0.0; + for (int var = 0; var < numberOfVariables_; var++) + { + sum += pow(x[var], 2.0); + } + + + fx[0] = sum ; + + solution->setObjective(0,fx[0]); + delete[]fx ; + delete[]x; } // evaluate diff --git a/src/problems/singleObjective/Sphere.h b/src/problems/singleObjective/Sphere.h index 04ebec3..a77f8b1 100644 --- a/src/problems/singleObjective/Sphere.h +++ b/src/problems/singleObjective/Sphere.h @@ -3,7 +3,7 @@ // Authors: // Antonio J. Nebro // Juan J. Durillo -// +// // Copyright (c) 2011 Antonio J. Nebro, Juan J. Durillo // // This program is free software: you can redistribute it and/or modify @@ -15,7 +15,7 @@ // but WITHOUT ANY WARRANTY; without even the implied warranty of // MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the // GNU Lesser General Public License for more details. -// +// // You should have received a copy of the GNU Lesser General Public License // along with this program. If not, see . @@ -31,12 +31,13 @@ * @class Sphere * @brief Class representing problem Sphere **/ -class Sphere : public Problem { - +class Sphere : public Problem +{ + public: - Sphere(string solutionType, int numberOfVariables = 10); - ~Sphere(); - void evaluate(Solution *solution); + Sphere(string solutionType, int numberOfVariables = 10); + ~Sphere(); + void evaluate(Solution *solution); }; #endif diff --git a/src/problems/singleObjective/cec2005Competition/Benchmark.cpp b/src/problems/singleObjective/cec2005Competition/Benchmark.cpp index 5723ec9..c0e91d8 100644 --- a/src/problems/singleObjective/cec2005Competition/Benchmark.cpp +++ b/src/problems/singleObjective/cec2005Competition/Benchmark.cpp @@ -22,8 +22,8 @@ #include //TODO: Cambiar ruta -//const string Benchmark::DEFAULT_FILE_BIAS = Configuration.cec2005SupportDataDirectory + "/fbias_data.txt"; -const string Benchmark::DEFAULT_FILE_BIAS = "../../data/cec2005CompetitionResources/supportData/fbias_data.txt"; +//const std::string Benchmark::DEFAULT_FILE_BIAS = Configuration.cec2005SupportDataDirectory + "/fbias_data.txt"; +const std::string Benchmark::DEFAULT_FILE_BIAS = "../../data/cec2005CompetitionResources/supportData/fbias_data.txt"; const int Benchmark::NUM_TEST_FUNC = 25; @@ -42,16 +42,18 @@ Benchmark::Benchmark() : Benchmark(DEFAULT_FILE_BIAS) {} /* * Constructor */ -Benchmark::Benchmark(string file_bias) { - m_biases = new double[NUM_TEST_FUNC]; - loadRowVectorFromFile(file_bias, NUM_TEST_FUNC, m_biases); +Benchmark::Benchmark(std::string file_bias) +{ + m_biases = snew double[NUM_TEST_FUNC]; + loadRowVectorFromFile(file_bias, NUM_TEST_FUNC, m_biases); } /* * Destructor */ -Benchmark::~Benchmark() { - delete [] m_biases; +Benchmark::~Benchmark() +{ + delete [] m_biases; } /** @@ -64,485 +66,562 @@ normal_distribution Benchmark::dist (0,1); /** * Use this function to manufacture new test function objects. */ -TestFunc * Benchmark::testFunctionFactory(int func_num, int dimension) { - switch (func_num) { +TestFunc * Benchmark::testFunctionFactory(int func_num, int dimension) +{ + switch (func_num) + { case 1: - return new F01ShiftedSphere(dimension, m_biases[func_num-1]); - break; + return snew F01ShiftedSphere(dimension, m_biases[func_num-1]); + break; case 2: - return new F02ShiftedSchwefel(dimension, m_biases[func_num-1]); - break; + return snew F02ShiftedSchwefel(dimension, m_biases[func_num-1]); + break; case 3: - return new F03ShiftedRotatedHighCondElliptic(dimension, m_biases[func_num-1]); - break; + return snew F03ShiftedRotatedHighCondElliptic(dimension, m_biases[func_num-1]); + break; case 4: - return new F04ShiftedSchwefelNoise(dimension, m_biases[func_num-1]); - break; + return snew F04ShiftedSchwefelNoise(dimension, m_biases[func_num-1]); + break; case 5: - return new F05SchwefelGlobalOptBound(dimension, m_biases[func_num-1]); - break; + return snew F05SchwefelGlobalOptBound(dimension, m_biases[func_num-1]); + break; case 6: - return new F06ShiftedRosenbrock(dimension, m_biases[func_num-1]); - break; + return snew F06ShiftedRosenbrock(dimension, m_biases[func_num-1]); + break; case 7: - return new F07ShiftedRotatedGriewank(dimension, m_biases[func_num-1]); - break; + return snew F07ShiftedRotatedGriewank(dimension, m_biases[func_num-1]); + break; case 8: - return new F08ShiftedRotatedAckleyGlobalOptBound(dimension, m_biases[func_num-1]); - break; + return snew F08ShiftedRotatedAckleyGlobalOptBound(dimension, m_biases[func_num-1]); + break; case 9: - return new F09ShiftedRastrigin(dimension, m_biases[func_num-1]); - break; + return snew F09ShiftedRastrigin(dimension, m_biases[func_num-1]); + break; case 10: - return new F10ShiftedRotatedRastrigin(dimension, m_biases[func_num-1]); - break; + return snew F10ShiftedRotatedRastrigin(dimension, m_biases[func_num-1]); + break; case 11: - return new F11ShiftedRotatedWeierstrass(dimension, m_biases[func_num-1]); - break; + return snew F11ShiftedRotatedWeierstrass(dimension, m_biases[func_num-1]); + break; case 12: - return new F12Schwefel(dimension, m_biases[func_num-1]); - break; + return snew F12Schwefel(dimension, m_biases[func_num-1]); + break; case 13: - return new F13ShiftedExpandedGriewankRosenbrock(dimension, m_biases[func_num-1]); - break; + return snew F13ShiftedExpandedGriewankRosenbrock(dimension, m_biases[func_num-1]); + break; case 14: - return new F14ShiftedRotatedExpandedScaffer(dimension, m_biases[func_num-1]); - break; + return snew F14ShiftedRotatedExpandedScaffer(dimension, m_biases[func_num-1]); + break; case 15: - return new F15HybridComposition1(dimension, m_biases[func_num-1]); - break; + return snew F15HybridComposition1(dimension, m_biases[func_num-1]); + break; case 16: - return new F16RotatedHybridComposition1(dimension, m_biases[func_num-1]); - break; + return snew F16RotatedHybridComposition1(dimension, m_biases[func_num-1]); + break; case 17: - return new F17RotatedHybridComposition1Noise(dimension, m_biases[func_num-1]); - break; + return snew F17RotatedHybridComposition1Noise(dimension, m_biases[func_num-1]); + break; case 18: - return new F18RotatedHybridComposition2(dimension, m_biases[func_num-1]); - break; + return snew F18RotatedHybridComposition2(dimension, m_biases[func_num-1]); + break; case 19: - return new F19RotatedHybridComposition2NarrowBasinGlobalOpt(dimension, m_biases[func_num-1]); - break; + return snew F19RotatedHybridComposition2NarrowBasinGlobalOpt(dimension, m_biases[func_num-1]); + break; case 20: - return new F20RotatedHybridComposition2GlobalOptBound(dimension, m_biases[func_num-1]); - break; + return snew F20RotatedHybridComposition2GlobalOptBound(dimension, m_biases[func_num-1]); + break; case 21: - return new F21RotatedHybridComposition3(dimension, m_biases[func_num-1]); - break; + return snew F21RotatedHybridComposition3(dimension, m_biases[func_num-1]); + break; case 22: - return new F22RotatedHybridComposition3HighCondNumMatrix(dimension, m_biases[func_num-1]); - break; + return snew F22RotatedHybridComposition3HighCondNumMatrix(dimension, m_biases[func_num-1]); + break; case 23: - return new F23NoncontinuousRotatedHybridComposition3(dimension, m_biases[func_num-1]); - break; + return snew F23NoncontinuousRotatedHybridComposition3(dimension, m_biases[func_num-1]); + break; case 24: - return new F24RotatedHybridComposition4(dimension, m_biases[func_num-1]); - break; + return snew F24RotatedHybridComposition4(dimension, m_biases[func_num-1]); + break; case 25: - return new F25RotatedHybridComposition4Bound(dimension, m_biases[func_num-1]); - break; + return snew F25RotatedHybridComposition4Bound(dimension, m_biases[func_num-1]); + break; default: - cerr << "Incorrect number of function. Expected an integer between " << - "1 and 25." << endl; - exit(-1); - } + cerr << "Incorrect number of function. Expected an integer between " << + "1 and 25." << std::endl; + exit(-1); + } } /** * Sphere function */ -double Benchmark::sphere(double * x, int length) { - double sum = 0.0; - for (int i = 0; i num_func; - int num_dim = job->num_dim; - - // Get the raw weights - double wMax = -numeric_limits::max(); - for (int i=0; iz[i], x, job->o[i], length); - for (int j=0; jz[i][j] * job->z[i][j]); +double Benchmark::hybrid_composition(double* x, HCJob* job, int length) +{ + + int num_func = job->num_func; + int num_dim = job->num_dim; + + // Get the raw weights + double wMax = -numeric_limits::max(); + for (int i=0; iz[i], x, job->o[i], length); + for (int j=0; jz[i][j] * job->z[i][j]); + } + job->w[i] = exp(-1.0 * sumSqr / (2.0 * num_dim * job->sigma[i] * job->sigma[i])); + if (wMax < job->w[i]) + wMax = job->w[i]; + } + + // Modify the weights + double wSum = 0.0; + double w1mMaxPow = 1.0 - pow(wMax, 10.0); + for (int i=0; iw[i] != wMax) + { + job->w[i] *= w1mMaxPow; + } + wSum += job->w[i]; } - job->w[i] = exp(-1.0 * sumSqr / (2.0 * num_dim * job->sigma[i] * job->sigma[i])); - if (wMax < job->w[i]) - wMax = job->w[i]; - } - - // Modify the weights - double wSum = 0.0; - double w1mMaxPow = 1.0 - pow(wMax, 10.0); - for (int i=0; iw[i] != wMax) { - job->w[i] *= w1mMaxPow; + + // Normalize the weights + for (int i=0; iw[i] /= wSum; } - wSum += job->w[i]; - } - - // Normalize the weights - for (int i=0; iw[i] /= wSum; - } - - double sumF = 0.0; - for (int i=0; iz[i][j] /= job->lambda[i]; + + double sumF = 0.0; + for (int i=0; iz[i][j] /= job->lambda[i]; + } + rotate(job->zM[i], job->z[i], job->M[i], length); + sumF += + job->w[i] * + ( + job->C * job->basic_func(i, job->zM[i], length) / job->fmax[i] + + job->biases[i] + ); } - rotate(job->zM[i], job->z[i], job->M[i], length); - sumF += - job->w[i] * - ( - job->C * job->basic_func(i, job->zM[i], length) / job->fmax[i] + - job->biases[i] - ); - } - return sumF; + return sumF; } /** * Rotate */ -void Benchmark::rotate(double * results, double * x, double ** matrix, int length) { - xA(results, x, matrix, length); +void Benchmark::rotate(double * results, double * x, double ** matrix, int length) +{ + xA(results, x, matrix, length); } /** * (1xD) row vector * (DxD) matrix = (1xD) row vector */ -void Benchmark::xA(double * result, double * x, double ** A, int length) { - for (int i = 0 ; i < length ; i ++) { - result[i] = 0.0; - for (int j = 0 ; j < length ; j ++) { - result[i] += (x[j] * A[j][i]); +void Benchmark::xA(double * result, double * x, double ** A, int length) +{ + for (int i = 0 ; i < length ; i ++) + { + result[i] = 0.0; + for (int j = 0 ; j < length ; j ++) + { + result[i] += (x[j] * A[j][i]); + } } - } } /** * (DxD) matrix * (Dx1) column vector = (Dx1) column vector */ -void Benchmark::Ax(double * result, double ** A, double * x, int length) { - for (int i = 0 ; i < length ; i++) { - result[i] = 0.0; - for (int j = 0 ; j < length ; j++) { - result[i] += (A[i][j] * x[j]); +void Benchmark::Ax(double * result, double ** A, double * x, int length) +{ + for (int i = 0 ; i < length ; i++) + { + result[i] = 0.0; + for (int j = 0 ; j < length ; j++) + { + result[i] += (A[i][j] * x[j]); + } } - } } -void Benchmark::loadRowVectorFromFile(string file, int columns, double * row) { +void Benchmark::loadRowVectorFromFile(std::string file, int columns, double * row) +{ - // Open the file - ifstream in(file.c_str()); - if( !in ) { - cerr << "Benchmark::loadRowVectorFromFile: failed when reading from file : " << - file << endl; - exit(-1); - } else { + // Open the file + ifstream in(file.c_str()); + if( !in ) + { + cerr << "Benchmark::loadRowVectorFromFile: failed when reading from file : " << + file << std::endl; + exit(-1); + } + else + { - loadRowVector(in, columns, row); - in.close(); + loadRowVector(in, columns, row); + in.close(); - } + } } -void Benchmark::loadRowVector(ifstream& in, int columns, double * row) { - string aux; - - if (getline(in, aux)) { - - istringstream iss(aux); - for (int i = 0; i < columns; i++) { - string stToken; - iss >> stToken; - if (stToken.compare("")!=0) { - row[i] = atof(stToken.c_str()); - } else { +void Benchmark::loadRowVector(ifstream& in, int columns, double * row) +{ + std::string aux; + + if (getline(in, aux)) + { + + istringstream iss(aux); + for (int i = 0; i < columns; i++) + { + std::string stToken; + iss >> stToken; + if (stToken.compare("")!=0) + { + row[i] = atof(stToken.c_str()); + } + else + { + cerr << "Benchmark::loadRowVector: unexpected format encountered when " << + "reading from file (incorrect number of tokens)." << std::endl; + exit(-1); + } + } + } + else + { cerr << "Benchmark::loadRowVector: unexpected format encountered when " << - "reading from file (incorrect number of tokens)." << endl; + "reading from file (zero lines found)." << std::endl; exit(-1); - } } - } else { - cerr << "Benchmark::loadRowVector: unexpected format encountered when " << - "reading from file (zero lines found)." << endl; - exit(-1); - } -} - -void Benchmark::loadNMatrixFromFile(string file, int N, int rows, int columns, double*** matrix) { - ifstream in(file.c_str()); - if (!in) { - cerr << "Benchmark::loadNMatrixFromFile: failed when reading from file : " << - file << endl; - exit(-1); - } else { - for (int i=0; i #include +#include "JMetalHeader.h" #include #include #include @@ -57,76 +58,78 @@ #include #include -using namespace std; -template int sgn(T val) { + +template int sgn(T val) +{ return (T(0) < val) - (val < T(0)); } -class Benchmark { +class Benchmark +{ private: - static const string DEFAULT_FILE_BIAS; + static const std::string DEFAULT_FILE_BIAS; - static const int NUM_TEST_FUNC; + static const int NUM_TEST_FUNC; - // For certain functions, some essential data can be calculated beforehand. - // Hence, a maximum supported number of dimensions should be specified. - // Specifiy the number of dimensions here if you need more. - static const int MAX_SUPPORT_DIM; - static const double PIx2; + // For certain functions, some essential data can be calculated beforehand. + // Hence, a maximum supported number of dimensions should be specified. + // Specifiy the number of dimensions here if you need more. + static const int MAX_SUPPORT_DIM; + static const double PIx2; - // Instance variables - double * m_biases; + // Instance variables + double * m_biases; public: - Benchmark(); - Benchmark(string file_bias); - ~Benchmark(); - - // Random number generator - static mt19937 e2; - static normal_distribution dist; - - TestFunc * testFunctionFactory(int func_num, int dimension); - - // Basic functions - static double sphere(double * x, int length); - static double sphere_noise(double * x, int length); - static double schwefel_102(double * x, int length); - static double rosenbrock(double * x, int length); - static double F2(double x, double y); - static double griewank(double * x, int length); - static double F8(double x); - static double ackley(double * x, int length); - static double myRound(double x); - static double myXRound(double x, double o); - static double myXRound(double x); - static double rastrigin(double * x, int length); - static double rastriginNonCont(double * x, int length); - static double weierstrass(double * x, int length); - static double weierstrass(double * x, int length, double a, double b, int Kmax); - static double F8F2(double * x, int length); - static double ScafferF6(double x, double y); - static double EScafferF6(double * x, int length); - static double EScafferF6NonCont(double * x, int length); - static double elliptic(double* x, int length); - static double hybrid_composition(double * x, HCJob * job, int length); - - // Elementary operations - static void shift(double * results, double * x, double * o, int length); - static void rotate(double * results, double * x, double ** matrix, int length); - - // Matrix & vector operations - static void xA(double * result, double * x, double ** A, int length); - static void Ax(double * result, double ** A, double * x, int length); - - // Utility functions for loading data from given text files - static void loadRowVectorFromFile(string file, int columns, double * row); - static void loadRowVector(ifstream& brSrc, int columns, double * row); - static void loadNMatrixFromFile(string file, int N, int rows, int columns, double*** matrix); - static void loadMatrixFromFile(string file, int rows, int columns, double ** matrix); - static void loadMatrix(ifstream& brSrc, int rows, int columns, double ** matrix); + Benchmark(); + Benchmark(std::string file_bias); + ~Benchmark(); + + // Random number generator + static mt19937 e2; + static normal_distribution dist; + + TestFunc * testFunctionFactory(int func_num, int dimension); + + // Basic functions + static double sphere(double * x, int length); + static double sphere_noise(double * x, int length); + static double schwefel_102(double * x, int length); + static double rosenbrock(double * x, int length); + static double F2(double x, double y); + static double griewank(double * x, int length); + static double F8(double x); + static double ackley(double * x, int length); + static double myRound(double x); + static double myXRound(double x, double o); + static double myXRound(double x); + static double rastrigin(double * x, int length); + static double rastriginNonCont(double * x, int length); + static double weierstrass(double * x, int length); + static double weierstrass(double * x, int length, double a, double b, int Kmax); + static double F8F2(double * x, int length); + static double ScafferF6(double x, double y); + static double EScafferF6(double * x, int length); + static double EScafferF6NonCont(double * x, int length); + static double elliptic(double* x, int length); + static double hybrid_composition(double * x, HCJob * job, int length); + + // Elementary operations + static void shift(double * results, double * x, double * o, int length); + static void rotate(double * results, double * x, double ** matrix, int length); + + // Matrix & vector operations + static void xA(double * result, double * x, double ** A, int length); + static void Ax(double * result, double ** A, double * x, int length); + + // Utility functions for loading data from given text files + static void loadRowVectorFromFile(std::string file, int columns, double * row); + static void loadRowVector(ifstream& brSrc, int columns, double * row); + static void loadNMatrixFromFile(std::string file, int N, int rows, int columns, double*** matrix); + static void loadMatrixFromFile(std::string file, int rows, int columns, double ** matrix); + static void loadMatrix(ifstream& brSrc, int rows, int columns, double ** matrix); }; // Benchmark diff --git a/src/problems/singleObjective/cec2005Competition/CMakeLists.txt b/src/problems/singleObjective/cec2005Competition/CMakeLists.txt new file mode 100644 index 0000000..294ec59 --- /dev/null +++ b/src/problems/singleObjective/cec2005Competition/CMakeLists.txt @@ -0,0 +1,3 @@ +file(GLOB SOURCES "*.cpp" "*.h") +ListToString(SOURCES ";" ${SOURCES}) +LIST_APPEND("${SOURCES}") \ No newline at end of file diff --git a/src/problems/singleObjective/cec2005Competition/F01ShiftedSphere.cpp b/src/problems/singleObjective/cec2005Competition/F01ShiftedSphere.cpp index c367694..af8a2d5 100644 --- a/src/problems/singleObjective/cec2005Competition/F01ShiftedSphere.cpp +++ b/src/problems/singleObjective/cec2005Competition/F01ShiftedSphere.cpp @@ -23,31 +23,33 @@ #include // Fixed (class) parameters -const string F01ShiftedSphere::FUNCTION_NAME = "Shifted Sphere Function"; +const std::string F01ShiftedSphere::FUNCTION_NAME = "Shifted Sphere Function"; // TODO: Cambiar ruta -const string F01ShiftedSphere::DEFAULT_FILE_DATA = "../../data/cec2005CompetitionResources/supportData/sphere_func_data.txt"; +const std::string F01ShiftedSphere::DEFAULT_FILE_DATA = "../../data/cec2005CompetitionResources/supportData/sphere_func_data.txt"; /** * Constructor. */ F01ShiftedSphere::F01ShiftedSphere(int dimension, double bias) - : F01ShiftedSphere(dimension, bias, DEFAULT_FILE_DATA) { + : F01ShiftedSphere(dimension, bias, DEFAULT_FILE_DATA) +{ } // F01ShiftedSphere /** * Constructor */ -F01ShiftedSphere::F01ShiftedSphere(int dimension, double bias, string file_data) - : TestFunc(dimension, bias, FUNCTION_NAME) { +F01ShiftedSphere::F01ShiftedSphere(int dimension, double bias, std::string file_data) + : TestFunc(dimension, bias, FUNCTION_NAME) +{ - // Note: dimension starts from 0 - m_o = new double[m_dimension]; - m_z = new double[m_dimension]; + // Note: dimension starts from 0 + m_o = snew double[m_dimension]; + m_z = snew double[m_dimension]; - // Load the shifted global optimum - Benchmark::loadRowVectorFromFile(file_data, m_dimension, m_o); + // Load the shifted global optimum + Benchmark::loadRowVectorFromFile(file_data, m_dimension, m_o); } // F01ShiftedSphere @@ -55,23 +57,25 @@ F01ShiftedSphere::F01ShiftedSphere(int dimension, double bias, string file_data) /** * Destructor */ -F01ShiftedSphere::~F01ShiftedSphere() { - delete [] m_o; - delete [] m_z; +F01ShiftedSphere::~F01ShiftedSphere() +{ + delete [] m_o; + delete [] m_z; } // ~F01ShiftedSphere /** * Function body */ -double F01ShiftedSphere::f(double * x) { - double result = 0.0; +double F01ShiftedSphere::f(double * x) +{ + double result = 0.0; - Benchmark::shift(m_z, x, m_o, m_dimension); + Benchmark::shift(m_z, x, m_o, m_dimension); - result = Benchmark::sphere(m_z, m_dimension); + result = Benchmark::sphere(m_z, m_dimension); - result += m_bias; + result += m_bias; - return result; + return result; } diff --git a/src/problems/singleObjective/cec2005Competition/F01ShiftedSphere.h b/src/problems/singleObjective/cec2005Competition/F01ShiftedSphere.h index f7e4777..c786db6 100644 --- a/src/problems/singleObjective/cec2005Competition/F01ShiftedSphere.h +++ b/src/problems/singleObjective/cec2005Competition/F01ShiftedSphere.h @@ -25,28 +25,29 @@ #include #include -class F01ShiftedSphere : public TestFunc { +class F01ShiftedSphere : public TestFunc +{ private: - // Fixed (class) parameters - static const string FUNCTION_NAME; - static const string DEFAULT_FILE_DATA; + // Fixed (class) parameters + static const std::string FUNCTION_NAME; + static const std::string DEFAULT_FILE_DATA; - // Shifted global optimum - double * m_o; + // Shifted global optimum + double * m_o; - // In order to avoid excessive memory allocation, - // a fixed memory buffer is allocated for each function object. - double * m_z; + // In order to avoid excessive memory allocation, + // a fixed memory buffer is allocated for each function object. + double * m_z; public: - F01ShiftedSphere(int dimension, double bias); - F01ShiftedSphere(int dimension, double bias, string file_data); - ~F01ShiftedSphere(); + F01ShiftedSphere(int dimension, double bias); + F01ShiftedSphere(int dimension, double bias, std::string file_data); + ~F01ShiftedSphere(); - double f (double * x); + double f (double * x); }; // F01ShiftedSphere diff --git a/src/problems/singleObjective/cec2005Competition/F02ShiftedSchwefel.cpp b/src/problems/singleObjective/cec2005Competition/F02ShiftedSchwefel.cpp index a7e4f80..b66ac50 100644 --- a/src/problems/singleObjective/cec2005Competition/F02ShiftedSchwefel.cpp +++ b/src/problems/singleObjective/cec2005Competition/F02ShiftedSchwefel.cpp @@ -23,31 +23,33 @@ #include // Fixed (class) parameters -const string F02ShiftedSchwefel::FUNCTION_NAME = "Shifted Schwefel's Problem 1.2"; +const std::string F02ShiftedSchwefel::FUNCTION_NAME = "Shifted Schwefel's Problem 1.2"; // TODO: Cambiar ruta -const string F02ShiftedSchwefel::DEFAULT_FILE_DATA = "../../data/cec2005CompetitionResources/supportData/schwefel_102_data.txt"; +const std::string F02ShiftedSchwefel::DEFAULT_FILE_DATA = "../../data/cec2005CompetitionResources/supportData/schwefel_102_data.txt"; /** * Constructor. */ F02ShiftedSchwefel::F02ShiftedSchwefel(int dimension, double bias) - : F02ShiftedSchwefel(dimension, bias, DEFAULT_FILE_DATA) { + : F02ShiftedSchwefel(dimension, bias, DEFAULT_FILE_DATA) +{ } // F02ShiftedSchwefel /** * Constructor */ -F02ShiftedSchwefel::F02ShiftedSchwefel(int dimension, double bias, string file_data) - : TestFunc(dimension, bias, FUNCTION_NAME) { +F02ShiftedSchwefel::F02ShiftedSchwefel(int dimension, double bias, std::string file_data) + : TestFunc(dimension, bias, FUNCTION_NAME) +{ - // Note: dimension starts from 0 - m_o = new double[m_dimension]; - m_z = new double[m_dimension]; + // Note: dimension starts from 0 + m_o = snew double[m_dimension]; + m_z = snew double[m_dimension]; - // Load the shifted global optimum - Benchmark::loadRowVectorFromFile(file_data, m_dimension, m_o); + // Load the shifted global optimum + Benchmark::loadRowVectorFromFile(file_data, m_dimension, m_o); } // F02ShiftedSchwefel @@ -55,23 +57,25 @@ F02ShiftedSchwefel::F02ShiftedSchwefel(int dimension, double bias, string file_d /** * Destructor */ -F02ShiftedSchwefel::~F02ShiftedSchwefel() { - delete [] m_o; - delete [] m_z; +F02ShiftedSchwefel::~F02ShiftedSchwefel() +{ + delete [] m_o; + delete [] m_z; } // ~F02ShiftedSchwefel /** * Function body */ -double F02ShiftedSchwefel::f(double * x) { - double result = 0.0; +double F02ShiftedSchwefel::f(double * x) +{ + double result = 0.0; - Benchmark::shift(m_z, x, m_o, m_dimension); + Benchmark::shift(m_z, x, m_o, m_dimension); - result = Benchmark::schwefel_102(m_z, m_dimension); + result = Benchmark::schwefel_102(m_z, m_dimension); - result += m_bias; + result += m_bias; - return result; + return result; } diff --git a/src/problems/singleObjective/cec2005Competition/F02ShiftedSchwefel.h b/src/problems/singleObjective/cec2005Competition/F02ShiftedSchwefel.h index 019fe18..4013e7d 100644 --- a/src/problems/singleObjective/cec2005Competition/F02ShiftedSchwefel.h +++ b/src/problems/singleObjective/cec2005Competition/F02ShiftedSchwefel.h @@ -25,28 +25,29 @@ #include #include -class F02ShiftedSchwefel : public TestFunc { +class F02ShiftedSchwefel : public TestFunc +{ private: - // Fixed (class) parameters - static const string FUNCTION_NAME; - static const string DEFAULT_FILE_DATA; + // Fixed (class) parameters + static const std::string FUNCTION_NAME; + static const std::string DEFAULT_FILE_DATA; - // Shifted global optimum - double * m_o; + // Shifted global optimum + double * m_o; - // In order to avoid excessive memory allocation, - // a fixed memory buffer is allocated for each function object. - double * m_z; + // In order to avoid excessive memory allocation, + // a fixed memory buffer is allocated for each function object. + double * m_z; public: - F02ShiftedSchwefel(int dimension, double bias); - F02ShiftedSchwefel(int dimension, double bias, string file_data); - ~F02ShiftedSchwefel(); + F02ShiftedSchwefel(int dimension, double bias); + F02ShiftedSchwefel(int dimension, double bias, std::string file_data); + ~F02ShiftedSchwefel(); - double f (double * x); + double f (double * x); }; // F02ShiftedSchwefel diff --git a/src/problems/singleObjective/cec2005Competition/F03ShiftedRotatedHighCondElliptic.cpp b/src/problems/singleObjective/cec2005Competition/F03ShiftedRotatedHighCondElliptic.cpp index d8ca2e9..abb4b7c 100644 --- a/src/problems/singleObjective/cec2005Competition/F03ShiftedRotatedHighCondElliptic.cpp +++ b/src/problems/singleObjective/cec2005Competition/F03ShiftedRotatedHighCondElliptic.cpp @@ -21,44 +21,48 @@ #include +#include "JMetalHeader.h" // Fixed (class) parameters -const string F03ShiftedRotatedHighCondElliptic::FUNCTION_NAME = "Shifted Rotated High Conditioned Elliptic Function"; +const std::string F03ShiftedRotatedHighCondElliptic::FUNCTION_NAME = "Shifted Rotated High Conditioned Elliptic Function"; // TODO: Cambiar ruta -const string F03ShiftedRotatedHighCondElliptic::DEFAULT_FILE_DATA = "../../data/cec2005CompetitionResources/supportData/high_cond_elliptic_rot_data.txt"; -const string F03ShiftedRotatedHighCondElliptic::DEFAULT_FILE_MX_PREFIX = "../../data/cec2005CompetitionResources/supportData/Elliptic_M_D"; -const string F03ShiftedRotatedHighCondElliptic::DEFAULT_FILE_MX_SUFFIX = ".txt"; +const std::string F03ShiftedRotatedHighCondElliptic::DEFAULT_FILE_DATA = "../../data/cec2005CompetitionResources/supportData/high_cond_elliptic_rot_data.txt"; +const std::string F03ShiftedRotatedHighCondElliptic::DEFAULT_FILE_MX_PREFIX = "../../data/cec2005CompetitionResources/supportData/Elliptic_M_D"; +const std::string F03ShiftedRotatedHighCondElliptic::DEFAULT_FILE_MX_SUFFIX = ".txt"; /** * Constructor. */ F03ShiftedRotatedHighCondElliptic::F03ShiftedRotatedHighCondElliptic(int dimension, double bias) - : F03ShiftedRotatedHighCondElliptic(dimension, bias, DEFAULT_FILE_DATA, getFileMxName(DEFAULT_FILE_MX_PREFIX, dimension, DEFAULT_FILE_MX_SUFFIX)) { + : F03ShiftedRotatedHighCondElliptic(dimension, bias, DEFAULT_FILE_DATA, getFileMxName(DEFAULT_FILE_MX_PREFIX, dimension, DEFAULT_FILE_MX_SUFFIX)) +{ } // F03ShiftedRotatedHighCondElliptic /** * Constructor */ -F03ShiftedRotatedHighCondElliptic::F03ShiftedRotatedHighCondElliptic(int dimension, double bias, string file_data, string file_m) - : TestFunc(dimension, bias, FUNCTION_NAME) { - - // Note: dimension starts from 0 - m_o = new double[m_dimension]; - m_matrix = new double*[m_dimension]; - for (int i=0; i #include -class F03ShiftedRotatedHighCondElliptic : public TestFunc { +class F03ShiftedRotatedHighCondElliptic : public TestFunc +{ private: - // Fixed (class) parameters - static const string FUNCTION_NAME; - static const string DEFAULT_FILE_DATA; - static const string DEFAULT_FILE_MX_PREFIX; - static const string DEFAULT_FILE_MX_SUFFIX; + // Fixed (class) parameters + static const std::string FUNCTION_NAME; + static const std::string DEFAULT_FILE_DATA; + static const std::string DEFAULT_FILE_MX_PREFIX; + static const std::string DEFAULT_FILE_MX_SUFFIX; - // Shifted global optimum - double * m_o; - double ** m_matrix; + // Shifted global optimum + double * m_o; + double ** m_matrix; - // In order to avoid excessive memory allocation, - // a fixed memory buffer is allocated for each function object. - double * m_z; - double * m_zM; + // In order to avoid excessive memory allocation, + // a fixed memory buffer is allocated for each function object. + double * m_z; + double * m_zM; - double constant; + double constant; - string getFileMxName(string prefix, int dimension, string suffix); + std::string getFileMxName(std::string prefix, int dimension, std::string suffix); public: - F03ShiftedRotatedHighCondElliptic(int dimension, double bias); - F03ShiftedRotatedHighCondElliptic(int dimension, double bias, string file_data, string file_m); - ~F03ShiftedRotatedHighCondElliptic(); + F03ShiftedRotatedHighCondElliptic(int dimension, double bias); + F03ShiftedRotatedHighCondElliptic(int dimension, double bias, std::string file_data, std::string file_m); + ~F03ShiftedRotatedHighCondElliptic(); - double f (double * x); + double f (double * x); }; // F03ShiftedRotatedHighCondElliptic diff --git a/src/problems/singleObjective/cec2005Competition/F04ShiftedSchwefelNoise.cpp b/src/problems/singleObjective/cec2005Competition/F04ShiftedSchwefelNoise.cpp index c583a89..fec44e8 100644 --- a/src/problems/singleObjective/cec2005Competition/F04ShiftedSchwefelNoise.cpp +++ b/src/problems/singleObjective/cec2005Competition/F04ShiftedSchwefelNoise.cpp @@ -23,31 +23,33 @@ #include // Fixed (class) parameters -const string F04ShiftedSchwefelNoise::FUNCTION_NAME = "Shifted Schwefel's Problem 1.2 with Noise in Fitness"; +const std::string F04ShiftedSchwefelNoise::FUNCTION_NAME = "Shifted Schwefel's Problem 1.2 with Noise in Fitness"; // TODO: Cambiar ruta -const string F04ShiftedSchwefelNoise::DEFAULT_FILE_DATA = "../../data/cec2005CompetitionResources/supportData/schwefel_102_data.txt"; +const std::string F04ShiftedSchwefelNoise::DEFAULT_FILE_DATA = "../../data/cec2005CompetitionResources/supportData/schwefel_102_data.txt"; /** * Constructor. */ F04ShiftedSchwefelNoise::F04ShiftedSchwefelNoise(int dimension, double bias) - : F04ShiftedSchwefelNoise(dimension, bias, DEFAULT_FILE_DATA) { + : F04ShiftedSchwefelNoise(dimension, bias, DEFAULT_FILE_DATA) +{ } // F04ShiftedSchwefelNoise /** * Constructor */ -F04ShiftedSchwefelNoise::F04ShiftedSchwefelNoise(int dimension, double bias, string file_data) - : TestFunc(dimension, bias, FUNCTION_NAME) { +F04ShiftedSchwefelNoise::F04ShiftedSchwefelNoise(int dimension, double bias, std::string file_data) + : TestFunc(dimension, bias, FUNCTION_NAME) +{ - // Note: dimension starts from 0 - m_o = new double[m_dimension]; - m_z = new double[m_dimension]; + // Note: dimension starts from 0 + m_o = snew double[m_dimension]; + m_z = snew double[m_dimension]; - // Load the shifted global optimum - Benchmark::loadRowVectorFromFile(file_data, m_dimension, m_o); + // Load the shifted global optimum + Benchmark::loadRowVectorFromFile(file_data, m_dimension, m_o); } // F04ShiftedSchwefelNoise @@ -55,27 +57,29 @@ F04ShiftedSchwefelNoise::F04ShiftedSchwefelNoise(int dimension, double bias, str /** * Destructor */ -F04ShiftedSchwefelNoise::~F04ShiftedSchwefelNoise() { - delete [] m_o; - delete [] m_z; +F04ShiftedSchwefelNoise::~F04ShiftedSchwefelNoise() +{ + delete [] m_o; + delete [] m_z; } // ~F04ShiftedSchwefelNoise /** * Function body */ -double F04ShiftedSchwefelNoise::f(double * x) { - double result = 0.0; +double F04ShiftedSchwefelNoise::f(double * x) +{ + double result = 0.0; - Benchmark::shift(m_z, x, m_o, m_dimension); + Benchmark::shift(m_z, x, m_o, m_dimension); - result = Benchmark::schwefel_102(m_z, m_dimension); + result = Benchmark::schwefel_102(m_z, m_dimension); - // NOISE - // Comment the next line to remove the noise - result *= (1.0 + 0.4 * fabs(Benchmark::dist(Benchmark::e2))); + // NOISE + // Comment the next line to remove the noise + result *= (1.0 + 0.4 * fabs(Benchmark::dist(Benchmark::e2))); - result += m_bias; + result += m_bias; - return result; + return result; } diff --git a/src/problems/singleObjective/cec2005Competition/F04ShiftedSchwefelNoise.h b/src/problems/singleObjective/cec2005Competition/F04ShiftedSchwefelNoise.h index e8825c9..9a6bb1f 100644 --- a/src/problems/singleObjective/cec2005Competition/F04ShiftedSchwefelNoise.h +++ b/src/problems/singleObjective/cec2005Competition/F04ShiftedSchwefelNoise.h @@ -25,28 +25,29 @@ #include #include -class F04ShiftedSchwefelNoise : public TestFunc { +class F04ShiftedSchwefelNoise : public TestFunc +{ private: - // Fixed (class) parameters - static const string FUNCTION_NAME; - static const string DEFAULT_FILE_DATA; + // Fixed (class) parameters + static const std::string FUNCTION_NAME; + static const std::string DEFAULT_FILE_DATA; - // Shifted global optimum - double * m_o; + // Shifted global optimum + double * m_o; - // In order to avoid excessive memory allocation, - // a fixed memory buffer is allocated for each function object. - double * m_z; + // In order to avoid excessive memory allocation, + // a fixed memory buffer is allocated for each function object. + double * m_z; public: - F04ShiftedSchwefelNoise(int dimension, double bias); - F04ShiftedSchwefelNoise(int dimension, double bias, string file_data); - ~F04ShiftedSchwefelNoise(); + F04ShiftedSchwefelNoise(int dimension, double bias); + F04ShiftedSchwefelNoise(int dimension, double bias, std::string file_data); + ~F04ShiftedSchwefelNoise(); - double f (double * x); + double f (double * x); }; // F04ShiftedSchwefelNoise diff --git a/src/problems/singleObjective/cec2005Competition/F05SchwefelGlobalOptBound.cpp b/src/problems/singleObjective/cec2005Competition/F05SchwefelGlobalOptBound.cpp index 389f048..878791a 100644 --- a/src/problems/singleObjective/cec2005Competition/F05SchwefelGlobalOptBound.cpp +++ b/src/problems/singleObjective/cec2005Competition/F05SchwefelGlobalOptBound.cpp @@ -21,63 +21,77 @@ #include +#include "JMetalHeader.h" // Fixed (class) parameters -const string F05SchwefelGlobalOptBound::FUNCTION_NAME = "Schwefel's Problem 2.6 with Global Optimum on Bounds"; +const std::string F05SchwefelGlobalOptBound::FUNCTION_NAME = "Schwefel's Problem 2.6 with Global Optimum on Bounds"; // TODO: Cambiar ruta -const string F05SchwefelGlobalOptBound::DEFAULT_FILE_DATA = "../../data/cec2005CompetitionResources/supportData/schwefel_206_data.txt"; +const std::string F05SchwefelGlobalOptBound::DEFAULT_FILE_DATA = "../../data/cec2005CompetitionResources/supportData/schwefel_206_data.txt"; /** * Constructor. */ F05SchwefelGlobalOptBound::F05SchwefelGlobalOptBound(int dimension, double bias) - : F05SchwefelGlobalOptBound(dimension, bias, DEFAULT_FILE_DATA) { + : F05SchwefelGlobalOptBound(dimension, bias, DEFAULT_FILE_DATA) +{ } // F05SchwefelGlobalOptBound /** * Constructor */ -F05SchwefelGlobalOptBound::F05SchwefelGlobalOptBound(int dimension, double bias, string file_data) - : TestFunc(dimension, bias, FUNCTION_NAME) { - - // Note: dimension starts from 0 - m_o = new double[m_dimension]; - m_A = new double*[m_dimension]; - for (int i=0; i= floor((3.0 * m_dimension) / 4.0)) { - m_o[i] = 100.0; - } else { - m_o[i] = m_data[0][i]; +F05SchwefelGlobalOptBound::F05SchwefelGlobalOptBound(int dimension, double bias, std::string file_data) + : TestFunc(dimension, bias, FUNCTION_NAME) +{ + + // Note: dimension starts from 0 + m_o = snew double[m_dimension]; + m_A = snew double*[m_dimension]; + for (int i=0; i= floor((3.0 * m_dimension) / 4.0)) + { + m_o[i] = 100.0; + } + else + { + m_o[i] = m_data[0][i]; + } + } + for (int i = 0 ; i < m_dimension ; i ++) + { + for (int j = 0 ; j < m_dimension ; j ++) + { + m_A[i][j] = m_data[i+1][j]; + } } - } - Benchmark::Ax(m_B, m_A, m_o, m_dimension); + Benchmark::Ax(m_B, m_A, m_o, m_dimension); - for (int i=0; i::max(); - - Benchmark::Ax(m_z, m_A, x, m_dimension); - - for (int i = 0 ; i < m_dimension ; i ++) { - double temp = fabs(m_z[i] - m_B[i]); - if (max < temp) { - max = temp; +double F05SchwefelGlobalOptBound::f(double * x) +{ + double max = -numeric_limits::max(); + + Benchmark::Ax(m_z, m_A, x, m_dimension); + + for (int i = 0 ; i < m_dimension ; i ++) + { + double temp = fabs(m_z[i] - m_B[i]); + if (max < temp) + { + max = temp; + } } - } - return (max + m_bias); + return (max + m_bias); } diff --git a/src/problems/singleObjective/cec2005Competition/F05SchwefelGlobalOptBound.h b/src/problems/singleObjective/cec2005Competition/F05SchwefelGlobalOptBound.h index 17f7fc2..2f7a3fc 100644 --- a/src/problems/singleObjective/cec2005Competition/F05SchwefelGlobalOptBound.h +++ b/src/problems/singleObjective/cec2005Competition/F05SchwefelGlobalOptBound.h @@ -25,30 +25,31 @@ #include #include -class F05SchwefelGlobalOptBound : public TestFunc { +class F05SchwefelGlobalOptBound : public TestFunc +{ private: - // Fixed (class) parameters - static const string FUNCTION_NAME; - static const string DEFAULT_FILE_DATA; + // Fixed (class) parameters + static const std::string FUNCTION_NAME; + static const std::string DEFAULT_FILE_DATA; - // Shifted global optimum - double * m_o; - double ** m_A; + // Shifted global optimum + double * m_o; + double ** m_A; - // In order to avoid excessive memory allocation, - // a fixed memory buffer is allocated for each function object. - double * m_B; - double * m_z; + // In order to avoid excessive memory allocation, + // a fixed memory buffer is allocated for each function object. + double * m_B; + double * m_z; public: - F05SchwefelGlobalOptBound(int dimension, double bias); - F05SchwefelGlobalOptBound(int dimension, double bias, string file_data); - ~F05SchwefelGlobalOptBound(); + F05SchwefelGlobalOptBound(int dimension, double bias); + F05SchwefelGlobalOptBound(int dimension, double bias, std::string file_data); + ~F05SchwefelGlobalOptBound(); - double f (double * x); + double f (double * x); }; // F05SchwefelGlobalOptBound diff --git a/src/problems/singleObjective/cec2005Competition/F06ShiftedRosenbrock.cpp b/src/problems/singleObjective/cec2005Competition/F06ShiftedRosenbrock.cpp index b5624ab..11df9d8 100644 --- a/src/problems/singleObjective/cec2005Competition/F06ShiftedRosenbrock.cpp +++ b/src/problems/singleObjective/cec2005Competition/F06ShiftedRosenbrock.cpp @@ -23,37 +23,40 @@ #include // Fixed (class) parameters -const string F06ShiftedRosenbrock::FUNCTION_NAME = "Shifted Rosenbrock's Function"; +const std::string F06ShiftedRosenbrock::FUNCTION_NAME = "Shifted Rosenbrock's Function"; // TODO: Cambiar ruta -const string F06ShiftedRosenbrock::DEFAULT_FILE_DATA = "../../data/cec2005CompetitionResources/supportData/rosenbrock_func_data.txt"; +const std::string F06ShiftedRosenbrock::DEFAULT_FILE_DATA = "../../data/cec2005CompetitionResources/supportData/rosenbrock_func_data.txt"; /** * Constructor. */ F06ShiftedRosenbrock::F06ShiftedRosenbrock(int dimension, double bias) - : F06ShiftedRosenbrock(dimension, bias, DEFAULT_FILE_DATA) { + : F06ShiftedRosenbrock(dimension, bias, DEFAULT_FILE_DATA) +{ } // F06ShiftedRosenbrock /** * Constructor */ -F06ShiftedRosenbrock::F06ShiftedRosenbrock(int dimension, double bias, string file_data) - : TestFunc(dimension, bias, FUNCTION_NAME) { +F06ShiftedRosenbrock::F06ShiftedRosenbrock(int dimension, double bias, std::string file_data) + : TestFunc(dimension, bias, FUNCTION_NAME) +{ - // Note: dimension starts from 0 - m_o = new double[m_dimension]; - m_z = new double[m_dimension]; + // Note: dimension starts from 0 + m_o = snew double[m_dimension]; + m_z = snew double[m_dimension]; - // Load the shifted global optimum - Benchmark::loadRowVectorFromFile(file_data, m_dimension, m_o); + // Load the shifted global optimum + Benchmark::loadRowVectorFromFile(file_data, m_dimension, m_o); - // z = x - o + 1 = x - (o - 1) - // Do the "(o - 1)" part first - for (int i = 0 ; i < m_dimension ; i ++) { - m_o[i] -= 1.0; - } + // z = x - o + 1 = x - (o - 1) + // Do the "(o - 1)" part first + for (int i = 0 ; i < m_dimension ; i ++) + { + m_o[i] -= 1.0; + } } // F06ShiftedRosenbrock @@ -61,23 +64,25 @@ F06ShiftedRosenbrock::F06ShiftedRosenbrock(int dimension, double bias, string fi /** * Destructor */ -F06ShiftedRosenbrock::~F06ShiftedRosenbrock() { - delete [] m_o; - delete [] m_z; +F06ShiftedRosenbrock::~F06ShiftedRosenbrock() +{ + delete [] m_o; + delete [] m_z; } // ~F06ShiftedRosenbrock /** * Function body */ -double F06ShiftedRosenbrock::f(double * x) { - double result = 0.0; +double F06ShiftedRosenbrock::f(double * x) +{ + double result = 0.0; - Benchmark::shift(m_z, x, m_o, m_dimension); + Benchmark::shift(m_z, x, m_o, m_dimension); - result = Benchmark::rosenbrock(m_z, m_dimension); + result = Benchmark::rosenbrock(m_z, m_dimension); - result += m_bias; + result += m_bias; - return result; + return result; } diff --git a/src/problems/singleObjective/cec2005Competition/F06ShiftedRosenbrock.h b/src/problems/singleObjective/cec2005Competition/F06ShiftedRosenbrock.h index 958b8e6..c9b14f3 100644 --- a/src/problems/singleObjective/cec2005Competition/F06ShiftedRosenbrock.h +++ b/src/problems/singleObjective/cec2005Competition/F06ShiftedRosenbrock.h @@ -25,28 +25,29 @@ #include #include -class F06ShiftedRosenbrock : public TestFunc { +class F06ShiftedRosenbrock : public TestFunc +{ private: - // Fixed (class) parameters - static const string FUNCTION_NAME; - static const string DEFAULT_FILE_DATA; + // Fixed (class) parameters + static const std::string FUNCTION_NAME; + static const std::string DEFAULT_FILE_DATA; - // Shifted global optimum - double * m_o; + // Shifted global optimum + double * m_o; - // In order to avoid excessive memory allocation, - // a fixed memory buffer is allocated for each function object. - double * m_z; + // In order to avoid excessive memory allocation, + // a fixed memory buffer is allocated for each function object. + double * m_z; public: - F06ShiftedRosenbrock(int dimension, double bias); - F06ShiftedRosenbrock(int dimension, double bias, string file_data); - ~F06ShiftedRosenbrock(); + F06ShiftedRosenbrock(int dimension, double bias); + F06ShiftedRosenbrock(int dimension, double bias, std::string file_data); + ~F06ShiftedRosenbrock(); - double f (double * x); + double f (double * x); }; // F06ShiftedRosenbrock diff --git a/src/problems/singleObjective/cec2005Competition/F07ShiftedRotatedGriewank.cpp b/src/problems/singleObjective/cec2005Competition/F07ShiftedRotatedGriewank.cpp index 8887f03..9c19171 100644 --- a/src/problems/singleObjective/cec2005Competition/F07ShiftedRotatedGriewank.cpp +++ b/src/problems/singleObjective/cec2005Competition/F07ShiftedRotatedGriewank.cpp @@ -21,42 +21,46 @@ #include +#include "JMetalHeader.h" // Fixed (class) parameters -const string F07ShiftedRotatedGriewank::FUNCTION_NAME = "Shifted Rotated Griewank's Function without Bounds"; +const std::string F07ShiftedRotatedGriewank::FUNCTION_NAME = "Shifted Rotated Griewank's Function without Bounds"; // TODO: Cambiar ruta -const string F07ShiftedRotatedGriewank::DEFAULT_FILE_DATA = "../../data/cec2005CompetitionResources/supportData/griewank_func_data.txt"; -const string F07ShiftedRotatedGriewank::DEFAULT_FILE_MX_PREFIX = "../../data/cec2005CompetitionResources/supportData/griewank_M_D"; -const string F07ShiftedRotatedGriewank::DEFAULT_FILE_MX_SUFFIX = ".txt"; +const std::string F07ShiftedRotatedGriewank::DEFAULT_FILE_DATA = "../../data/cec2005CompetitionResources/supportData/griewank_func_data.txt"; +const std::string F07ShiftedRotatedGriewank::DEFAULT_FILE_MX_PREFIX = "../../data/cec2005CompetitionResources/supportData/griewank_M_D"; +const std::string F07ShiftedRotatedGriewank::DEFAULT_FILE_MX_SUFFIX = ".txt"; /** * Constructor. */ F07ShiftedRotatedGriewank::F07ShiftedRotatedGriewank(int dimension, double bias) - : F07ShiftedRotatedGriewank(dimension, bias, DEFAULT_FILE_DATA, getFileMxName(DEFAULT_FILE_MX_PREFIX, dimension, DEFAULT_FILE_MX_SUFFIX)) { + : F07ShiftedRotatedGriewank(dimension, bias, DEFAULT_FILE_DATA, getFileMxName(DEFAULT_FILE_MX_PREFIX, dimension, DEFAULT_FILE_MX_SUFFIX)) +{ } // F07ShiftedRotatedGriewank /** * Constructor */ -F07ShiftedRotatedGriewank::F07ShiftedRotatedGriewank(int dimension, double bias, string file_data, string file_m) - : TestFunc(dimension, bias, FUNCTION_NAME) { - - // Note: dimension starts from 0 - m_o = new double[m_dimension]; - m_matrix = new double*[m_dimension]; - for (int i=0; i #include -class F07ShiftedRotatedGriewank : public TestFunc { +class F07ShiftedRotatedGriewank : public TestFunc +{ private: - // Fixed (class) parameters - static const string FUNCTION_NAME; - static const string DEFAULT_FILE_DATA; - static const string DEFAULT_FILE_MX_PREFIX; - static const string DEFAULT_FILE_MX_SUFFIX; + // Fixed (class) parameters + static const std::string FUNCTION_NAME; + static const std::string DEFAULT_FILE_DATA; + static const std::string DEFAULT_FILE_MX_PREFIX; + static const std::string DEFAULT_FILE_MX_SUFFIX; - // Shifted global optimum - double * m_o; - double ** m_matrix; + // Shifted global optimum + double * m_o; + double ** m_matrix; - // In order to avoid excessive memory allocation, - // a fixed memory buffer is allocated for each function object. - double * m_z; - double * m_zM; + // In order to avoid excessive memory allocation, + // a fixed memory buffer is allocated for each function object. + double * m_z; + double * m_zM; - string getFileMxName(string prefix, int dimension, string suffix); + std::string getFileMxName(std::string prefix, int dimension, std::string suffix); public: - F07ShiftedRotatedGriewank(int dimension, double bias); - F07ShiftedRotatedGriewank(int dimension, double bias, string file_data, string file_m); - ~F07ShiftedRotatedGriewank(); + F07ShiftedRotatedGriewank(int dimension, double bias); + F07ShiftedRotatedGriewank(int dimension, double bias, std::string file_data, std::string file_m); + ~F07ShiftedRotatedGriewank(); - double f (double * x); + double f (double * x); }; // F07ShiftedRotatedGriewank diff --git a/src/problems/singleObjective/cec2005Competition/F08ShiftedRotatedAckleyGlobalOptBound.cpp b/src/problems/singleObjective/cec2005Competition/F08ShiftedRotatedAckleyGlobalOptBound.cpp index 7770bd8..46242d4 100644 --- a/src/problems/singleObjective/cec2005Competition/F08ShiftedRotatedAckleyGlobalOptBound.cpp +++ b/src/problems/singleObjective/cec2005Competition/F08ShiftedRotatedAckleyGlobalOptBound.cpp @@ -21,46 +21,51 @@ #include +#include "JMetalHeader.h" // Fixed (class) parameters -const string F08ShiftedRotatedAckleyGlobalOptBound::FUNCTION_NAME = "Shifted Rotated Ackley's Function with Global Optimum on Bounds"; +const std::string F08ShiftedRotatedAckleyGlobalOptBound::FUNCTION_NAME = "Shifted Rotated Ackley's Function with Global Optimum on Bounds"; // TODO: Cambiar ruta -const string F08ShiftedRotatedAckleyGlobalOptBound::DEFAULT_FILE_DATA = "../../data/cec2005CompetitionResources/supportData/ackley_func_data.txt"; -const string F08ShiftedRotatedAckleyGlobalOptBound::DEFAULT_FILE_MX_PREFIX = "../../data/cec2005CompetitionResources/supportData/ackley_M_D"; -const string F08ShiftedRotatedAckleyGlobalOptBound::DEFAULT_FILE_MX_SUFFIX = ".txt"; +const std::string F08ShiftedRotatedAckleyGlobalOptBound::DEFAULT_FILE_DATA = "../../data/cec2005CompetitionResources/supportData/ackley_func_data.txt"; +const std::string F08ShiftedRotatedAckleyGlobalOptBound::DEFAULT_FILE_MX_PREFIX = "../../data/cec2005CompetitionResources/supportData/ackley_M_D"; +const std::string F08ShiftedRotatedAckleyGlobalOptBound::DEFAULT_FILE_MX_SUFFIX = ".txt"; /** * Constructor. */ F08ShiftedRotatedAckleyGlobalOptBound::F08ShiftedRotatedAckleyGlobalOptBound(int dimension, double bias) - : F08ShiftedRotatedAckleyGlobalOptBound(dimension, bias, DEFAULT_FILE_DATA, getFileMxName(DEFAULT_FILE_MX_PREFIX, dimension, DEFAULT_FILE_MX_SUFFIX)) { + : F08ShiftedRotatedAckleyGlobalOptBound(dimension, bias, DEFAULT_FILE_DATA, getFileMxName(DEFAULT_FILE_MX_PREFIX, dimension, DEFAULT_FILE_MX_SUFFIX)) +{ } // F08ShiftedRotatedAckleyGlobalOptBound /** * Constructor */ -F08ShiftedRotatedAckleyGlobalOptBound::F08ShiftedRotatedAckleyGlobalOptBound(int dimension, double bias, string file_data, string file_m) - : TestFunc(dimension, bias, FUNCTION_NAME) { - - // Note: dimension starts from 0 - m_o = new double[m_dimension]; - m_matrix = new double*[m_dimension]; - for (int i=0; i #include -class F08ShiftedRotatedAckleyGlobalOptBound : public TestFunc { +class F08ShiftedRotatedAckleyGlobalOptBound : public TestFunc +{ private: - // Fixed (class) parameters - static const string FUNCTION_NAME; - static const string DEFAULT_FILE_DATA; - static const string DEFAULT_FILE_MX_PREFIX; - static const string DEFAULT_FILE_MX_SUFFIX; + // Fixed (class) parameters + static const std::string FUNCTION_NAME; + static const std::string DEFAULT_FILE_DATA; + static const std::string DEFAULT_FILE_MX_PREFIX; + static const std::string DEFAULT_FILE_MX_SUFFIX; - // Shifted global optimum - double * m_o; - double ** m_matrix; + // Shifted global optimum + double * m_o; + double ** m_matrix; - // In order to avoid excessive memory allocation, - // a fixed memory buffer is allocated for each function object. - double * m_z; - double * m_zM; + // In order to avoid excessive memory allocation, + // a fixed memory buffer is allocated for each function object. + double * m_z; + double * m_zM; - string getFileMxName(string prefix, int dimension, string suffix); + std::string getFileMxName(std::string prefix, int dimension, std::string suffix); public: - F08ShiftedRotatedAckleyGlobalOptBound(int dimension, double bias); - F08ShiftedRotatedAckleyGlobalOptBound(int dimension, double bias, string file_data, string file_m); - ~F08ShiftedRotatedAckleyGlobalOptBound(); + F08ShiftedRotatedAckleyGlobalOptBound(int dimension, double bias); + F08ShiftedRotatedAckleyGlobalOptBound(int dimension, double bias, std::string file_data, std::string file_m); + ~F08ShiftedRotatedAckleyGlobalOptBound(); - double f (double * x); + double f (double * x); }; // F08ShiftedRotatedAckleyGlobalOptBound diff --git a/src/problems/singleObjective/cec2005Competition/F09ShiftedRastrigin.cpp b/src/problems/singleObjective/cec2005Competition/F09ShiftedRastrigin.cpp index 2964a21..3596391 100644 --- a/src/problems/singleObjective/cec2005Competition/F09ShiftedRastrigin.cpp +++ b/src/problems/singleObjective/cec2005Competition/F09ShiftedRastrigin.cpp @@ -23,31 +23,33 @@ #include // Fixed (class) parameters -const string F09ShiftedRastrigin::FUNCTION_NAME = "Shifted Rastrigin's Function"; +const std::string F09ShiftedRastrigin::FUNCTION_NAME = "Shifted Rastrigin's Function"; // TODO: Cambiar ruta -const string F09ShiftedRastrigin::DEFAULT_FILE_DATA = "../../data/cec2005CompetitionResources/supportData/rastrigin_func_data.txt"; +const std::string F09ShiftedRastrigin::DEFAULT_FILE_DATA = "../../data/cec2005CompetitionResources/supportData/rastrigin_func_data.txt"; /** * Constructor. */ F09ShiftedRastrigin::F09ShiftedRastrigin(int dimension, double bias) - : F09ShiftedRastrigin(dimension, bias, DEFAULT_FILE_DATA) { + : F09ShiftedRastrigin(dimension, bias, DEFAULT_FILE_DATA) +{ } // F09ShiftedRastrigin /** * Constructor */ -F09ShiftedRastrigin::F09ShiftedRastrigin(int dimension, double bias, string file_data) - : TestFunc(dimension, bias, FUNCTION_NAME) { +F09ShiftedRastrigin::F09ShiftedRastrigin(int dimension, double bias, std::string file_data) + : TestFunc(dimension, bias, FUNCTION_NAME) +{ - // Note: dimension starts from 0 - m_o = new double[m_dimension]; - m_z = new double[m_dimension]; + // Note: dimension starts from 0 + m_o = snew double[m_dimension]; + m_z = snew double[m_dimension]; - // Load the shifted global optimum - Benchmark::loadRowVectorFromFile(file_data, m_dimension, m_o); + // Load the shifted global optimum + Benchmark::loadRowVectorFromFile(file_data, m_dimension, m_o); } // F09ShiftedRastrigin @@ -55,23 +57,25 @@ F09ShiftedRastrigin::F09ShiftedRastrigin(int dimension, double bias, string file /** * Destructor */ -F09ShiftedRastrigin::~F09ShiftedRastrigin() { - delete [] m_o; - delete [] m_z; +F09ShiftedRastrigin::~F09ShiftedRastrigin() +{ + delete [] m_o; + delete [] m_z; } // ~F09ShiftedRastrigin /** * Function body */ -double F09ShiftedRastrigin::f(double * x) { - double result = 0.0; +double F09ShiftedRastrigin::f(double * x) +{ + double result = 0.0; - Benchmark::shift(m_z, x, m_o, m_dimension); + Benchmark::shift(m_z, x, m_o, m_dimension); - result = Benchmark::rastrigin(m_z, m_dimension); + result = Benchmark::rastrigin(m_z, m_dimension); - result += m_bias; + result += m_bias; - return result; + return result; } diff --git a/src/problems/singleObjective/cec2005Competition/F09ShiftedRastrigin.h b/src/problems/singleObjective/cec2005Competition/F09ShiftedRastrigin.h index 45e1183..2442a73 100644 --- a/src/problems/singleObjective/cec2005Competition/F09ShiftedRastrigin.h +++ b/src/problems/singleObjective/cec2005Competition/F09ShiftedRastrigin.h @@ -25,28 +25,29 @@ #include #include -class F09ShiftedRastrigin : public TestFunc { +class F09ShiftedRastrigin : public TestFunc +{ private: - // Fixed (class) parameters - static const string FUNCTION_NAME; - static const string DEFAULT_FILE_DATA; + // Fixed (class) parameters + static const std::string FUNCTION_NAME; + static const std::string DEFAULT_FILE_DATA; - // Shifted global optimum - double * m_o; + // Shifted global optimum + double * m_o; - // In order to avoid excessive memory allocation, - // a fixed memory buffer is allocated for each function object. - double * m_z; + // In order to avoid excessive memory allocation, + // a fixed memory buffer is allocated for each function object. + double * m_z; public: - F09ShiftedRastrigin(int dimension, double bias); - F09ShiftedRastrigin(int dimension, double bias, string file_data); - ~F09ShiftedRastrigin(); + F09ShiftedRastrigin(int dimension, double bias); + F09ShiftedRastrigin(int dimension, double bias, std::string file_data); + ~F09ShiftedRastrigin(); - double f (double * x); + double f (double * x); }; // F09ShiftedRastrigin diff --git a/src/problems/singleObjective/cec2005Competition/F10ShiftedRotatedRastrigin.cpp b/src/problems/singleObjective/cec2005Competition/F10ShiftedRotatedRastrigin.cpp index f474ca1..9c38489 100644 --- a/src/problems/singleObjective/cec2005Competition/F10ShiftedRotatedRastrigin.cpp +++ b/src/problems/singleObjective/cec2005Competition/F10ShiftedRotatedRastrigin.cpp @@ -21,42 +21,46 @@ #include +#include "JMetalHeader.h" // Fixed (class) parameters -const string F10ShiftedRotatedRastrigin::FUNCTION_NAME = "Shifted Rotated Rastrigin's Function"; +const std::string F10ShiftedRotatedRastrigin::FUNCTION_NAME = "Shifted Rotated Rastrigin's Function"; // TODO: Cambiar ruta -const string F10ShiftedRotatedRastrigin::DEFAULT_FILE_DATA = "../../data/cec2005CompetitionResources/supportData/rastrigin_func_data.txt"; -const string F10ShiftedRotatedRastrigin::DEFAULT_FILE_MX_PREFIX = "../../data/cec2005CompetitionResources/supportData/rastrigin_M_D"; -const string F10ShiftedRotatedRastrigin::DEFAULT_FILE_MX_SUFFIX = ".txt"; +const std::string F10ShiftedRotatedRastrigin::DEFAULT_FILE_DATA = "../../data/cec2005CompetitionResources/supportData/rastrigin_func_data.txt"; +const std::string F10ShiftedRotatedRastrigin::DEFAULT_FILE_MX_PREFIX = "../../data/cec2005CompetitionResources/supportData/rastrigin_M_D"; +const std::string F10ShiftedRotatedRastrigin::DEFAULT_FILE_MX_SUFFIX = ".txt"; /** * Constructor. */ F10ShiftedRotatedRastrigin::F10ShiftedRotatedRastrigin(int dimension, double bias) - : F10ShiftedRotatedRastrigin(dimension, bias, DEFAULT_FILE_DATA, getFileMxName(DEFAULT_FILE_MX_PREFIX, dimension, DEFAULT_FILE_MX_SUFFIX)) { + : F10ShiftedRotatedRastrigin(dimension, bias, DEFAULT_FILE_DATA, getFileMxName(DEFAULT_FILE_MX_PREFIX, dimension, DEFAULT_FILE_MX_SUFFIX)) +{ } // F10ShiftedRotatedRastrigin /** * Constructor */ -F10ShiftedRotatedRastrigin::F10ShiftedRotatedRastrigin(int dimension, double bias, string file_data, string file_m) - : TestFunc(dimension, bias, FUNCTION_NAME) { - - // Note: dimension starts from 0 - m_o = new double[m_dimension]; - m_matrix = new double*[m_dimension]; - for (int i=0; i #include -class F10ShiftedRotatedRastrigin : public TestFunc { +class F10ShiftedRotatedRastrigin : public TestFunc +{ private: - // Fixed (class) parameters - static const string FUNCTION_NAME; - static const string DEFAULT_FILE_DATA; - static const string DEFAULT_FILE_MX_PREFIX; - static const string DEFAULT_FILE_MX_SUFFIX; + // Fixed (class) parameters + static const std::string FUNCTION_NAME; + static const std::string DEFAULT_FILE_DATA; + static const std::string DEFAULT_FILE_MX_PREFIX; + static const std::string DEFAULT_FILE_MX_SUFFIX; - // Shifted global optimum - double * m_o; - double ** m_matrix; + // Shifted global optimum + double * m_o; + double ** m_matrix; - // In order to avoid excessive memory allocation, - // a fixed memory buffer is allocated for each function object. - double * m_z; - double * m_zM; + // In order to avoid excessive memory allocation, + // a fixed memory buffer is allocated for each function object. + double * m_z; + double * m_zM; - string getFileMxName(string prefix, int dimension, string suffix); + std::string getFileMxName(std::string prefix, int dimension, std::string suffix); public: - F10ShiftedRotatedRastrigin(int dimension, double bias); - F10ShiftedRotatedRastrigin(int dimension, double bias, string file_data, string file_m); - ~F10ShiftedRotatedRastrigin(); + F10ShiftedRotatedRastrigin(int dimension, double bias); + F10ShiftedRotatedRastrigin(int dimension, double bias, std::string file_data, std::string file_m); + ~F10ShiftedRotatedRastrigin(); - double f (double * x); + double f (double * x); }; // F10ShiftedRotatedRastrigin diff --git a/src/problems/singleObjective/cec2005Competition/F11ShiftedRotatedWeierstrass.cpp b/src/problems/singleObjective/cec2005Competition/F11ShiftedRotatedWeierstrass.cpp index f8e689f..52e78e5 100644 --- a/src/problems/singleObjective/cec2005Competition/F11ShiftedRotatedWeierstrass.cpp +++ b/src/problems/singleObjective/cec2005Competition/F11ShiftedRotatedWeierstrass.cpp @@ -21,13 +21,14 @@ #include +#include "JMetalHeader.h" // Fixed (class) parameters -const string F11ShiftedRotatedWeierstrass::FUNCTION_NAME = "Shifted Rotated Weierstrass Function"; +const std::string F11ShiftedRotatedWeierstrass::FUNCTION_NAME = "Shifted Rotated Weierstrass Function"; // TODO: Cambiar ruta -const string F11ShiftedRotatedWeierstrass::DEFAULT_FILE_DATA = "../../data/cec2005CompetitionResources/supportData/weierstrass_data.txt"; -const string F11ShiftedRotatedWeierstrass::DEFAULT_FILE_MX_PREFIX = "../../data/cec2005CompetitionResources/supportData/weierstrass_M_D"; -const string F11ShiftedRotatedWeierstrass::DEFAULT_FILE_MX_SUFFIX = ".txt"; +const std::string F11ShiftedRotatedWeierstrass::DEFAULT_FILE_DATA = "../../data/cec2005CompetitionResources/supportData/weierstrass_data.txt"; +const std::string F11ShiftedRotatedWeierstrass::DEFAULT_FILE_MX_PREFIX = "../../data/cec2005CompetitionResources/supportData/weierstrass_M_D"; +const std::string F11ShiftedRotatedWeierstrass::DEFAULT_FILE_MX_SUFFIX = ".txt"; const int F11ShiftedRotatedWeierstrass::Kmax = 20; const double F11ShiftedRotatedWeierstrass::a = 0.5; @@ -38,29 +39,32 @@ const double F11ShiftedRotatedWeierstrass::b = 3.0; * Constructor. */ F11ShiftedRotatedWeierstrass::F11ShiftedRotatedWeierstrass(int dimension, double bias) - : F11ShiftedRotatedWeierstrass(dimension, bias, DEFAULT_FILE_DATA, getFileMxName(DEFAULT_FILE_MX_PREFIX, dimension, DEFAULT_FILE_MX_SUFFIX)) { + : F11ShiftedRotatedWeierstrass(dimension, bias, DEFAULT_FILE_DATA, getFileMxName(DEFAULT_FILE_MX_PREFIX, dimension, DEFAULT_FILE_MX_SUFFIX)) +{ } // F11ShiftedRotatedWeierstrass /** * Constructor */ -F11ShiftedRotatedWeierstrass::F11ShiftedRotatedWeierstrass(int dimension, double bias, string file_data, string file_m) - : TestFunc(dimension, bias, FUNCTION_NAME) { - - // Note: dimension starts from 0 - m_o = new double[m_dimension]; - m_matrix = new double*[m_dimension]; - for (int i=0; i #include -class F11ShiftedRotatedWeierstrass : public TestFunc { +class F11ShiftedRotatedWeierstrass : public TestFunc +{ private: - // Fixed (class) parameters - static const string FUNCTION_NAME; - static const string DEFAULT_FILE_DATA; - static const string DEFAULT_FILE_MX_PREFIX; - static const string DEFAULT_FILE_MX_SUFFIX; + // Fixed (class) parameters + static const std::string FUNCTION_NAME; + static const std::string DEFAULT_FILE_DATA; + static const std::string DEFAULT_FILE_MX_PREFIX; + static const std::string DEFAULT_FILE_MX_SUFFIX; - static const int Kmax; - static const double a; - static const double b; + static const int Kmax; + static const double a; + static const double b; - // Shifted global optimum - double * m_o; - double ** m_matrix; + // Shifted global optimum + double * m_o; + double ** m_matrix; - // In order to avoid excessive memory allocation, - // a fixed memory buffer is allocated for each function object. - double * m_z; - double * m_zM; + // In order to avoid excessive memory allocation, + // a fixed memory buffer is allocated for each function object. + double * m_z; + double * m_zM; - string getFileMxName(string prefix, int dimension, string suffix); + std::string getFileMxName(std::string prefix, int dimension, std::string suffix); public: - F11ShiftedRotatedWeierstrass(int dimension, double bias); - F11ShiftedRotatedWeierstrass(int dimension, double bias, string file_data, string file_m); - ~F11ShiftedRotatedWeierstrass(); + F11ShiftedRotatedWeierstrass(int dimension, double bias); + F11ShiftedRotatedWeierstrass(int dimension, double bias, std::string file_data, std::string file_m); + ~F11ShiftedRotatedWeierstrass(); - double f (double * x); + double f (double * x); }; // F11ShiftedRotatedWeierstrass diff --git a/src/problems/singleObjective/cec2005Competition/F12Schwefel.cpp b/src/problems/singleObjective/cec2005Competition/F12Schwefel.cpp index 7011d9d..4e7dbc9 100644 --- a/src/problems/singleObjective/cec2005Competition/F12Schwefel.cpp +++ b/src/problems/singleObjective/cec2005Competition/F12Schwefel.cpp @@ -21,71 +21,82 @@ #include +#include "JMetalHeader.h" // Fixed (class) parameters -const string F12Schwefel::FUNCTION_NAME = "Schwefel's Problem 2.13"; +const std::string F12Schwefel::FUNCTION_NAME = "Schwefel's Problem 2.13"; // TODO: Cambiar ruta -const string F12Schwefel::DEFAULT_FILE_DATA = "../../data/cec2005CompetitionResources/supportData/schwefel_213_data.txt"; +const std::string F12Schwefel::DEFAULT_FILE_DATA = "../../data/cec2005CompetitionResources/supportData/schwefel_213_data.txt"; /** * Constructor. */ F12Schwefel::F12Schwefel(int dimension, double bias) - : F12Schwefel(dimension, bias, DEFAULT_FILE_DATA) { + : F12Schwefel(dimension, bias, DEFAULT_FILE_DATA) +{ } // F12Schwefel /** * Constructor */ -F12Schwefel::F12Schwefel(int dimension, double bias, string file_data) - : TestFunc(dimension, bias, FUNCTION_NAME) { - - // Note: dimension starts from 0 - m_o = new double[m_dimension]; - m_a = new double*[m_dimension]; - for (int i = 0; i < m_dimension; i++) { - m_a[i] = new double[m_dimension]; - } - m_b = new double*[m_dimension]; - for (int i = 0; i < m_dimension; i++) { - m_b[i] = new double[m_dimension]; - } - - m_A = new double[m_dimension]; - m_B = new double[m_dimension]; - - // Data: - // 1. a 100x100 - // 2. b 100x100 - // 3. alpha 1x100 - double ** m_data = new double*[100+100+1]; - for (int i = 0; i < (100+100+1); i++) { - m_data[i] = new double[m_dimension]; - } - - // Load the shifted global optimum - Benchmark::loadMatrixFromFile(file_data, (100+100+1), m_dimension, m_data); - for (int i = 0 ; i < m_dimension; i++) { - for (int j = 0 ; j < m_dimension; j++) { - m_a[i][j] = m_data[i][j]; - m_b[i][j] = m_data[100+i][j]; +F12Schwefel::F12Schwefel(int dimension, double bias, std::string file_data) + : TestFunc(dimension, bias, FUNCTION_NAME) +{ + + // Note: dimension starts from 0 + m_o = snew double[m_dimension]; + m_a = snew double*[m_dimension]; + for (int i = 0; i < m_dimension; i++) + { + m_a[i] = snew double[m_dimension]; + } + m_b = snew double*[m_dimension]; + for (int i = 0; i < m_dimension; i++) + { + m_b[i] = snew double[m_dimension]; + } + + m_A = snew double[m_dimension]; + m_B = snew double[m_dimension]; + + // Data: + // 1. a 100x100 + // 2. b 100x100 + // 3. alpha 1x100 + double ** m_data = snew double*[100+100+1]; + for (int i = 0; i < (100+100+1); i++) + { + m_data[i] = snew double[m_dimension]; + } + + // Load the shifted global optimum + Benchmark::loadMatrixFromFile(file_data, (100+100+1), m_dimension, m_data); + for (int i = 0 ; i < m_dimension; i++) + { + for (int j = 0 ; j < m_dimension; j++) + { + m_a[i][j] = m_data[i][j]; + m_b[i][j] = m_data[100+i][j]; + } + m_o[i] = m_data[100+100][i]; } - m_o[i] = m_data[100+100][i]; - } - for (int i = 0; i < m_dimension; i++) { - m_A[i] = 0.0; - for (int j = 0; j < m_dimension; j++) { - m_A[i] += (m_a[i][j] * sin(m_o[j]) + m_b[i][j] * cos(m_o[j])); + for (int i = 0; i < m_dimension; i++) + { + m_A[i] = 0.0; + for (int j = 0; j < m_dimension; j++) + { + m_A[i] += (m_a[i][j] * sin(m_o[j]) + m_b[i][j] * cos(m_o[j])); + } } - } - for (int i = 0; i < (100+100+1); i++) { - delete [] m_data[i]; - } - delete [] m_data; + for (int i = 0; i < (100+100+1); i++) + { + delete [] m_data[i]; + } + delete [] m_data; } // F12Schwefel @@ -93,36 +104,42 @@ F12Schwefel::F12Schwefel(int dimension, double bias, string file_data) /** * Destructor */ -F12Schwefel::~F12Schwefel() { - delete [] m_o; - for (int i = 0; i < m_dimension; i++) { - delete [] m_a[i]; - } - delete [] m_a; - for (int i = 0; i #include -class F12Schwefel : public TestFunc { +class F12Schwefel : public TestFunc +{ private: - // Fixed (class) parameters - static const string FUNCTION_NAME; - static const string DEFAULT_FILE_DATA; + // Fixed (class) parameters + static const std::string FUNCTION_NAME; + static const std::string DEFAULT_FILE_DATA; - // Shifted global optimum - double * m_o; - double ** m_a; - double ** m_b; + // Shifted global optimum + double * m_o; + double ** m_a; + double ** m_b; - // In order to avoid excessive memory allocation, - // a fixed memory buffer is allocated for each function object. - double * m_A; - double * m_B; + // In order to avoid excessive memory allocation, + // a fixed memory buffer is allocated for each function object. + double * m_A; + double * m_B; public: - F12Schwefel(int dimension, double bias); - F12Schwefel(int dimension, double bias, string file_data); - ~F12Schwefel(); + F12Schwefel(int dimension, double bias); + F12Schwefel(int dimension, double bias, std::string file_data); + ~F12Schwefel(); - double f (double * x); + double f (double * x); }; // F12Schwefel diff --git a/src/problems/singleObjective/cec2005Competition/F13ShiftedExpandedGriewankRosenbrock.cpp b/src/problems/singleObjective/cec2005Competition/F13ShiftedExpandedGriewankRosenbrock.cpp index df5a240..ae03be4 100644 --- a/src/problems/singleObjective/cec2005Competition/F13ShiftedExpandedGriewankRosenbrock.cpp +++ b/src/problems/singleObjective/cec2005Competition/F13ShiftedExpandedGriewankRosenbrock.cpp @@ -23,37 +23,40 @@ #include // Fixed (class) parameters -const string F13ShiftedExpandedGriewankRosenbrock::FUNCTION_NAME = "Shifted Expanded Griewank's plus Rosenbrock's Function"; +const std::string F13ShiftedExpandedGriewankRosenbrock::FUNCTION_NAME = "Shifted Expanded Griewank's plus Rosenbrock's Function"; // TODO: Cambiar ruta -const string F13ShiftedExpandedGriewankRosenbrock::DEFAULT_FILE_DATA = "../../data/cec2005CompetitionResources/supportData/EF8F2_func_data.txt"; +const std::string F13ShiftedExpandedGriewankRosenbrock::DEFAULT_FILE_DATA = "../../data/cec2005CompetitionResources/supportData/EF8F2_func_data.txt"; /** * Constructor. */ F13ShiftedExpandedGriewankRosenbrock::F13ShiftedExpandedGriewankRosenbrock(int dimension, double bias) - : F13ShiftedExpandedGriewankRosenbrock(dimension, bias, DEFAULT_FILE_DATA) { + : F13ShiftedExpandedGriewankRosenbrock(dimension, bias, DEFAULT_FILE_DATA) +{ } // F13ShiftedExpandedGriewankRosenbrock /** * Constructor */ -F13ShiftedExpandedGriewankRosenbrock::F13ShiftedExpandedGriewankRosenbrock(int dimension, double bias, string file_data) - : TestFunc(dimension, bias, FUNCTION_NAME) { +F13ShiftedExpandedGriewankRosenbrock::F13ShiftedExpandedGriewankRosenbrock(int dimension, double bias, std::string file_data) + : TestFunc(dimension, bias, FUNCTION_NAME) +{ - // Note: dimension starts from 0 - m_o = new double[m_dimension]; - m_z = new double[m_dimension]; + // Note: dimension starts from 0 + m_o = snew double[m_dimension]; + m_z = snew double[m_dimension]; - // Load the shifted global optimum - Benchmark::loadRowVectorFromFile(file_data, m_dimension, m_o); + // Load the shifted global optimum + Benchmark::loadRowVectorFromFile(file_data, m_dimension, m_o); - // z = x - o + 1 = x - (o - 1) - // Do the "(o - 1)" part first - for (int i = 0 ; i < m_dimension ; i++) { - m_o[i] -= 1.0; - } + // z = x - o + 1 = x - (o - 1) + // Do the "(o - 1)" part first + for (int i = 0 ; i < m_dimension ; i++) + { + m_o[i] -= 1.0; + } } // F13ShiftedExpandedGriewankRosenbrock @@ -61,23 +64,25 @@ F13ShiftedExpandedGriewankRosenbrock::F13ShiftedExpandedGriewankRosenbrock(int d /** * Destructor */ -F13ShiftedExpandedGriewankRosenbrock::~F13ShiftedExpandedGriewankRosenbrock() { - delete [] m_o; - delete [] m_z; +F13ShiftedExpandedGriewankRosenbrock::~F13ShiftedExpandedGriewankRosenbrock() +{ + delete [] m_o; + delete [] m_z; } // ~F13ShiftedExpandedGriewankRosenbrock /** * Function body */ -double F13ShiftedExpandedGriewankRosenbrock::f(double * x) { - double result = 0.0; +double F13ShiftedExpandedGriewankRosenbrock::f(double * x) +{ + double result = 0.0; - Benchmark::shift(m_z, x, m_o, m_dimension); + Benchmark::shift(m_z, x, m_o, m_dimension); - result = Benchmark::F8F2(m_z, m_dimension); + result = Benchmark::F8F2(m_z, m_dimension); - result += m_bias; + result += m_bias; - return result; + return result; } diff --git a/src/problems/singleObjective/cec2005Competition/F13ShiftedExpandedGriewankRosenbrock.h b/src/problems/singleObjective/cec2005Competition/F13ShiftedExpandedGriewankRosenbrock.h index 6c33859..60565c5 100644 --- a/src/problems/singleObjective/cec2005Competition/F13ShiftedExpandedGriewankRosenbrock.h +++ b/src/problems/singleObjective/cec2005Competition/F13ShiftedExpandedGriewankRosenbrock.h @@ -25,28 +25,29 @@ #include #include -class F13ShiftedExpandedGriewankRosenbrock : public TestFunc { +class F13ShiftedExpandedGriewankRosenbrock : public TestFunc +{ private: - // Fixed (class) parameters - static const string FUNCTION_NAME; - static const string DEFAULT_FILE_DATA; + // Fixed (class) parameters + static const std::string FUNCTION_NAME; + static const std::string DEFAULT_FILE_DATA; - // Shifted global optimum - double * m_o; + // Shifted global optimum + double * m_o; - // In order to avoid excessive memory allocation, - // a fixed memory buffer is allocated for each function object. - double * m_z; + // In order to avoid excessive memory allocation, + // a fixed memory buffer is allocated for each function object. + double * m_z; public: - F13ShiftedExpandedGriewankRosenbrock(int dimension, double bias); - F13ShiftedExpandedGriewankRosenbrock(int dimension, double bias, string file_data); - ~F13ShiftedExpandedGriewankRosenbrock(); + F13ShiftedExpandedGriewankRosenbrock(int dimension, double bias); + F13ShiftedExpandedGriewankRosenbrock(int dimension, double bias, std::string file_data); + ~F13ShiftedExpandedGriewankRosenbrock(); - double f (double * x); + double f (double * x); }; // F13ShiftedExpandedGriewankRosenbrock diff --git a/src/problems/singleObjective/cec2005Competition/F14ShiftedRotatedExpandedScaffer.cpp b/src/problems/singleObjective/cec2005Competition/F14ShiftedRotatedExpandedScaffer.cpp index c4c866b..4b190c9 100644 --- a/src/problems/singleObjective/cec2005Competition/F14ShiftedRotatedExpandedScaffer.cpp +++ b/src/problems/singleObjective/cec2005Competition/F14ShiftedRotatedExpandedScaffer.cpp @@ -21,42 +21,46 @@ #include +#include "JMetalHeader.h" // Fixed (class) parameters -const string F14ShiftedRotatedExpandedScaffer::FUNCTION_NAME = "Shifted Rotated Expanded Scaffer's F6 Function"; +const std::string F14ShiftedRotatedExpandedScaffer::FUNCTION_NAME = "Shifted Rotated Expanded Scaffer's F6 Function"; // TODO: Cambiar ruta -const string F14ShiftedRotatedExpandedScaffer::DEFAULT_FILE_DATA = "../../data/cec2005CompetitionResources/supportData/E_ScafferF6_func_data.txt"; -const string F14ShiftedRotatedExpandedScaffer::DEFAULT_FILE_MX_PREFIX = "../../data/cec2005CompetitionResources/supportData/E_ScafferF6_M_D"; -const string F14ShiftedRotatedExpandedScaffer::DEFAULT_FILE_MX_SUFFIX = ".txt"; +const std::string F14ShiftedRotatedExpandedScaffer::DEFAULT_FILE_DATA = "../../data/cec2005CompetitionResources/supportData/E_ScafferF6_func_data.txt"; +const std::string F14ShiftedRotatedExpandedScaffer::DEFAULT_FILE_MX_PREFIX = "../../data/cec2005CompetitionResources/supportData/E_ScafferF6_M_D"; +const std::string F14ShiftedRotatedExpandedScaffer::DEFAULT_FILE_MX_SUFFIX = ".txt"; /** * Constructor. */ F14ShiftedRotatedExpandedScaffer::F14ShiftedRotatedExpandedScaffer(int dimension, double bias) - : F14ShiftedRotatedExpandedScaffer(dimension, bias, DEFAULT_FILE_DATA, getFileMxName(DEFAULT_FILE_MX_PREFIX, dimension, DEFAULT_FILE_MX_SUFFIX)) { + : F14ShiftedRotatedExpandedScaffer(dimension, bias, DEFAULT_FILE_DATA, getFileMxName(DEFAULT_FILE_MX_PREFIX, dimension, DEFAULT_FILE_MX_SUFFIX)) +{ } // F14ShiftedRotatedExpandedScaffer /** * Constructor */ -F14ShiftedRotatedExpandedScaffer::F14ShiftedRotatedExpandedScaffer(int dimension, double bias, string file_data, string file_m) - : TestFunc(dimension, bias, FUNCTION_NAME) { - - // Note: dimension starts from 0 - m_o = new double[m_dimension]; - m_matrix = new double*[m_dimension]; - for (int i=0; i #include -class F14ShiftedRotatedExpandedScaffer : public TestFunc { +class F14ShiftedRotatedExpandedScaffer : public TestFunc +{ private: - // Fixed (class) parameters - static const string FUNCTION_NAME; - static const string DEFAULT_FILE_DATA; - static const string DEFAULT_FILE_MX_PREFIX; - static const string DEFAULT_FILE_MX_SUFFIX; + // Fixed (class) parameters + static const std::string FUNCTION_NAME; + static const std::string DEFAULT_FILE_DATA; + static const std::string DEFAULT_FILE_MX_PREFIX; + static const std::string DEFAULT_FILE_MX_SUFFIX; - // Shifted global optimum - double * m_o; - double ** m_matrix; + // Shifted global optimum + double * m_o; + double ** m_matrix; - // In order to avoid excessive memory allocation, - // a fixed memory buffer is allocated for each function object. - double * m_z; - double * m_zM; + // In order to avoid excessive memory allocation, + // a fixed memory buffer is allocated for each function object. + double * m_z; + double * m_zM; - string getFileMxName(string prefix, int dimension, string suffix); + std::string getFileMxName(std::string prefix, int dimension, std::string suffix); public: - F14ShiftedRotatedExpandedScaffer(int dimension, double bias); - F14ShiftedRotatedExpandedScaffer(int dimension, double bias, string file_data, string file_m); - ~F14ShiftedRotatedExpandedScaffer(); + F14ShiftedRotatedExpandedScaffer(int dimension, double bias); + F14ShiftedRotatedExpandedScaffer(int dimension, double bias, std::string file_data, std::string file_m); + ~F14ShiftedRotatedExpandedScaffer(); - double f (double * x); + double f (double * x); }; // F14ShiftedRotatedExpandedScaffer diff --git a/src/problems/singleObjective/cec2005Competition/F15HybridComposition1.cpp b/src/problems/singleObjective/cec2005Competition/F15HybridComposition1.cpp index 7057325..3fb8db7 100644 --- a/src/problems/singleObjective/cec2005Competition/F15HybridComposition1.cpp +++ b/src/problems/singleObjective/cec2005Competition/F15HybridComposition1.cpp @@ -21,27 +21,31 @@ #include +#include "JMetalHeader.h" // Fixed (class) parameters -const string F15HybridComposition1::FUNCTION_NAME = "Hybrid Composition Function 1"; +const std::string F15HybridComposition1::FUNCTION_NAME = "Hybrid Composition Function 1"; // TODO: Cambiar ruta -const string F15HybridComposition1::DEFAULT_FILE_DATA = "../../data/cec2005CompetitionResources/supportData/hybrid_func1_data.txt"; +const std::string F15HybridComposition1::DEFAULT_FILE_DATA = "../../data/cec2005CompetitionResources/supportData/hybrid_func1_data.txt"; -const double F15HybridComposition1::m_sigma[NUM_FUNC] = { - 1.0, 1.0, 1.0, 1.0, 1.0, - 1.0, 1.0, 1.0, 1.0, 1.0 +const double F15HybridComposition1::m_sigma[NUM_FUNC] = +{ + 1.0, 1.0, 1.0, 1.0, 1.0, + 1.0, 1.0, 1.0, 1.0, 1.0 }; -const double F15HybridComposition1::m_lambda[NUM_FUNC] = { - 1.0, 1.0, 10.0, 10.0, - 5.0/60.0, 5.0/60.0, 5.0/32.0, 5.0/32.0, - 5.0/100.0, 5.0/100.0 +const double F15HybridComposition1::m_lambda[NUM_FUNC] = +{ + 1.0, 1.0, 10.0, 10.0, + 5.0/60.0, 5.0/60.0, 5.0/32.0, 5.0/32.0, + 5.0/100.0, 5.0/100.0 }; -const double F15HybridComposition1::m_func_biases[NUM_FUNC] = { - 0.0, 100.0, 200.0, 300.0, 400.0, - 500.0, 600.0, 700.0, 800.0, 900.0 +const double F15HybridComposition1::m_func_biases[NUM_FUNC] = +{ + 0.0, 100.0, 200.0, 300.0, 400.0, + 500.0, 600.0, 700.0, 800.0, 900.0 }; @@ -49,74 +53,84 @@ const double F15HybridComposition1::m_func_biases[NUM_FUNC] = { * Constructor. */ F15HybridComposition1::F15HybridComposition1(int dimension, double bias) - : F15HybridComposition1(dimension, bias, DEFAULT_FILE_DATA) { + : F15HybridComposition1(dimension, bias, DEFAULT_FILE_DATA) +{ } // F15HybridComposition1 /** * Constructor */ -F15HybridComposition1::F15HybridComposition1(int dimension, double bias, string file_data) - : TestFunc(dimension, bias, FUNCTION_NAME) { - - // Note: dimension starts from 0 - m_o = new double*[NUM_FUNC]; - m_M = new double**[NUM_FUNC]; - - m_testPoint = new double[m_dimension]; - m_testPointM = new double[m_dimension]; - m_fmax = new double[NUM_FUNC]; - - m_w = new double[NUM_FUNC]; - m_z = new double*[NUM_FUNC]; - m_zM = new double*[NUM_FUNC]; - - for (int i=0; inum_func = NUM_FUNC; + theJob->num_dim = m_dimension; + theJob->C = 2000.0; + for (int i=0; isigma[i] = m_sigma[i]; + theJob->biases[i] = m_func_biases[i]; + theJob->lambda[i] = m_lambda[i]; } - } - - // Initialize the hybrid composition job object - theJob = new MyHCJob(NUM_FUNC); - theJob->num_func = NUM_FUNC; - theJob->num_dim = m_dimension; - theJob->C = 2000.0; - for (int i=0; isigma[i] = m_sigma[i]; - theJob->biases[i] = m_func_biases[i]; - theJob->lambda[i] = m_lambda[i]; - } - theJob->o = m_o; - theJob->M = m_M; - theJob->w = m_w; - theJob->z = m_z; - theJob->zM = m_zM; - // Calculate/estimate the fmax for all the functions involved - for (int i=0; io = m_o; + theJob->M = m_M; + theJob->w = m_w; + theJob->z = m_z; + theJob->zM = m_zM; + // Calculate/estimate the fmax for all the functions involved + for (int i=0; ibasic_func(i, m_testPointM, m_dimension)); } - Benchmark::rotate(m_testPointM, m_testPoint, m_M[i], m_dimension); - m_fmax[i] = fabs(theJob->basic_func(i, m_testPointM, m_dimension)); - } - theJob->fmax = m_fmax; + theJob->fmax = m_fmax; } // F15HybridComposition1 @@ -124,78 +138,85 @@ F15HybridComposition1::F15HybridComposition1(int dimension, double bias, string /** * Destructor */ -F15HybridComposition1::~F15HybridComposition1() { - - for (int i=0; i #include -class F15HybridComposition1 : public TestFunc { +class F15HybridComposition1 : public TestFunc +{ private: - // Fixed (class) parameters - static const string FUNCTION_NAME; - static const string DEFAULT_FILE_DATA; + // Fixed (class) parameters + static const std::string FUNCTION_NAME; + static const std::string DEFAULT_FILE_DATA; - // Number of functions - static const int NUM_FUNC = 10; + // Number of functions + static const int NUM_FUNC = 10; - // Shifted global optimum - double ** m_o; - double *** m_M; - static const double m_sigma[NUM_FUNC]; - static const double m_lambda[NUM_FUNC]; - static const double m_func_biases[NUM_FUNC]; - double * m_testPoint; - double * m_testPointM; - double * m_fmax; + // Shifted global optimum + double ** m_o; + double *** m_M; + static const double m_sigma[NUM_FUNC]; + static const double m_lambda[NUM_FUNC]; + static const double m_func_biases[NUM_FUNC]; + double * m_testPoint; + double * m_testPointM; + double * m_fmax; - // In order to avoid excessive memory allocation, - // a fixed memory buffer is allocated for each function object. - double * m_w; - double ** m_z; - double ** m_zM; + // In order to avoid excessive memory allocation, + // a fixed memory buffer is allocated for each function object. + double * m_w; + double ** m_z; + double ** m_zM; - class MyHCJob : public HCJob { - public: - MyHCJob(int numFunc); - double basic_func(int func_no, double* x, int length); - }; + class MyHCJob : public HCJob + { + public: + MyHCJob(int numFunc); + double basic_func(int func_no, double* x, int length); + }; - MyHCJob * theJob; + MyHCJob * theJob; public: - F15HybridComposition1(int dimension, double bias); - F15HybridComposition1(int dimension, double bias, string file_data); - ~F15HybridComposition1(); + F15HybridComposition1(int dimension, double bias); + F15HybridComposition1(int dimension, double bias, std::string file_data); + ~F15HybridComposition1(); - double f (double * x); + double f (double * x); }; // F15HybridComposition1 diff --git a/src/problems/singleObjective/cec2005Competition/F16RotatedHybridComposition1.cpp b/src/problems/singleObjective/cec2005Competition/F16RotatedHybridComposition1.cpp index 23e5f2e..5bd01e2 100644 --- a/src/problems/singleObjective/cec2005Competition/F16RotatedHybridComposition1.cpp +++ b/src/problems/singleObjective/cec2005Competition/F16RotatedHybridComposition1.cpp @@ -21,28 +21,32 @@ #include +#include "JMetalHeader.h" // Fixed (class) parameters -const string F16RotatedHybridComposition1::FUNCTION_NAME = "Rotated Hybrid Composition Function 1"; +const std::string F16RotatedHybridComposition1::FUNCTION_NAME = "Rotated Hybrid Composition Function 1"; // TODO: Cambiar ruta -const string F16RotatedHybridComposition1::DEFAULT_FILE_DATA = "../../data/cec2005CompetitionResources/supportData/hybrid_func1_data.txt"; -const string F16RotatedHybridComposition1::DEFAULT_FILE_MX_PREFIX = "../../data/cec2005CompetitionResources/supportData/hybrid_func1_M_D"; -const string F16RotatedHybridComposition1::DEFAULT_FILE_MX_SUFFIX = ".txt"; - -const double F16RotatedHybridComposition1::m_sigma[NUM_FUNC] = { - 1.0, 1.0, 1.0, 1.0, 1.0, - 1.0, 1.0, 1.0, 1.0, 1.0 +const std::string F16RotatedHybridComposition1::DEFAULT_FILE_DATA = "../../data/cec2005CompetitionResources/supportData/hybrid_func1_data.txt"; +const std::string F16RotatedHybridComposition1::DEFAULT_FILE_MX_PREFIX = "../../data/cec2005CompetitionResources/supportData/hybrid_func1_M_D"; +const std::string F16RotatedHybridComposition1::DEFAULT_FILE_MX_SUFFIX = ".txt"; + +const double F16RotatedHybridComposition1::m_sigma[NUM_FUNC] = +{ + 1.0, 1.0, 1.0, 1.0, 1.0, + 1.0, 1.0, 1.0, 1.0, 1.0 }; -const double F16RotatedHybridComposition1::m_lambda[NUM_FUNC] = { - 1.0, 1.0, 10.0, 10.0, - 5.0/60.0, 5.0/60.0, 5.0/32.0, 5.0/32.0, - 5.0/100.0, 5.0/100.0 +const double F16RotatedHybridComposition1::m_lambda[NUM_FUNC] = +{ + 1.0, 1.0, 10.0, 10.0, + 5.0/60.0, 5.0/60.0, 5.0/32.0, 5.0/32.0, + 5.0/100.0, 5.0/100.0 }; -const double F16RotatedHybridComposition1::m_func_biases[NUM_FUNC] = { - 0.0, 100.0, 200.0, 300.0, 400.0, - 500.0, 600.0, 700.0, 800.0, 900.0 +const double F16RotatedHybridComposition1::m_func_biases[NUM_FUNC] = +{ + 0.0, 100.0, 200.0, 300.0, 400.0, + 500.0, 600.0, 700.0, 800.0, 900.0 }; @@ -50,67 +54,74 @@ const double F16RotatedHybridComposition1::m_func_biases[NUM_FUNC] = { * Constructor. */ F16RotatedHybridComposition1::F16RotatedHybridComposition1(int dimension, double bias) - : F16RotatedHybridComposition1(dimension, bias, DEFAULT_FILE_DATA, getFileMxName(DEFAULT_FILE_MX_PREFIX, dimension, DEFAULT_FILE_MX_SUFFIX)) { + : F16RotatedHybridComposition1(dimension, bias, DEFAULT_FILE_DATA, getFileMxName(DEFAULT_FILE_MX_PREFIX, dimension, DEFAULT_FILE_MX_SUFFIX)) +{ } // F16RotatedHybridComposition1 /** * Constructor */ -F16RotatedHybridComposition1::F16RotatedHybridComposition1(int dimension, double bias, string file_data, string file_m) - : TestFunc(dimension, bias, FUNCTION_NAME) { - - // Note: dimension starts from 0 - m_o = new double*[NUM_FUNC]; - m_M = new double**[NUM_FUNC]; - - m_testPoint = new double[m_dimension]; - m_testPointM = new double[m_dimension]; - m_fmax = new double[NUM_FUNC]; - - m_w = new double[NUM_FUNC]; - m_z = new double*[NUM_FUNC]; - m_zM = new double*[NUM_FUNC]; - - for (int i=0; inum_func = NUM_FUNC; + theJob->num_dim = m_dimension; + theJob->C = 2000.0; + for (int i=0; isigma[i] = m_sigma[i]; + theJob->biases[i] = m_func_biases[i]; + theJob->lambda[i] = m_lambda[i]; } - } - - // Load the shifted global optimum - Benchmark::loadMatrixFromFile(file_data, NUM_FUNC, m_dimension, m_o); - // Load the matrix - Benchmark::loadNMatrixFromFile(file_m, NUM_FUNC, m_dimension, m_dimension, m_M); - - // Initialize the hybrid composition job object - theJob = new MyHCJob(NUM_FUNC); - theJob->num_func = NUM_FUNC; - theJob->num_dim = m_dimension; - theJob->C = 2000.0; - for (int i=0; isigma[i] = m_sigma[i]; - theJob->biases[i] = m_func_biases[i]; - theJob->lambda[i] = m_lambda[i]; - } - theJob->o = m_o; - theJob->M = m_M; - theJob->w = m_w; - theJob->z = m_z; - theJob->zM = m_zM; - // Calculate/estimate the fmax for all the functions involved - for (int i=0; io = m_o; + theJob->M = m_M; + theJob->w = m_w; + theJob->z = m_z; + theJob->zM = m_zM; + // Calculate/estimate the fmax for all the functions involved + for (int i=0; ibasic_func(i, m_testPointM, m_dimension)); } - Benchmark::rotate(m_testPointM, m_testPoint, m_M[i], m_dimension); - m_fmax[i] = fabs(theJob->basic_func(i, m_testPointM, m_dimension)); - } - theJob->fmax = m_fmax; + theJob->fmax = m_fmax; } // F16RotatedHybridComposition1 @@ -118,85 +129,93 @@ F16RotatedHybridComposition1::F16RotatedHybridComposition1(int dimension, double /** * Destructor */ -F16RotatedHybridComposition1::~F16RotatedHybridComposition1() { - - for (int i=0; i #include -class F16RotatedHybridComposition1 : public TestFunc { +class F16RotatedHybridComposition1 : public TestFunc +{ private: - // Fixed (class) parameters - static const string FUNCTION_NAME; - static const string DEFAULT_FILE_DATA; - static const string DEFAULT_FILE_MX_PREFIX; - static const string DEFAULT_FILE_MX_SUFFIX; - - // Number of functions - static const int NUM_FUNC = 10; - - // Shifted global optimum - double ** m_o; - double *** m_M; - static const double m_sigma[NUM_FUNC]; - static const double m_lambda[NUM_FUNC]; - static const double m_func_biases[NUM_FUNC]; - double * m_testPoint; - double * m_testPointM; - double * m_fmax; - - // In order to avoid excessive memory allocation, - // a fixed memory buffer is allocated for each function object. - double * m_w; - double ** m_z; - double ** m_zM; - - class MyHCJob : public HCJob { - public: - MyHCJob(int numFunc); - double basic_func(int func_no, double* x, int length); - }; - - MyHCJob * theJob; - - string getFileMxName(string prefix, int dimension, string suffix); + // Fixed (class) parameters + static const std::string FUNCTION_NAME; + static const std::string DEFAULT_FILE_DATA; + static const std::string DEFAULT_FILE_MX_PREFIX; + static const std::string DEFAULT_FILE_MX_SUFFIX; + + // Number of functions + static const int NUM_FUNC = 10; + + // Shifted global optimum + double ** m_o; + double *** m_M; + static const double m_sigma[NUM_FUNC]; + static const double m_lambda[NUM_FUNC]; + static const double m_func_biases[NUM_FUNC]; + double * m_testPoint; + double * m_testPointM; + double * m_fmax; + + // In order to avoid excessive memory allocation, + // a fixed memory buffer is allocated for each function object. + double * m_w; + double ** m_z; + double ** m_zM; + + class MyHCJob : public HCJob + { + public: + MyHCJob(int numFunc); + double basic_func(int func_no, double* x, int length); + }; + + MyHCJob * theJob; + + std::string getFileMxName(std::string prefix, int dimension, std::string suffix); public: - F16RotatedHybridComposition1(int dimension, double bias); - F16RotatedHybridComposition1(int dimension, double bias, string file_data, string file_m); - ~F16RotatedHybridComposition1(); + F16RotatedHybridComposition1(int dimension, double bias); + F16RotatedHybridComposition1(int dimension, double bias, std::string file_data, std::string file_m); + ~F16RotatedHybridComposition1(); - double f (double * x); + double f (double * x); }; // F16RotatedHybridComposition1 diff --git a/src/problems/singleObjective/cec2005Competition/F17RotatedHybridComposition1Noise.cpp b/src/problems/singleObjective/cec2005Competition/F17RotatedHybridComposition1Noise.cpp index 16fd83e..42478a6 100644 --- a/src/problems/singleObjective/cec2005Competition/F17RotatedHybridComposition1Noise.cpp +++ b/src/problems/singleObjective/cec2005Competition/F17RotatedHybridComposition1Noise.cpp @@ -21,28 +21,32 @@ #include +#include "JMetalHeader.h" // Fixed (class) parameters -const string F17RotatedHybridComposition1Noise::FUNCTION_NAME = "Rotated Hybrid Composition Function 1 with Noise in Fitness"; +const std::string F17RotatedHybridComposition1Noise::FUNCTION_NAME = "Rotated Hybrid Composition Function 1 with Noise in Fitness"; // TODO: Cambiar ruta -const string F17RotatedHybridComposition1Noise::DEFAULT_FILE_DATA = "../../data/cec2005CompetitionResources/supportData/hybrid_func1_data.txt"; -const string F17RotatedHybridComposition1Noise::DEFAULT_FILE_MX_PREFIX = "../../data/cec2005CompetitionResources/supportData/hybrid_func1_M_D"; -const string F17RotatedHybridComposition1Noise::DEFAULT_FILE_MX_SUFFIX = ".txt"; - -const double F17RotatedHybridComposition1Noise::m_sigma[NUM_FUNC] = { - 1.0, 1.0, 1.0, 1.0, 1.0, - 1.0, 1.0, 1.0, 1.0, 1.0 +const std::string F17RotatedHybridComposition1Noise::DEFAULT_FILE_DATA = "../../data/cec2005CompetitionResources/supportData/hybrid_func1_data.txt"; +const std::string F17RotatedHybridComposition1Noise::DEFAULT_FILE_MX_PREFIX = "../../data/cec2005CompetitionResources/supportData/hybrid_func1_M_D"; +const std::string F17RotatedHybridComposition1Noise::DEFAULT_FILE_MX_SUFFIX = ".txt"; + +const double F17RotatedHybridComposition1Noise::m_sigma[NUM_FUNC] = +{ + 1.0, 1.0, 1.0, 1.0, 1.0, + 1.0, 1.0, 1.0, 1.0, 1.0 }; -const double F17RotatedHybridComposition1Noise::m_lambda[NUM_FUNC] = { - 1.0, 1.0, 10.0, 10.0, - 5.0/60.0, 5.0/60.0, 5.0/32.0, 5.0/32.0, - 5.0/100.0, 5.0/100.0 +const double F17RotatedHybridComposition1Noise::m_lambda[NUM_FUNC] = +{ + 1.0, 1.0, 10.0, 10.0, + 5.0/60.0, 5.0/60.0, 5.0/32.0, 5.0/32.0, + 5.0/100.0, 5.0/100.0 }; -const double F17RotatedHybridComposition1Noise::m_func_biases[NUM_FUNC] = { - 0.0, 100.0, 200.0, 300.0, 400.0, - 500.0, 600.0, 700.0, 800.0, 900.0 +const double F17RotatedHybridComposition1Noise::m_func_biases[NUM_FUNC] = +{ + 0.0, 100.0, 200.0, 300.0, 400.0, + 500.0, 600.0, 700.0, 800.0, 900.0 }; @@ -50,67 +54,74 @@ const double F17RotatedHybridComposition1Noise::m_func_biases[NUM_FUNC] = { * Constructor. */ F17RotatedHybridComposition1Noise::F17RotatedHybridComposition1Noise(int dimension, double bias) - : F17RotatedHybridComposition1Noise(dimension, bias, DEFAULT_FILE_DATA, getFileMxName(DEFAULT_FILE_MX_PREFIX, dimension, DEFAULT_FILE_MX_SUFFIX)) { + : F17RotatedHybridComposition1Noise(dimension, bias, DEFAULT_FILE_DATA, getFileMxName(DEFAULT_FILE_MX_PREFIX, dimension, DEFAULT_FILE_MX_SUFFIX)) +{ } // F17RotatedHybridComposition1Noise /** * Constructor */ -F17RotatedHybridComposition1Noise::F17RotatedHybridComposition1Noise(int dimension, double bias, string file_data, string file_m) - : TestFunc(dimension, bias, FUNCTION_NAME) { - - // Note: dimension starts from 0 - m_o = new double*[NUM_FUNC]; - m_M = new double**[NUM_FUNC]; - - m_testPoint = new double[m_dimension]; - m_testPointM = new double[m_dimension]; - m_fmax = new double[NUM_FUNC]; - - m_w = new double[NUM_FUNC]; - m_z = new double*[NUM_FUNC]; - m_zM = new double*[NUM_FUNC]; - - for (int i=0; inum_func = NUM_FUNC; + theJob->num_dim = m_dimension; + theJob->C = 2000.0; + for (int i=0; isigma[i] = m_sigma[i]; + theJob->biases[i] = m_func_biases[i]; + theJob->lambda[i] = m_lambda[i]; } - } - - // Load the shifted global optimum - Benchmark::loadMatrixFromFile(file_data, NUM_FUNC, m_dimension, m_o); - // Load the matrix - Benchmark::loadNMatrixFromFile(file_m, NUM_FUNC, m_dimension, m_dimension, m_M); - - // Initialize the hybrid composition job object - theJob = new MyHCJob(NUM_FUNC); - theJob->num_func = NUM_FUNC; - theJob->num_dim = m_dimension; - theJob->C = 2000.0; - for (int i=0; isigma[i] = m_sigma[i]; - theJob->biases[i] = m_func_biases[i]; - theJob->lambda[i] = m_lambda[i]; - } - theJob->o = m_o; - theJob->M = m_M; - theJob->w = m_w; - theJob->z = m_z; - theJob->zM = m_zM; - // Calculate/estimate the fmax for all the functions involved - for (int i=0; io = m_o; + theJob->M = m_M; + theJob->w = m_w; + theJob->z = m_z; + theJob->zM = m_zM; + // Calculate/estimate the fmax for all the functions involved + for (int i=0; ibasic_func(i, m_testPointM, m_dimension)); } - Benchmark::rotate(m_testPointM, m_testPoint, m_M[i], m_dimension); - m_fmax[i] = fabs(theJob->basic_func(i, m_testPointM, m_dimension)); - } - theJob->fmax = m_fmax; + theJob->fmax = m_fmax; } // F17RotatedHybridComposition1Noise @@ -118,89 +129,97 @@ F17RotatedHybridComposition1Noise::F17RotatedHybridComposition1Noise(int dimensi /** * Destructor */ -F17RotatedHybridComposition1Noise::~F17RotatedHybridComposition1Noise() { - - for (int i=0; i #include -class F17RotatedHybridComposition1Noise : public TestFunc { +class F17RotatedHybridComposition1Noise : public TestFunc +{ private: - // Fixed (class) parameters - static const string FUNCTION_NAME; - static const string DEFAULT_FILE_DATA; - static const string DEFAULT_FILE_MX_PREFIX; - static const string DEFAULT_FILE_MX_SUFFIX; - - // Number of functions - static const int NUM_FUNC = 10; - - // Shifted global optimum - double ** m_o; - double *** m_M; - static const double m_sigma[NUM_FUNC]; - static const double m_lambda[NUM_FUNC]; - static const double m_func_biases[NUM_FUNC]; - double * m_testPoint; - double * m_testPointM; - double * m_fmax; - - // In order to avoid excessive memory allocation, - // a fixed memory buffer is allocated for each function object. - double * m_w; - double ** m_z; - double ** m_zM; - - class MyHCJob : public HCJob { - public: - MyHCJob(int numFunc); - double basic_func(int func_no, double* x, int length); - }; - - MyHCJob * theJob; - - string getFileMxName(string prefix, int dimension, string suffix); + // Fixed (class) parameters + static const std::string FUNCTION_NAME; + static const std::string DEFAULT_FILE_DATA; + static const std::string DEFAULT_FILE_MX_PREFIX; + static const std::string DEFAULT_FILE_MX_SUFFIX; + + // Number of functions + static const int NUM_FUNC = 10; + + // Shifted global optimum + double ** m_o; + double *** m_M; + static const double m_sigma[NUM_FUNC]; + static const double m_lambda[NUM_FUNC]; + static const double m_func_biases[NUM_FUNC]; + double * m_testPoint; + double * m_testPointM; + double * m_fmax; + + // In order to avoid excessive memory allocation, + // a fixed memory buffer is allocated for each function object. + double * m_w; + double ** m_z; + double ** m_zM; + + class MyHCJob : public HCJob + { + public: + MyHCJob(int numFunc); + double basic_func(int func_no, double* x, int length); + }; + + MyHCJob * theJob; + + std::string getFileMxName(std::string prefix, int dimension, std::string suffix); public: - F17RotatedHybridComposition1Noise(int dimension, double bias); - F17RotatedHybridComposition1Noise(int dimension, double bias, string file_data, string file_m); - ~F17RotatedHybridComposition1Noise(); + F17RotatedHybridComposition1Noise(int dimension, double bias); + F17RotatedHybridComposition1Noise(int dimension, double bias, std::string file_data, std::string file_m); + ~F17RotatedHybridComposition1Noise(); - double f (double * x); + double f (double * x); }; // F17RotatedHybridComposition1Noise diff --git a/src/problems/singleObjective/cec2005Competition/F18RotatedHybridComposition2.cpp b/src/problems/singleObjective/cec2005Competition/F18RotatedHybridComposition2.cpp index dbee489..0291440 100644 --- a/src/problems/singleObjective/cec2005Competition/F18RotatedHybridComposition2.cpp +++ b/src/problems/singleObjective/cec2005Competition/F18RotatedHybridComposition2.cpp @@ -21,27 +21,31 @@ #include +#include "JMetalHeader.h" // Fixed (class) parameters -const string F18RotatedHybridComposition2::FUNCTION_NAME = "Rotated Hybrid Composition Function 2"; +const std::string F18RotatedHybridComposition2::FUNCTION_NAME = "Rotated Hybrid Composition Function 2"; // TODO: Cambiar ruta -const string F18RotatedHybridComposition2::DEFAULT_FILE_DATA = "../../data/cec2005CompetitionResources/supportData/hybrid_func2_data.txt"; -const string F18RotatedHybridComposition2::DEFAULT_FILE_MX_PREFIX = "../../data/cec2005CompetitionResources/supportData/hybrid_func2_M_D"; -const string F18RotatedHybridComposition2::DEFAULT_FILE_MX_SUFFIX = ".txt"; - -const double F18RotatedHybridComposition2::m_sigma[NUM_FUNC] = { - 1.0, 2.0, 1.5, 1.5, 1.0, 1.0, - 1.5, 1.5, 2.0, 2.0 +const std::string F18RotatedHybridComposition2::DEFAULT_FILE_DATA = "../../data/cec2005CompetitionResources/supportData/hybrid_func2_data.txt"; +const std::string F18RotatedHybridComposition2::DEFAULT_FILE_MX_PREFIX = "../../data/cec2005CompetitionResources/supportData/hybrid_func2_M_D"; +const std::string F18RotatedHybridComposition2::DEFAULT_FILE_MX_SUFFIX = ".txt"; + +const double F18RotatedHybridComposition2::m_sigma[NUM_FUNC] = +{ + 1.0, 2.0, 1.5, 1.5, 1.0, 1.0, + 1.5, 1.5, 2.0, 2.0 }; -const double F18RotatedHybridComposition2::m_lambda[NUM_FUNC] = { - 2.0*5.0/32.0, 5.0/32.0, 2.0*1, 1.0, 2.0*5.0/100.0, - 5.0/100.0, 2.0*10.0, 10.0, 2.0*5.0/60.0, 5.0/60.0 +const double F18RotatedHybridComposition2::m_lambda[NUM_FUNC] = +{ + 2.0*5.0/32.0, 5.0/32.0, 2.0*1, 1.0, 2.0*5.0/100.0, + 5.0/100.0, 2.0*10.0, 10.0, 2.0*5.0/60.0, 5.0/60.0 }; -const double F18RotatedHybridComposition2::m_func_biases[NUM_FUNC] = { - 0.0, 100.0, 200.0, 300.0, 400.0, - 500.0, 600.0, 700.0, 800.0, 900.0 +const double F18RotatedHybridComposition2::m_func_biases[NUM_FUNC] = +{ + 0.0, 100.0, 200.0, 300.0, 400.0, + 500.0, 600.0, 700.0, 800.0, 900.0 }; @@ -49,70 +53,78 @@ const double F18RotatedHybridComposition2::m_func_biases[NUM_FUNC] = { * Constructor. */ F18RotatedHybridComposition2::F18RotatedHybridComposition2(int dimension, double bias) - : F18RotatedHybridComposition2(dimension, bias, DEFAULT_FILE_DATA, getFileMxName(DEFAULT_FILE_MX_PREFIX, dimension, DEFAULT_FILE_MX_SUFFIX)) { + : F18RotatedHybridComposition2(dimension, bias, DEFAULT_FILE_DATA, getFileMxName(DEFAULT_FILE_MX_PREFIX, dimension, DEFAULT_FILE_MX_SUFFIX)) +{ } // F18RotatedHybridComposition2 /** * Constructor */ -F18RotatedHybridComposition2::F18RotatedHybridComposition2(int dimension, double bias, string file_data, string file_m) - : TestFunc(dimension, bias, FUNCTION_NAME) { - - // Note: dimension starts from 0 - m_o = new double*[NUM_FUNC]; - m_M = new double**[NUM_FUNC]; - - m_testPoint = new double[m_dimension]; - m_testPointM = new double[m_dimension]; - m_fmax = new double[NUM_FUNC]; - - m_w = new double[NUM_FUNC]; - m_z = new double*[NUM_FUNC]; - m_zM = new double*[NUM_FUNC]; - - for (int i=0; inum_func = NUM_FUNC; - theJob->num_dim = m_dimension; - theJob->C = 2000.0; - for (int i=0; isigma[i] = m_sigma[i]; - theJob->biases[i] = m_func_biases[i]; - theJob->lambda[i] = m_lambda[i]; - } - theJob->o = m_o; - theJob->M = m_M; - theJob->w = m_w; - theJob->z = m_z; - theJob->zM = m_zM; - // Calculate/estimate the fmax for all the functions involved - for (int i=0; inum_func = NUM_FUNC; + theJob->num_dim = m_dimension; + theJob->C = 2000.0; + for (int i=0; isigma[i] = m_sigma[i]; + theJob->biases[i] = m_func_biases[i]; + theJob->lambda[i] = m_lambda[i]; } - Benchmark::rotate(m_testPointM, m_testPoint, m_M[i], m_dimension); - m_fmax[i] = fabs(theJob->basic_func(i, m_testPointM, m_dimension)); - } - theJob->fmax = m_fmax; + theJob->o = m_o; + theJob->M = m_M; + theJob->w = m_w; + theJob->z = m_z; + theJob->zM = m_zM; + // Calculate/estimate the fmax for all the functions involved + for (int i=0; ibasic_func(i, m_testPointM, m_dimension)); + } + theJob->fmax = m_fmax; } // F18RotatedHybridComposition2 @@ -120,85 +132,93 @@ F18RotatedHybridComposition2::F18RotatedHybridComposition2(int dimension, double /** * Destructor */ -F18RotatedHybridComposition2::~F18RotatedHybridComposition2() { - - for (int i=0; i #include -class F18RotatedHybridComposition2 : public TestFunc { +class F18RotatedHybridComposition2 : public TestFunc +{ private: - // Fixed (class) parameters - static const string FUNCTION_NAME; - static const string DEFAULT_FILE_DATA; - static const string DEFAULT_FILE_MX_PREFIX; - static const string DEFAULT_FILE_MX_SUFFIX; - - // Number of functions - static const int NUM_FUNC = 10; - - // Shifted global optimum - double ** m_o; - double *** m_M; - static const double m_sigma[NUM_FUNC]; - static const double m_lambda[NUM_FUNC]; - static const double m_func_biases[NUM_FUNC]; - double * m_testPoint; - double * m_testPointM; - double * m_fmax; - - // In order to avoid excessive memory allocation, - // a fixed memory buffer is allocated for each function object. - double * m_w; - double ** m_z; - double ** m_zM; - - class MyHCJob : public HCJob { - public: - MyHCJob(int numFunc); - double basic_func(int func_no, double* x, int length); - }; - - MyHCJob * theJob; - - string getFileMxName(string prefix, int dimension, string suffix); + // Fixed (class) parameters + static const std::string FUNCTION_NAME; + static const std::string DEFAULT_FILE_DATA; + static const std::string DEFAULT_FILE_MX_PREFIX; + static const std::string DEFAULT_FILE_MX_SUFFIX; + + // Number of functions + static const int NUM_FUNC = 10; + + // Shifted global optimum + double ** m_o; + double *** m_M; + static const double m_sigma[NUM_FUNC]; + static const double m_lambda[NUM_FUNC]; + static const double m_func_biases[NUM_FUNC]; + double * m_testPoint; + double * m_testPointM; + double * m_fmax; + + // In order to avoid excessive memory allocation, + // a fixed memory buffer is allocated for each function object. + double * m_w; + double ** m_z; + double ** m_zM; + + class MyHCJob : public HCJob + { + public: + MyHCJob(int numFunc); + double basic_func(int func_no, double* x, int length); + }; + + MyHCJob * theJob; + + std::string getFileMxName(std::string prefix, int dimension, std::string suffix); public: - F18RotatedHybridComposition2(int dimension, double bias); - F18RotatedHybridComposition2(int dimension, double bias, string file_data, string file_m); - ~F18RotatedHybridComposition2(); + F18RotatedHybridComposition2(int dimension, double bias); + F18RotatedHybridComposition2(int dimension, double bias, std::string file_data, std::string file_m); + ~F18RotatedHybridComposition2(); - double f (double * x); + double f (double * x); }; // F18RotatedHybridComposition2 diff --git a/src/problems/singleObjective/cec2005Competition/F19RotatedHybridComposition2NarrowBasinGlobalOpt.cpp b/src/problems/singleObjective/cec2005Competition/F19RotatedHybridComposition2NarrowBasinGlobalOpt.cpp index 2893edc..a0c761f 100644 --- a/src/problems/singleObjective/cec2005Competition/F19RotatedHybridComposition2NarrowBasinGlobalOpt.cpp +++ b/src/problems/singleObjective/cec2005Competition/F19RotatedHybridComposition2NarrowBasinGlobalOpt.cpp @@ -21,27 +21,31 @@ #include +#include "JMetalHeader.h" // Fixed (class) parameters -const string F19RotatedHybridComposition2NarrowBasinGlobalOpt::FUNCTION_NAME = "Rotated Hybrid Composition Function 2 with narrow basin global optimum"; +const std::string F19RotatedHybridComposition2NarrowBasinGlobalOpt::FUNCTION_NAME = "Rotated Hybrid Composition Function 2 with narrow basin global optimum"; // TODO: Cambiar ruta -const string F19RotatedHybridComposition2NarrowBasinGlobalOpt::DEFAULT_FILE_DATA = "../../data/cec2005CompetitionResources/supportData/hybrid_func2_data.txt"; -const string F19RotatedHybridComposition2NarrowBasinGlobalOpt::DEFAULT_FILE_MX_PREFIX = "../../data/cec2005CompetitionResources/supportData/hybrid_func2_M_D"; -const string F19RotatedHybridComposition2NarrowBasinGlobalOpt::DEFAULT_FILE_MX_SUFFIX = ".txt"; - -const double F19RotatedHybridComposition2NarrowBasinGlobalOpt::m_sigma[NUM_FUNC] = { - 1.0, 2.0, 1.5, 1.5, 1.0, 1.0, - 1.5, 1.5, 2.0, 2.0 +const std::string F19RotatedHybridComposition2NarrowBasinGlobalOpt::DEFAULT_FILE_DATA = "../../data/cec2005CompetitionResources/supportData/hybrid_func2_data.txt"; +const std::string F19RotatedHybridComposition2NarrowBasinGlobalOpt::DEFAULT_FILE_MX_PREFIX = "../../data/cec2005CompetitionResources/supportData/hybrid_func2_M_D"; +const std::string F19RotatedHybridComposition2NarrowBasinGlobalOpt::DEFAULT_FILE_MX_SUFFIX = ".txt"; + +const double F19RotatedHybridComposition2NarrowBasinGlobalOpt::m_sigma[NUM_FUNC] = +{ + 1.0, 2.0, 1.5, 1.5, 1.0, 1.0, + 1.5, 1.5, 2.0, 2.0 }; -const double F19RotatedHybridComposition2NarrowBasinGlobalOpt::m_lambda[NUM_FUNC] = { - 2.0*5.0/32.0, 5.0/32.0, 2.0*1, 1.0, 2.0*5.0/100.0, - 5.0/100.0, 2.0*10.0, 10.0, 2.0*5.0/60.0, 5.0/60.0 +const double F19RotatedHybridComposition2NarrowBasinGlobalOpt::m_lambda[NUM_FUNC] = +{ + 2.0*5.0/32.0, 5.0/32.0, 2.0*1, 1.0, 2.0*5.0/100.0, + 5.0/100.0, 2.0*10.0, 10.0, 2.0*5.0/60.0, 5.0/60.0 }; -const double F19RotatedHybridComposition2NarrowBasinGlobalOpt::m_func_biases[NUM_FUNC] = { - 0.0, 100.0, 200.0, 300.0, 400.0, - 500.0, 600.0, 700.0, 800.0, 900.0 +const double F19RotatedHybridComposition2NarrowBasinGlobalOpt::m_func_biases[NUM_FUNC] = +{ + 0.0, 100.0, 200.0, 300.0, 400.0, + 500.0, 600.0, 700.0, 800.0, 900.0 }; @@ -49,70 +53,78 @@ const double F19RotatedHybridComposition2NarrowBasinGlobalOpt::m_func_biases[NUM * Constructor. */ F19RotatedHybridComposition2NarrowBasinGlobalOpt::F19RotatedHybridComposition2NarrowBasinGlobalOpt(int dimension, double bias) - : F19RotatedHybridComposition2NarrowBasinGlobalOpt(dimension, bias, DEFAULT_FILE_DATA, getFileMxName(DEFAULT_FILE_MX_PREFIX, dimension, DEFAULT_FILE_MX_SUFFIX)) { + : F19RotatedHybridComposition2NarrowBasinGlobalOpt(dimension, bias, DEFAULT_FILE_DATA, getFileMxName(DEFAULT_FILE_MX_PREFIX, dimension, DEFAULT_FILE_MX_SUFFIX)) +{ } // F19RotatedHybridComposition2NarrowBasinGlobalOpt /** * Constructor */ -F19RotatedHybridComposition2NarrowBasinGlobalOpt::F19RotatedHybridComposition2NarrowBasinGlobalOpt(int dimension, double bias, string file_data, string file_m) - : TestFunc(dimension, bias, FUNCTION_NAME) { - - // Note: dimension starts from 0 - m_o = new double*[NUM_FUNC]; - m_M = new double**[NUM_FUNC]; - - m_testPoint = new double[m_dimension]; - m_testPointM = new double[m_dimension]; - m_fmax = new double[NUM_FUNC]; - - m_w = new double[NUM_FUNC]; - m_z = new double*[NUM_FUNC]; - m_zM = new double*[NUM_FUNC]; - - for (int i=0; inum_func = NUM_FUNC; - theJob->num_dim = m_dimension; - theJob->C = 2000.0; - for (int i=0; isigma[i] = m_sigma[i]; - theJob->biases[i] = m_func_biases[i]; - theJob->lambda[i] = m_lambda[i]; - } - theJob->o = m_o; - theJob->M = m_M; - theJob->w = m_w; - theJob->z = m_z; - theJob->zM = m_zM; - // Calculate/estimate the fmax for all the functions involved - for (int i=0; inum_func = NUM_FUNC; + theJob->num_dim = m_dimension; + theJob->C = 2000.0; + for (int i=0; isigma[i] = m_sigma[i]; + theJob->biases[i] = m_func_biases[i]; + theJob->lambda[i] = m_lambda[i]; } - Benchmark::rotate(m_testPointM, m_testPoint, m_M[i], m_dimension); - m_fmax[i] = fabs(theJob->basic_func(i, m_testPointM, m_dimension)); - } - theJob->fmax = m_fmax; + theJob->o = m_o; + theJob->M = m_M; + theJob->w = m_w; + theJob->z = m_z; + theJob->zM = m_zM; + // Calculate/estimate the fmax for all the functions involved + for (int i=0; ibasic_func(i, m_testPointM, m_dimension)); + } + theJob->fmax = m_fmax; } // F19RotatedHybridComposition2NarrowBasinGlobalOpt @@ -120,85 +132,93 @@ F19RotatedHybridComposition2NarrowBasinGlobalOpt::F19RotatedHybridComposition2Na /** * Destructor */ -F19RotatedHybridComposition2NarrowBasinGlobalOpt::~F19RotatedHybridComposition2NarrowBasinGlobalOpt() { - - for (int i=0; i #include -class F19RotatedHybridComposition2NarrowBasinGlobalOpt : public TestFunc { +class F19RotatedHybridComposition2NarrowBasinGlobalOpt : public TestFunc +{ private: - // Fixed (class) parameters - static const string FUNCTION_NAME; - static const string DEFAULT_FILE_DATA; - static const string DEFAULT_FILE_MX_PREFIX; - static const string DEFAULT_FILE_MX_SUFFIX; - - // Number of functions - static const int NUM_FUNC = 10; - - // Shifted global optimum - double ** m_o; - double *** m_M; - static const double m_sigma[NUM_FUNC]; - static const double m_lambda[NUM_FUNC]; - static const double m_func_biases[NUM_FUNC]; - double * m_testPoint; - double * m_testPointM; - double * m_fmax; - - // In order to avoid excessive memory allocation, - // a fixed memory buffer is allocated for each function object. - double * m_w; - double ** m_z; - double ** m_zM; - - class MyHCJob : public HCJob { - public: - MyHCJob(int numFunc); - double basic_func(int func_no, double* x, int length); - }; - - MyHCJob * theJob; - - string getFileMxName(string prefix, int dimension, string suffix); + // Fixed (class) parameters + static const std::string FUNCTION_NAME; + static const std::string DEFAULT_FILE_DATA; + static const std::string DEFAULT_FILE_MX_PREFIX; + static const std::string DEFAULT_FILE_MX_SUFFIX; + + // Number of functions + static const int NUM_FUNC = 10; + + // Shifted global optimum + double ** m_o; + double *** m_M; + static const double m_sigma[NUM_FUNC]; + static const double m_lambda[NUM_FUNC]; + static const double m_func_biases[NUM_FUNC]; + double * m_testPoint; + double * m_testPointM; + double * m_fmax; + + // In order to avoid excessive memory allocation, + // a fixed memory buffer is allocated for each function object. + double * m_w; + double ** m_z; + double ** m_zM; + + class MyHCJob : public HCJob + { + public: + MyHCJob(int numFunc); + double basic_func(int func_no, double* x, int length); + }; + + MyHCJob * theJob; + + std::string getFileMxName(std::string prefix, int dimension, std::string suffix); public: - F19RotatedHybridComposition2NarrowBasinGlobalOpt(int dimension, double bias); - F19RotatedHybridComposition2NarrowBasinGlobalOpt(int dimension, double bias, string file_data, string file_m); - ~F19RotatedHybridComposition2NarrowBasinGlobalOpt(); + F19RotatedHybridComposition2NarrowBasinGlobalOpt(int dimension, double bias); + F19RotatedHybridComposition2NarrowBasinGlobalOpt(int dimension, double bias, std::string file_data, std::string file_m); + ~F19RotatedHybridComposition2NarrowBasinGlobalOpt(); - double f (double * x); + double f (double * x); }; // F19RotatedHybridComposition2NarrowBasinGlobalOpt diff --git a/src/problems/singleObjective/cec2005Competition/F20RotatedHybridComposition2GlobalOptBound.cpp b/src/problems/singleObjective/cec2005Competition/F20RotatedHybridComposition2GlobalOptBound.cpp index eb34695..ebe88a0 100644 --- a/src/problems/singleObjective/cec2005Competition/F20RotatedHybridComposition2GlobalOptBound.cpp +++ b/src/problems/singleObjective/cec2005Competition/F20RotatedHybridComposition2GlobalOptBound.cpp @@ -21,27 +21,31 @@ #include +#include "JMetalHeader.h" // Fixed (class) parameters -const string F20RotatedHybridComposition2GlobalOptBound::FUNCTION_NAME = "Rotated Hybrid Composition Function 2 with Global Optimum on the Bounds"; +const std::string F20RotatedHybridComposition2GlobalOptBound::FUNCTION_NAME = "Rotated Hybrid Composition Function 2 with Global Optimum on the Bounds"; // TODO: Cambiar ruta -const string F20RotatedHybridComposition2GlobalOptBound::DEFAULT_FILE_DATA = "../../data/cec2005CompetitionResources/supportData/hybrid_func2_data.txt"; -const string F20RotatedHybridComposition2GlobalOptBound::DEFAULT_FILE_MX_PREFIX = "../../data/cec2005CompetitionResources/supportData/hybrid_func2_M_D"; -const string F20RotatedHybridComposition2GlobalOptBound::DEFAULT_FILE_MX_SUFFIX = ".txt"; - -const double F20RotatedHybridComposition2GlobalOptBound::m_sigma[NUM_FUNC] = { - 1.0, 2.0, 1.5, 1.5, 1.0, 1.0, - 1.5, 1.5, 2.0, 2.0 +const std::string F20RotatedHybridComposition2GlobalOptBound::DEFAULT_FILE_DATA = "../../data/cec2005CompetitionResources/supportData/hybrid_func2_data.txt"; +const std::string F20RotatedHybridComposition2GlobalOptBound::DEFAULT_FILE_MX_PREFIX = "../../data/cec2005CompetitionResources/supportData/hybrid_func2_M_D"; +const std::string F20RotatedHybridComposition2GlobalOptBound::DEFAULT_FILE_MX_SUFFIX = ".txt"; + +const double F20RotatedHybridComposition2GlobalOptBound::m_sigma[NUM_FUNC] = +{ + 1.0, 2.0, 1.5, 1.5, 1.0, 1.0, + 1.5, 1.5, 2.0, 2.0 }; -const double F20RotatedHybridComposition2GlobalOptBound::m_lambda[NUM_FUNC] = { - 2.0*5.0/32.0, 5.0/32.0, 2.0*1, 1.0, 2.0*5.0/100.0, - 5.0/100.0, 2.0*10.0, 10.0, 2.0*5.0/60.0, 5.0/60.0 +const double F20RotatedHybridComposition2GlobalOptBound::m_lambda[NUM_FUNC] = +{ + 2.0*5.0/32.0, 5.0/32.0, 2.0*1, 1.0, 2.0*5.0/100.0, + 5.0/100.0, 2.0*10.0, 10.0, 2.0*5.0/60.0, 5.0/60.0 }; -const double F20RotatedHybridComposition2GlobalOptBound::m_func_biases[NUM_FUNC] = { - 0.0, 100.0, 200.0, 300.0, 400.0, - 500.0, 600.0, 700.0, 800.0, 900.0 +const double F20RotatedHybridComposition2GlobalOptBound::m_func_biases[NUM_FUNC] = +{ + 0.0, 100.0, 200.0, 300.0, 400.0, + 500.0, 600.0, 700.0, 800.0, 900.0 }; @@ -49,73 +53,82 @@ const double F20RotatedHybridComposition2GlobalOptBound::m_func_biases[NUM_FUNC] * Constructor. */ F20RotatedHybridComposition2GlobalOptBound::F20RotatedHybridComposition2GlobalOptBound(int dimension, double bias) - : F20RotatedHybridComposition2GlobalOptBound(dimension, bias, DEFAULT_FILE_DATA, getFileMxName(DEFAULT_FILE_MX_PREFIX, dimension, DEFAULT_FILE_MX_SUFFIX)) { + : F20RotatedHybridComposition2GlobalOptBound(dimension, bias, DEFAULT_FILE_DATA, getFileMxName(DEFAULT_FILE_MX_PREFIX, dimension, DEFAULT_FILE_MX_SUFFIX)) +{ } // F20RotatedHybridComposition2GlobalOptBound /** * Constructor */ -F20RotatedHybridComposition2GlobalOptBound::F20RotatedHybridComposition2GlobalOptBound(int dimension, double bias, string file_data, string file_m) - : TestFunc(dimension, bias, FUNCTION_NAME) { - - // Note: dimension starts from 0 - m_o = new double*[NUM_FUNC]; - m_M = new double**[NUM_FUNC]; - - m_testPoint = new double[m_dimension]; - m_testPointM = new double[m_dimension]; - m_fmax = new double[NUM_FUNC]; - - m_w = new double[NUM_FUNC]; - m_z = new double*[NUM_FUNC]; - m_zM = new double*[NUM_FUNC]; - - for (int i=0; inum_func = NUM_FUNC; - theJob->num_dim = m_dimension; - theJob->C = 2000.0; - for (int i=0; isigma[i] = m_sigma[i]; - theJob->biases[i] = m_func_biases[i]; - theJob->lambda[i] = m_lambda[i]; - } - theJob->o = m_o; - theJob->M = m_M; - theJob->w = m_w; - theJob->z = m_z; - theJob->zM = m_zM; - // Calculate/estimate the fmax for all the functions involved - for (int i=0; inum_func = NUM_FUNC; + theJob->num_dim = m_dimension; + theJob->C = 2000.0; + for (int i=0; isigma[i] = m_sigma[i]; + theJob->biases[i] = m_func_biases[i]; + theJob->lambda[i] = m_lambda[i]; } - Benchmark::rotate(m_testPointM, m_testPoint, m_M[i], m_dimension); - m_fmax[i] = fabs(theJob->basic_func(i, m_testPointM, m_dimension)); - } - theJob->fmax = m_fmax; + theJob->o = m_o; + theJob->M = m_M; + theJob->w = m_w; + theJob->z = m_z; + theJob->zM = m_zM; + // Calculate/estimate the fmax for all the functions involved + for (int i=0; ibasic_func(i, m_testPointM, m_dimension)); + } + theJob->fmax = m_fmax; } // F20RotatedHybridComposition2GlobalOptBound @@ -123,85 +136,93 @@ F20RotatedHybridComposition2GlobalOptBound::F20RotatedHybridComposition2GlobalOp /** * Destructor */ -F20RotatedHybridComposition2GlobalOptBound::~F20RotatedHybridComposition2GlobalOptBound() { - - for (int i=0; i #include -class F20RotatedHybridComposition2GlobalOptBound : public TestFunc { +class F20RotatedHybridComposition2GlobalOptBound : public TestFunc +{ private: - // Fixed (class) parameters - static const string FUNCTION_NAME; - static const string DEFAULT_FILE_DATA; - static const string DEFAULT_FILE_MX_PREFIX; - static const string DEFAULT_FILE_MX_SUFFIX; - - // Number of functions - static const int NUM_FUNC = 10; - - // Shifted global optimum - double ** m_o; - double *** m_M; - static const double m_sigma[NUM_FUNC]; - static const double m_lambda[NUM_FUNC]; - static const double m_func_biases[NUM_FUNC]; - double * m_testPoint; - double * m_testPointM; - double * m_fmax; - - // In order to avoid excessive memory allocation, - // a fixed memory buffer is allocated for each function object. - double * m_w; - double ** m_z; - double ** m_zM; - - class MyHCJob : public HCJob { - public: - MyHCJob(int numFunc); - double basic_func(int func_no, double* x, int length); - }; - - MyHCJob * theJob; - - string getFileMxName(string prefix, int dimension, string suffix); + // Fixed (class) parameters + static const std::string FUNCTION_NAME; + static const std::string DEFAULT_FILE_DATA; + static const std::string DEFAULT_FILE_MX_PREFIX; + static const std::string DEFAULT_FILE_MX_SUFFIX; + + // Number of functions + static const int NUM_FUNC = 10; + + // Shifted global optimum + double ** m_o; + double *** m_M; + static const double m_sigma[NUM_FUNC]; + static const double m_lambda[NUM_FUNC]; + static const double m_func_biases[NUM_FUNC]; + double * m_testPoint; + double * m_testPointM; + double * m_fmax; + + // In order to avoid excessive memory allocation, + // a fixed memory buffer is allocated for each function object. + double * m_w; + double ** m_z; + double ** m_zM; + + class MyHCJob : public HCJob + { + public: + MyHCJob(int numFunc); + double basic_func(int func_no, double* x, int length); + }; + + MyHCJob * theJob; + + std::string getFileMxName(std::string prefix, int dimension, std::string suffix); public: - F20RotatedHybridComposition2GlobalOptBound(int dimension, double bias); - F20RotatedHybridComposition2GlobalOptBound(int dimension, double bias, string file_data, string file_m); - ~F20RotatedHybridComposition2GlobalOptBound(); + F20RotatedHybridComposition2GlobalOptBound(int dimension, double bias); + F20RotatedHybridComposition2GlobalOptBound(int dimension, double bias, std::string file_data, std::string file_m); + ~F20RotatedHybridComposition2GlobalOptBound(); - double f (double * x); + double f (double * x); }; // F20RotatedHybridComposition2GlobalOptBound diff --git a/src/problems/singleObjective/cec2005Competition/F21RotatedHybridComposition3.cpp b/src/problems/singleObjective/cec2005Competition/F21RotatedHybridComposition3.cpp index 1570ec5..5005f57 100644 --- a/src/problems/singleObjective/cec2005Competition/F21RotatedHybridComposition3.cpp +++ b/src/problems/singleObjective/cec2005Competition/F21RotatedHybridComposition3.cpp @@ -21,27 +21,31 @@ #include +#include "JMetalHeader.h" // Fixed (class) parameters -const string F21RotatedHybridComposition3::FUNCTION_NAME = "Rotated Hybrid Composition Function 3"; +const std::string F21RotatedHybridComposition3::FUNCTION_NAME = "Rotated Hybrid Composition Function 3"; // TODO: Cambiar ruta -const string F21RotatedHybridComposition3::DEFAULT_FILE_DATA = "../../data/cec2005CompetitionResources/supportData/hybrid_func3_data.txt"; -const string F21RotatedHybridComposition3::DEFAULT_FILE_MX_PREFIX = "../../data/cec2005CompetitionResources/supportData/hybrid_func3_M_D"; -const string F21RotatedHybridComposition3::DEFAULT_FILE_MX_SUFFIX = ".txt"; - -const double F21RotatedHybridComposition3::m_sigma[NUM_FUNC] = { - 1.0, 1.0, 1.0, 1.0, 1.0, - 2.0, 2.0, 2.0, 2.0, 2.0 +const std::string F21RotatedHybridComposition3::DEFAULT_FILE_DATA = "../../data/cec2005CompetitionResources/supportData/hybrid_func3_data.txt"; +const std::string F21RotatedHybridComposition3::DEFAULT_FILE_MX_PREFIX = "../../data/cec2005CompetitionResources/supportData/hybrid_func3_M_D"; +const std::string F21RotatedHybridComposition3::DEFAULT_FILE_MX_SUFFIX = ".txt"; + +const double F21RotatedHybridComposition3::m_sigma[NUM_FUNC] = +{ + 1.0, 1.0, 1.0, 1.0, 1.0, + 2.0, 2.0, 2.0, 2.0, 2.0 }; -const double F21RotatedHybridComposition3::m_lambda[NUM_FUNC] = { +const double F21RotatedHybridComposition3::m_lambda[NUM_FUNC] = +{ 5.0*5.0/100.0, 5.0/100.0, 5.0*1.0, 1.0, 5.0*1.0, 1.0, 5.0*10.0, 10.0, 5.0*5.0/200.0, 5.0/200.0 }; -const double F21RotatedHybridComposition3::m_func_biases[NUM_FUNC] = { - 0.0, 100.0, 200.0, 300.0, 400.0, - 500.0, 600.0, 700.0, 800.0, 900.0 +const double F21RotatedHybridComposition3::m_func_biases[NUM_FUNC] = +{ + 0.0, 100.0, 200.0, 300.0, 400.0, + 500.0, 600.0, 700.0, 800.0, 900.0 }; @@ -49,67 +53,74 @@ const double F21RotatedHybridComposition3::m_func_biases[NUM_FUNC] = { * Constructor. */ F21RotatedHybridComposition3::F21RotatedHybridComposition3(int dimension, double bias) - : F21RotatedHybridComposition3(dimension, bias, DEFAULT_FILE_DATA, getFileMxName(DEFAULT_FILE_MX_PREFIX, dimension, DEFAULT_FILE_MX_SUFFIX)) { + : F21RotatedHybridComposition3(dimension, bias, DEFAULT_FILE_DATA, getFileMxName(DEFAULT_FILE_MX_PREFIX, dimension, DEFAULT_FILE_MX_SUFFIX)) +{ } // F21RotatedHybridComposition3 /** * Constructor */ -F21RotatedHybridComposition3::F21RotatedHybridComposition3(int dimension, double bias, string file_data, string file_m) - : TestFunc(dimension, bias, FUNCTION_NAME) { - - // Note: dimension starts from 0 - m_o = new double*[NUM_FUNC]; - m_M = new double**[NUM_FUNC]; - - m_testPoint = new double[m_dimension]; - m_testPointM = new double[m_dimension]; - m_fmax = new double[NUM_FUNC]; - - m_w = new double[NUM_FUNC]; - m_z = new double*[NUM_FUNC]; - m_zM = new double*[NUM_FUNC]; - - for (int i=0; inum_func = NUM_FUNC; + theJob->num_dim = m_dimension; + theJob->C = 2000.0; + for (int i=0; isigma[i] = m_sigma[i]; + theJob->biases[i] = m_func_biases[i]; + theJob->lambda[i] = m_lambda[i]; } - } - - // Load the shifted global optimum - Benchmark::loadMatrixFromFile(file_data, NUM_FUNC, m_dimension, m_o); - // Load the matrix - Benchmark::loadNMatrixFromFile(file_m, NUM_FUNC, m_dimension, m_dimension, m_M); - - // Initialize the hybrid composition job object - theJob = new MyHCJob(NUM_FUNC); - theJob->num_func = NUM_FUNC; - theJob->num_dim = m_dimension; - theJob->C = 2000.0; - for (int i=0; isigma[i] = m_sigma[i]; - theJob->biases[i] = m_func_biases[i]; - theJob->lambda[i] = m_lambda[i]; - } - theJob->o = m_o; - theJob->M = m_M; - theJob->w = m_w; - theJob->z = m_z; - theJob->zM = m_zM; - // Calculate/estimate the fmax for all the functions involved - for (int i=0; io = m_o; + theJob->M = m_M; + theJob->w = m_w; + theJob->z = m_z; + theJob->zM = m_zM; + // Calculate/estimate the fmax for all the functions involved + for (int i=0; ibasic_func(i, m_testPointM, m_dimension)); } - Benchmark::rotate(m_testPointM, m_testPoint, m_M[i], m_dimension); - m_fmax[i] = fabs(theJob->basic_func(i, m_testPointM, m_dimension)); - } - theJob->fmax = m_fmax; + theJob->fmax = m_fmax; } // F21RotatedHybridComposition3 @@ -117,85 +128,93 @@ F21RotatedHybridComposition3::F21RotatedHybridComposition3(int dimension, double /** * Destructor */ -F21RotatedHybridComposition3::~F21RotatedHybridComposition3() { - - for (int i=0; i #include -class F21RotatedHybridComposition3 : public TestFunc { +class F21RotatedHybridComposition3 : public TestFunc +{ private: - // Fixed (class) parameters - static const string FUNCTION_NAME; - static const string DEFAULT_FILE_DATA; - static const string DEFAULT_FILE_MX_PREFIX; - static const string DEFAULT_FILE_MX_SUFFIX; - - // Number of functions - static const int NUM_FUNC = 10; - - // Shifted global optimum - double ** m_o; - double *** m_M; - static const double m_sigma[NUM_FUNC]; - static const double m_lambda[NUM_FUNC]; - static const double m_func_biases[NUM_FUNC]; - double * m_testPoint; - double * m_testPointM; - double * m_fmax; - - // In order to avoid excessive memory allocation, - // a fixed memory buffer is allocated for each function object. - double * m_w; - double ** m_z; - double ** m_zM; - - class MyHCJob : public HCJob { - public: - MyHCJob(int numFunc); - double basic_func(int func_no, double* x, int length); - }; - - MyHCJob * theJob; - - string getFileMxName(string prefix, int dimension, string suffix); + // Fixed (class) parameters + static const std::string FUNCTION_NAME; + static const std::string DEFAULT_FILE_DATA; + static const std::string DEFAULT_FILE_MX_PREFIX; + static const std::string DEFAULT_FILE_MX_SUFFIX; + + // Number of functions + static const int NUM_FUNC = 10; + + // Shifted global optimum + double ** m_o; + double *** m_M; + static const double m_sigma[NUM_FUNC]; + static const double m_lambda[NUM_FUNC]; + static const double m_func_biases[NUM_FUNC]; + double * m_testPoint; + double * m_testPointM; + double * m_fmax; + + // In order to avoid excessive memory allocation, + // a fixed memory buffer is allocated for each function object. + double * m_w; + double ** m_z; + double ** m_zM; + + class MyHCJob : public HCJob + { + public: + MyHCJob(int numFunc); + double basic_func(int func_no, double* x, int length); + }; + + MyHCJob * theJob; + + std::string getFileMxName(std::string prefix, int dimension, std::string suffix); public: - F21RotatedHybridComposition3(int dimension, double bias); - F21RotatedHybridComposition3(int dimension, double bias, string file_data, string file_m); - ~F21RotatedHybridComposition3(); + F21RotatedHybridComposition3(int dimension, double bias); + F21RotatedHybridComposition3(int dimension, double bias, std::string file_data, std::string file_m); + ~F21RotatedHybridComposition3(); - double f (double * x); + double f (double * x); }; // F21RotatedHybridComposition3 diff --git a/src/problems/singleObjective/cec2005Competition/F22RotatedHybridComposition3HighCondNumMatrix.cpp b/src/problems/singleObjective/cec2005Competition/F22RotatedHybridComposition3HighCondNumMatrix.cpp index aeec872..3ce148c 100644 --- a/src/problems/singleObjective/cec2005Competition/F22RotatedHybridComposition3HighCondNumMatrix.cpp +++ b/src/problems/singleObjective/cec2005Competition/F22RotatedHybridComposition3HighCondNumMatrix.cpp @@ -21,27 +21,31 @@ #include +#include "JMetalHeader.h" // Fixed (class) parameters -const string F22RotatedHybridComposition3HighCondNumMatrix::FUNCTION_NAME = "Rotated Hybrid Composition Function 3 with High Condition Number Matrix"; +const std::string F22RotatedHybridComposition3HighCondNumMatrix::FUNCTION_NAME = "Rotated Hybrid Composition Function 3 with High Condition Number Matrix"; // TODO: Cambiar ruta -const string F22RotatedHybridComposition3HighCondNumMatrix::DEFAULT_FILE_DATA = "../../data/cec2005CompetitionResources/supportData/hybrid_func3_data.txt"; -const string F22RotatedHybridComposition3HighCondNumMatrix::DEFAULT_FILE_MX_PREFIX = "../../data/cec2005CompetitionResources/supportData/hybrid_func3_HM_D"; -const string F22RotatedHybridComposition3HighCondNumMatrix::DEFAULT_FILE_MX_SUFFIX = ".txt"; - -const double F22RotatedHybridComposition3HighCondNumMatrix::m_sigma[NUM_FUNC] = { - 1.0, 1.0, 1.0, 1.0, 1.0, - 2.0, 2.0, 2.0, 2.0, 2.0 +const std::string F22RotatedHybridComposition3HighCondNumMatrix::DEFAULT_FILE_DATA = "../../data/cec2005CompetitionResources/supportData/hybrid_func3_data.txt"; +const std::string F22RotatedHybridComposition3HighCondNumMatrix::DEFAULT_FILE_MX_PREFIX = "../../data/cec2005CompetitionResources/supportData/hybrid_func3_HM_D"; +const std::string F22RotatedHybridComposition3HighCondNumMatrix::DEFAULT_FILE_MX_SUFFIX = ".txt"; + +const double F22RotatedHybridComposition3HighCondNumMatrix::m_sigma[NUM_FUNC] = +{ + 1.0, 1.0, 1.0, 1.0, 1.0, + 2.0, 2.0, 2.0, 2.0, 2.0 }; -const double F22RotatedHybridComposition3HighCondNumMatrix::m_lambda[NUM_FUNC] = { +const double F22RotatedHybridComposition3HighCondNumMatrix::m_lambda[NUM_FUNC] = +{ 5.0*5.0/100.0, 5.0/100.0, 5.0*1.0, 1.0, 5.0*1.0, 1.0, 5.0*10.0, 10.0, 5.0*5.0/200.0, 5.0/200.0 }; -const double F22RotatedHybridComposition3HighCondNumMatrix::m_func_biases[NUM_FUNC] = { - 0.0, 100.0, 200.0, 300.0, 400.0, - 500.0, 600.0, 700.0, 800.0, 900.0 +const double F22RotatedHybridComposition3HighCondNumMatrix::m_func_biases[NUM_FUNC] = +{ + 0.0, 100.0, 200.0, 300.0, 400.0, + 500.0, 600.0, 700.0, 800.0, 900.0 }; @@ -49,67 +53,74 @@ const double F22RotatedHybridComposition3HighCondNumMatrix::m_func_biases[NUM_FU * Constructor. */ F22RotatedHybridComposition3HighCondNumMatrix::F22RotatedHybridComposition3HighCondNumMatrix(int dimension, double bias) - : F22RotatedHybridComposition3HighCondNumMatrix(dimension, bias, DEFAULT_FILE_DATA, getFileMxName(DEFAULT_FILE_MX_PREFIX, dimension, DEFAULT_FILE_MX_SUFFIX)) { + : F22RotatedHybridComposition3HighCondNumMatrix(dimension, bias, DEFAULT_FILE_DATA, getFileMxName(DEFAULT_FILE_MX_PREFIX, dimension, DEFAULT_FILE_MX_SUFFIX)) +{ } // F22RotatedHybridComposition3HighCondNumMatrix /** * Constructor */ -F22RotatedHybridComposition3HighCondNumMatrix::F22RotatedHybridComposition3HighCondNumMatrix(int dimension, double bias, string file_data, string file_m) - : TestFunc(dimension, bias, FUNCTION_NAME) { - - // Note: dimension starts from 0 - m_o = new double*[NUM_FUNC]; - m_M = new double**[NUM_FUNC]; - - m_testPoint = new double[m_dimension]; - m_testPointM = new double[m_dimension]; - m_fmax = new double[NUM_FUNC]; - - m_w = new double[NUM_FUNC]; - m_z = new double*[NUM_FUNC]; - m_zM = new double*[NUM_FUNC]; - - for (int i=0; inum_func = NUM_FUNC; + theJob->num_dim = m_dimension; + theJob->C = 2000.0; + for (int i=0; isigma[i] = m_sigma[i]; + theJob->biases[i] = m_func_biases[i]; + theJob->lambda[i] = m_lambda[i]; } - } - - // Load the shifted global optimum - Benchmark::loadMatrixFromFile(file_data, NUM_FUNC, m_dimension, m_o); - // Load the matrix - Benchmark::loadNMatrixFromFile(file_m, NUM_FUNC, m_dimension, m_dimension, m_M); - - // Initialize the hybrid composition job object - theJob = new MyHCJob(NUM_FUNC); - theJob->num_func = NUM_FUNC; - theJob->num_dim = m_dimension; - theJob->C = 2000.0; - for (int i=0; isigma[i] = m_sigma[i]; - theJob->biases[i] = m_func_biases[i]; - theJob->lambda[i] = m_lambda[i]; - } - theJob->o = m_o; - theJob->M = m_M; - theJob->w = m_w; - theJob->z = m_z; - theJob->zM = m_zM; - // Calculate/estimate the fmax for all the functions involved - for (int i=0; io = m_o; + theJob->M = m_M; + theJob->w = m_w; + theJob->z = m_z; + theJob->zM = m_zM; + // Calculate/estimate the fmax for all the functions involved + for (int i=0; ibasic_func(i, m_testPointM, m_dimension)); } - Benchmark::rotate(m_testPointM, m_testPoint, m_M[i], m_dimension); - m_fmax[i] = fabs(theJob->basic_func(i, m_testPointM, m_dimension)); - } - theJob->fmax = m_fmax; + theJob->fmax = m_fmax; } // F22RotatedHybridComposition3HighCondNumMatrix @@ -117,85 +128,93 @@ F22RotatedHybridComposition3HighCondNumMatrix::F22RotatedHybridComposition3HighC /** * Destructor */ -F22RotatedHybridComposition3HighCondNumMatrix::~F22RotatedHybridComposition3HighCondNumMatrix() { - - for (int i=0; i #include -class F22RotatedHybridComposition3HighCondNumMatrix : public TestFunc { +class F22RotatedHybridComposition3HighCondNumMatrix : public TestFunc +{ private: - // Fixed (class) parameters - static const string FUNCTION_NAME; - static const string DEFAULT_FILE_DATA; - static const string DEFAULT_FILE_MX_PREFIX; - static const string DEFAULT_FILE_MX_SUFFIX; - - // Number of functions - static const int NUM_FUNC = 10; - - // Shifted global optimum - double ** m_o; - double *** m_M; - static const double m_sigma[NUM_FUNC]; - static const double m_lambda[NUM_FUNC]; - static const double m_func_biases[NUM_FUNC]; - double * m_testPoint; - double * m_testPointM; - double * m_fmax; - - // In order to avoid excessive memory allocation, - // a fixed memory buffer is allocated for each function object. - double * m_w; - double ** m_z; - double ** m_zM; - - class MyHCJob : public HCJob { - public: - MyHCJob(int numFunc); - double basic_func(int func_no, double* x, int length); - }; - - MyHCJob * theJob; - - string getFileMxName(string prefix, int dimension, string suffix); + // Fixed (class) parameters + static const std::string FUNCTION_NAME; + static const std::string DEFAULT_FILE_DATA; + static const std::string DEFAULT_FILE_MX_PREFIX; + static const std::string DEFAULT_FILE_MX_SUFFIX; + + // Number of functions + static const int NUM_FUNC = 10; + + // Shifted global optimum + double ** m_o; + double *** m_M; + static const double m_sigma[NUM_FUNC]; + static const double m_lambda[NUM_FUNC]; + static const double m_func_biases[NUM_FUNC]; + double * m_testPoint; + double * m_testPointM; + double * m_fmax; + + // In order to avoid excessive memory allocation, + // a fixed memory buffer is allocated for each function object. + double * m_w; + double ** m_z; + double ** m_zM; + + class MyHCJob : public HCJob + { + public: + MyHCJob(int numFunc); + double basic_func(int func_no, double* x, int length); + }; + + MyHCJob * theJob; + + std::string getFileMxName(std::string prefix, int dimension, std::string suffix); public: - F22RotatedHybridComposition3HighCondNumMatrix(int dimension, double bias); - F22RotatedHybridComposition3HighCondNumMatrix(int dimension, double bias, string file_data, string file_m); - ~F22RotatedHybridComposition3HighCondNumMatrix(); + F22RotatedHybridComposition3HighCondNumMatrix(int dimension, double bias); + F22RotatedHybridComposition3HighCondNumMatrix(int dimension, double bias, std::string file_data, std::string file_m); + ~F22RotatedHybridComposition3HighCondNumMatrix(); - double f (double * x); + double f (double * x); }; // F22RotatedHybridComposition3HighCondNumMatrix diff --git a/src/problems/singleObjective/cec2005Competition/F23NoncontinuousRotatedHybridComposition3.cpp b/src/problems/singleObjective/cec2005Competition/F23NoncontinuousRotatedHybridComposition3.cpp index fbbbcc4..9d8a541 100644 --- a/src/problems/singleObjective/cec2005Competition/F23NoncontinuousRotatedHybridComposition3.cpp +++ b/src/problems/singleObjective/cec2005Competition/F23NoncontinuousRotatedHybridComposition3.cpp @@ -21,27 +21,31 @@ #include +#include "JMetalHeader.h" // Fixed (class) parameters -const string F23NoncontinuousRotatedHybridComposition3::FUNCTION_NAME = "Non-Continuous Rotated Hybrid Composition Function 3"; +const std::string F23NoncontinuousRotatedHybridComposition3::FUNCTION_NAME = "Non-Continuous Rotated Hybrid Composition Function 3"; // TODO: Cambiar ruta -const string F23NoncontinuousRotatedHybridComposition3::DEFAULT_FILE_DATA = "../../data/cec2005CompetitionResources/supportData/hybrid_func3_data.txt"; -const string F23NoncontinuousRotatedHybridComposition3::DEFAULT_FILE_MX_PREFIX = "../../data/cec2005CompetitionResources/supportData/hybrid_func3_M_D"; -const string F23NoncontinuousRotatedHybridComposition3::DEFAULT_FILE_MX_SUFFIX = ".txt"; - -const double F23NoncontinuousRotatedHybridComposition3::m_sigma[NUM_FUNC] = { - 1.0, 1.0, 1.0, 1.0, 1.0, - 2.0, 2.0, 2.0, 2.0, 2.0 +const std::string F23NoncontinuousRotatedHybridComposition3::DEFAULT_FILE_DATA = "../../data/cec2005CompetitionResources/supportData/hybrid_func3_data.txt"; +const std::string F23NoncontinuousRotatedHybridComposition3::DEFAULT_FILE_MX_PREFIX = "../../data/cec2005CompetitionResources/supportData/hybrid_func3_M_D"; +const std::string F23NoncontinuousRotatedHybridComposition3::DEFAULT_FILE_MX_SUFFIX = ".txt"; + +const double F23NoncontinuousRotatedHybridComposition3::m_sigma[NUM_FUNC] = +{ + 1.0, 1.0, 1.0, 1.0, 1.0, + 2.0, 2.0, 2.0, 2.0, 2.0 }; -const double F23NoncontinuousRotatedHybridComposition3::m_lambda[NUM_FUNC] = { +const double F23NoncontinuousRotatedHybridComposition3::m_lambda[NUM_FUNC] = +{ 5.0*5.0/100.0, 5.0/100.0, 5.0*1.0, 1.0, 5.0*1.0, 1.0, 5.0*10.0, 10.0, 5.0*5.0/200.0, 5.0/200.0 }; -const double F23NoncontinuousRotatedHybridComposition3::m_func_biases[NUM_FUNC] = { - 0.0, 100.0, 200.0, 300.0, 400.0, - 500.0, 600.0, 700.0, 800.0, 900.0 +const double F23NoncontinuousRotatedHybridComposition3::m_func_biases[NUM_FUNC] = +{ + 0.0, 100.0, 200.0, 300.0, 400.0, + 500.0, 600.0, 700.0, 800.0, 900.0 }; @@ -49,67 +53,74 @@ const double F23NoncontinuousRotatedHybridComposition3::m_func_biases[NUM_FUNC] * Constructor. */ F23NoncontinuousRotatedHybridComposition3::F23NoncontinuousRotatedHybridComposition3(int dimension, double bias) - : F23NoncontinuousRotatedHybridComposition3(dimension, bias, DEFAULT_FILE_DATA, getFileMxName(DEFAULT_FILE_MX_PREFIX, dimension, DEFAULT_FILE_MX_SUFFIX)) { + : F23NoncontinuousRotatedHybridComposition3(dimension, bias, DEFAULT_FILE_DATA, getFileMxName(DEFAULT_FILE_MX_PREFIX, dimension, DEFAULT_FILE_MX_SUFFIX)) +{ } // F23NoncontinuousRotatedHybridComposition3 /** * Constructor */ -F23NoncontinuousRotatedHybridComposition3::F23NoncontinuousRotatedHybridComposition3(int dimension, double bias, string file_data, string file_m) - : TestFunc(dimension, bias, FUNCTION_NAME) { - - // Note: dimension starts from 0 - m_o = new double*[NUM_FUNC]; - m_M = new double**[NUM_FUNC]; - - m_testPoint = new double[m_dimension]; - m_testPointM = new double[m_dimension]; - m_fmax = new double[NUM_FUNC]; - - m_w = new double[NUM_FUNC]; - m_z = new double*[NUM_FUNC]; - m_zM = new double*[NUM_FUNC]; - - for (int i=0; inum_func = NUM_FUNC; + theJob->num_dim = m_dimension; + theJob->C = 2000.0; + for (int i=0; isigma[i] = m_sigma[i]; + theJob->biases[i] = m_func_biases[i]; + theJob->lambda[i] = m_lambda[i]; } - } - - // Load the shifted global optimum - Benchmark::loadMatrixFromFile(file_data, NUM_FUNC, m_dimension, m_o); - // Load the matrix - Benchmark::loadNMatrixFromFile(file_m, NUM_FUNC, m_dimension, m_dimension, m_M); - - // Initialize the hybrid composition job object - theJob = new MyHCJob(NUM_FUNC); - theJob->num_func = NUM_FUNC; - theJob->num_dim = m_dimension; - theJob->C = 2000.0; - for (int i=0; isigma[i] = m_sigma[i]; - theJob->biases[i] = m_func_biases[i]; - theJob->lambda[i] = m_lambda[i]; - } - theJob->o = m_o; - theJob->M = m_M; - theJob->w = m_w; - theJob->z = m_z; - theJob->zM = m_zM; - // Calculate/estimate the fmax for all the functions involved - for (int i=0; io = m_o; + theJob->M = m_M; + theJob->w = m_w; + theJob->z = m_z; + theJob->zM = m_zM; + // Calculate/estimate the fmax for all the functions involved + for (int i=0; ibasic_func(i, m_testPointM, m_dimension)); } - Benchmark::rotate(m_testPointM, m_testPoint, m_M[i], m_dimension); - m_fmax[i] = fabs(theJob->basic_func(i, m_testPointM, m_dimension)); - } - theJob->fmax = m_fmax; + theJob->fmax = m_fmax; } // F23NoncontinuousRotatedHybridComposition3 @@ -117,89 +128,98 @@ F23NoncontinuousRotatedHybridComposition3::F23NoncontinuousRotatedHybridComposit /** * Destructor */ -F23NoncontinuousRotatedHybridComposition3::~F23NoncontinuousRotatedHybridComposition3() { - - for (int i=0; i #include -class F23NoncontinuousRotatedHybridComposition3 : public TestFunc { +class F23NoncontinuousRotatedHybridComposition3 : public TestFunc +{ private: - // Fixed (class) parameters - static const string FUNCTION_NAME; - static const string DEFAULT_FILE_DATA; - static const string DEFAULT_FILE_MX_PREFIX; - static const string DEFAULT_FILE_MX_SUFFIX; - - // Number of functions - static const int NUM_FUNC = 10; - - // Shifted global optimum - double ** m_o; - double *** m_M; - static const double m_sigma[NUM_FUNC]; - static const double m_lambda[NUM_FUNC]; - static const double m_func_biases[NUM_FUNC]; - double * m_testPoint; - double * m_testPointM; - double * m_fmax; - - // In order to avoid excessive memory allocation, - // a fixed memory buffer is allocated for each function object. - double * m_w; - double ** m_z; - double ** m_zM; - - class MyHCJob : public HCJob { - public: - MyHCJob(int numFunc); - double basic_func(int func_no, double* x, int length); - }; - - MyHCJob * theJob; - - string getFileMxName(string prefix, int dimension, string suffix); + // Fixed (class) parameters + static const std::string FUNCTION_NAME; + static const std::string DEFAULT_FILE_DATA; + static const std::string DEFAULT_FILE_MX_PREFIX; + static const std::string DEFAULT_FILE_MX_SUFFIX; + + // Number of functions + static const int NUM_FUNC = 10; + + // Shifted global optimum + double ** m_o; + double *** m_M; + static const double m_sigma[NUM_FUNC]; + static const double m_lambda[NUM_FUNC]; + static const double m_func_biases[NUM_FUNC]; + double * m_testPoint; + double * m_testPointM; + double * m_fmax; + + // In order to avoid excessive memory allocation, + // a fixed memory buffer is allocated for each function object. + double * m_w; + double ** m_z; + double ** m_zM; + + class MyHCJob : public HCJob + { + public: + MyHCJob(int numFunc); + double basic_func(int func_no, double* x, int length); + }; + + MyHCJob * theJob; + + std::string getFileMxName(std::string prefix, int dimension, std::string suffix); public: - F23NoncontinuousRotatedHybridComposition3(int dimension, double bias); - F23NoncontinuousRotatedHybridComposition3(int dimension, double bias, string file_data, string file_m); - ~F23NoncontinuousRotatedHybridComposition3(); + F23NoncontinuousRotatedHybridComposition3(int dimension, double bias); + F23NoncontinuousRotatedHybridComposition3(int dimension, double bias, std::string file_data, std::string file_m); + ~F23NoncontinuousRotatedHybridComposition3(); - double f (double * x); + double f (double * x); }; // F23NoncontinuousRotatedHybridComposition3 diff --git a/src/problems/singleObjective/cec2005Competition/F24RotatedHybridComposition4.cpp b/src/problems/singleObjective/cec2005Competition/F24RotatedHybridComposition4.cpp index 657139e..54066c3 100644 --- a/src/problems/singleObjective/cec2005Competition/F24RotatedHybridComposition4.cpp +++ b/src/problems/singleObjective/cec2005Competition/F24RotatedHybridComposition4.cpp @@ -21,27 +21,31 @@ #include +#include "JMetalHeader.h" // Fixed (class) parameters -const string F24RotatedHybridComposition4::FUNCTION_NAME = "Rotated Hybrid Composition Function 4"; +const std::string F24RotatedHybridComposition4::FUNCTION_NAME = "Rotated Hybrid Composition Function 4"; // TODO: Cambiar ruta -const string F24RotatedHybridComposition4::DEFAULT_FILE_DATA = "../../data/cec2005CompetitionResources/supportData/hybrid_func4_data.txt"; -const string F24RotatedHybridComposition4::DEFAULT_FILE_MX_PREFIX = "../../data/cec2005CompetitionResources/supportData/hybrid_func4_M_D"; -const string F24RotatedHybridComposition4::DEFAULT_FILE_MX_SUFFIX = ".txt"; - -const double F24RotatedHybridComposition4::m_sigma[NUM_FUNC] = { - 2.0, 2.0, 2.0, 2.0, 2.0, - 2.0, 2.0, 2.0, 2.0, 2.0 +const std::string F24RotatedHybridComposition4::DEFAULT_FILE_DATA = "../../data/cec2005CompetitionResources/supportData/hybrid_func4_data.txt"; +const std::string F24RotatedHybridComposition4::DEFAULT_FILE_MX_PREFIX = "../../data/cec2005CompetitionResources/supportData/hybrid_func4_M_D"; +const std::string F24RotatedHybridComposition4::DEFAULT_FILE_MX_SUFFIX = ".txt"; + +const double F24RotatedHybridComposition4::m_sigma[NUM_FUNC] = +{ + 2.0, 2.0, 2.0, 2.0, 2.0, + 2.0, 2.0, 2.0, 2.0, 2.0 }; -const double F24RotatedHybridComposition4::m_lambda[NUM_FUNC] = { +const double F24RotatedHybridComposition4::m_lambda[NUM_FUNC] = +{ 10.0, 5.0/20.0, 1.0, 5.0/32.0, 1.0, 5.0/100.0, 5.0/50.0, 1.0, 5.0/100.0, 5.0/100.0 }; -const double F24RotatedHybridComposition4::m_func_biases[NUM_FUNC] = { - 0.0, 100.0, 200.0, 300.0, 400.0, - 500.0, 600.0, 700.0, 800.0, 900.0 +const double F24RotatedHybridComposition4::m_func_biases[NUM_FUNC] = +{ + 0.0, 100.0, 200.0, 300.0, 400.0, + 500.0, 600.0, 700.0, 800.0, 900.0 }; @@ -49,67 +53,74 @@ const double F24RotatedHybridComposition4::m_func_biases[NUM_FUNC] = { * Constructor. */ F24RotatedHybridComposition4::F24RotatedHybridComposition4(int dimension, double bias) - : F24RotatedHybridComposition4(dimension, bias, DEFAULT_FILE_DATA, getFileMxName(DEFAULT_FILE_MX_PREFIX, dimension, DEFAULT_FILE_MX_SUFFIX)) { + : F24RotatedHybridComposition4(dimension, bias, DEFAULT_FILE_DATA, getFileMxName(DEFAULT_FILE_MX_PREFIX, dimension, DEFAULT_FILE_MX_SUFFIX)) +{ } // F24RotatedHybridComposition4 /** * Constructor */ -F24RotatedHybridComposition4::F24RotatedHybridComposition4(int dimension, double bias, string file_data, string file_m) - : TestFunc(dimension, bias, FUNCTION_NAME) { - - // Note: dimension starts from 0 - m_o = new double*[NUM_FUNC]; - m_M = new double**[NUM_FUNC]; - - m_testPoint = new double[m_dimension]; - m_testPointM = new double[m_dimension]; - m_fmax = new double[NUM_FUNC]; - - m_w = new double[NUM_FUNC]; - m_z = new double*[NUM_FUNC]; - m_zM = new double*[NUM_FUNC]; - - for (int i=0; inum_func = NUM_FUNC; + theJob->num_dim = m_dimension; + theJob->C = 2000.0; + for (int i=0; isigma[i] = m_sigma[i]; + theJob->biases[i] = m_func_biases[i]; + theJob->lambda[i] = m_lambda[i]; } - } - - // Load the shifted global optimum - Benchmark::loadMatrixFromFile(file_data, NUM_FUNC, m_dimension, m_o); - // Load the matrix - Benchmark::loadNMatrixFromFile(file_m, NUM_FUNC, m_dimension, m_dimension, m_M); - - // Initialize the hybrid composition job object - theJob = new MyHCJob(NUM_FUNC); - theJob->num_func = NUM_FUNC; - theJob->num_dim = m_dimension; - theJob->C = 2000.0; - for (int i=0; isigma[i] = m_sigma[i]; - theJob->biases[i] = m_func_biases[i]; - theJob->lambda[i] = m_lambda[i]; - } - theJob->o = m_o; - theJob->M = m_M; - theJob->w = m_w; - theJob->z = m_z; - theJob->zM = m_zM; - // Calculate/estimate the fmax for all the functions involved - for (int i=0; io = m_o; + theJob->M = m_M; + theJob->w = m_w; + theJob->z = m_z; + theJob->zM = m_zM; + // Calculate/estimate the fmax for all the functions involved + for (int i=0; ibasic_func(i, m_testPointM, m_dimension)); } - Benchmark::rotate(m_testPointM, m_testPoint, m_M[i], m_dimension); - m_fmax[i] = fabs(theJob->basic_func(i, m_testPointM, m_dimension)); - } - theJob->fmax = m_fmax; + theJob->fmax = m_fmax; } // F24RotatedHybridComposition4 @@ -117,95 +128,103 @@ F24RotatedHybridComposition4::F24RotatedHybridComposition4(int dimension, double /** * Destructor */ -F24RotatedHybridComposition4::~F24RotatedHybridComposition4() { - - for (int i=0; i #include -class F24RotatedHybridComposition4 : public TestFunc { +class F24RotatedHybridComposition4 : public TestFunc +{ private: - // Fixed (class) parameters - static const string FUNCTION_NAME; - static const string DEFAULT_FILE_DATA; - static const string DEFAULT_FILE_MX_PREFIX; - static const string DEFAULT_FILE_MX_SUFFIX; - - // Number of functions - static const int NUM_FUNC = 10; - - // Shifted global optimum - double ** m_o; - double *** m_M; - static const double m_sigma[NUM_FUNC]; - static const double m_lambda[NUM_FUNC]; - static const double m_func_biases[NUM_FUNC]; - double * m_testPoint; - double * m_testPointM; - double * m_fmax; - - // In order to avoid excessive memory allocation, - // a fixed memory buffer is allocated for each function object. - double * m_w; - double ** m_z; - double ** m_zM; - - class MyHCJob : public HCJob { - public: - MyHCJob(int numFunc); - double basic_func(int func_no, double* x, int length); - }; - - MyHCJob * theJob; - - string getFileMxName(string prefix, int dimension, string suffix); + // Fixed (class) parameters + static const std::string FUNCTION_NAME; + static const std::string DEFAULT_FILE_DATA; + static const std::string DEFAULT_FILE_MX_PREFIX; + static const std::string DEFAULT_FILE_MX_SUFFIX; + + // Number of functions + static const int NUM_FUNC = 10; + + // Shifted global optimum + double ** m_o; + double *** m_M; + static const double m_sigma[NUM_FUNC]; + static const double m_lambda[NUM_FUNC]; + static const double m_func_biases[NUM_FUNC]; + double * m_testPoint; + double * m_testPointM; + double * m_fmax; + + // In order to avoid excessive memory allocation, + // a fixed memory buffer is allocated for each function object. + double * m_w; + double ** m_z; + double ** m_zM; + + class MyHCJob : public HCJob + { + public: + MyHCJob(int numFunc); + double basic_func(int func_no, double* x, int length); + }; + + MyHCJob * theJob; + + std::string getFileMxName(std::string prefix, int dimension, std::string suffix); public: - F24RotatedHybridComposition4(int dimension, double bias); - F24RotatedHybridComposition4(int dimension, double bias, string file_data, string file_m); - ~F24RotatedHybridComposition4(); + F24RotatedHybridComposition4(int dimension, double bias); + F24RotatedHybridComposition4(int dimension, double bias, std::string file_data, std::string file_m); + ~F24RotatedHybridComposition4(); - double f (double * x); + double f (double * x); }; // F24RotatedHybridComposition4 diff --git a/src/problems/singleObjective/cec2005Competition/F25RotatedHybridComposition4Bound.cpp b/src/problems/singleObjective/cec2005Competition/F25RotatedHybridComposition4Bound.cpp index 9e25487..06cbed5 100644 --- a/src/problems/singleObjective/cec2005Competition/F25RotatedHybridComposition4Bound.cpp +++ b/src/problems/singleObjective/cec2005Competition/F25RotatedHybridComposition4Bound.cpp @@ -21,27 +21,31 @@ #include +#include "JMetalHeader.h" // Fixed (class) parameters -const string F25RotatedHybridComposition4Bound::FUNCTION_NAME = "Rotated Hybrid Composition Function 4 without bounds"; +const std::string F25RotatedHybridComposition4Bound::FUNCTION_NAME = "Rotated Hybrid Composition Function 4 without bounds"; // TODO: Cambiar ruta -const string F25RotatedHybridComposition4Bound::DEFAULT_FILE_DATA = "../../data/cec2005CompetitionResources/supportData/hybrid_func4_data.txt"; -const string F25RotatedHybridComposition4Bound::DEFAULT_FILE_MX_PREFIX = "../../data/cec2005CompetitionResources/supportData/hybrid_func4_M_D"; -const string F25RotatedHybridComposition4Bound::DEFAULT_FILE_MX_SUFFIX = ".txt"; - -const double F25RotatedHybridComposition4Bound::m_sigma[NUM_FUNC] = { - 2.0, 2.0, 2.0, 2.0, 2.0, - 2.0, 2.0, 2.0, 2.0, 2.0 +const std::string F25RotatedHybridComposition4Bound::DEFAULT_FILE_DATA = "../../data/cec2005CompetitionResources/supportData/hybrid_func4_data.txt"; +const std::string F25RotatedHybridComposition4Bound::DEFAULT_FILE_MX_PREFIX = "../../data/cec2005CompetitionResources/supportData/hybrid_func4_M_D"; +const std::string F25RotatedHybridComposition4Bound::DEFAULT_FILE_MX_SUFFIX = ".txt"; + +const double F25RotatedHybridComposition4Bound::m_sigma[NUM_FUNC] = +{ + 2.0, 2.0, 2.0, 2.0, 2.0, + 2.0, 2.0, 2.0, 2.0, 2.0 }; -const double F25RotatedHybridComposition4Bound::m_lambda[NUM_FUNC] = { +const double F25RotatedHybridComposition4Bound::m_lambda[NUM_FUNC] = +{ 10.0, 5.0/20.0, 1.0, 5.0/32.0, 1.0, 5.0/100.0, 5.0/50.0, 1.0, 5.0/100.0, 5.0/100.0 }; -const double F25RotatedHybridComposition4Bound::m_func_biases[NUM_FUNC] = { - 0.0, 100.0, 200.0, 300.0, 400.0, - 500.0, 600.0, 700.0, 800.0, 900.0 +const double F25RotatedHybridComposition4Bound::m_func_biases[NUM_FUNC] = +{ + 0.0, 100.0, 200.0, 300.0, 400.0, + 500.0, 600.0, 700.0, 800.0, 900.0 }; @@ -49,67 +53,74 @@ const double F25RotatedHybridComposition4Bound::m_func_biases[NUM_FUNC] = { * Constructor. */ F25RotatedHybridComposition4Bound::F25RotatedHybridComposition4Bound(int dimension, double bias) - : F25RotatedHybridComposition4Bound(dimension, bias, DEFAULT_FILE_DATA, getFileMxName(DEFAULT_FILE_MX_PREFIX, dimension, DEFAULT_FILE_MX_SUFFIX)) { + : F25RotatedHybridComposition4Bound(dimension, bias, DEFAULT_FILE_DATA, getFileMxName(DEFAULT_FILE_MX_PREFIX, dimension, DEFAULT_FILE_MX_SUFFIX)) +{ } // F25RotatedHybridComposition4Bound /** * Constructor */ -F25RotatedHybridComposition4Bound::F25RotatedHybridComposition4Bound(int dimension, double bias, string file_data, string file_m) - : TestFunc(dimension, bias, FUNCTION_NAME) { - - // Note: dimension starts from 0 - m_o = new double*[NUM_FUNC]; - m_M = new double**[NUM_FUNC]; - - m_testPoint = new double[m_dimension]; - m_testPointM = new double[m_dimension]; - m_fmax = new double[NUM_FUNC]; - - m_w = new double[NUM_FUNC]; - m_z = new double*[NUM_FUNC]; - m_zM = new double*[NUM_FUNC]; - - for (int i=0; inum_func = NUM_FUNC; + theJob->num_dim = m_dimension; + theJob->C = 2000.0; + for (int i=0; isigma[i] = m_sigma[i]; + theJob->biases[i] = m_func_biases[i]; + theJob->lambda[i] = m_lambda[i]; } - } - - // Load the shifted global optimum - Benchmark::loadMatrixFromFile(file_data, NUM_FUNC, m_dimension, m_o); - // Load the matrix - Benchmark::loadNMatrixFromFile(file_m, NUM_FUNC, m_dimension, m_dimension, m_M); - - // Initialize the hybrid composition job object - theJob = new MyHCJob(NUM_FUNC); - theJob->num_func = NUM_FUNC; - theJob->num_dim = m_dimension; - theJob->C = 2000.0; - for (int i=0; isigma[i] = m_sigma[i]; - theJob->biases[i] = m_func_biases[i]; - theJob->lambda[i] = m_lambda[i]; - } - theJob->o = m_o; - theJob->M = m_M; - theJob->w = m_w; - theJob->z = m_z; - theJob->zM = m_zM; - // Calculate/estimate the fmax for all the functions involved - for (int i=0; io = m_o; + theJob->M = m_M; + theJob->w = m_w; + theJob->z = m_z; + theJob->zM = m_zM; + // Calculate/estimate the fmax for all the functions involved + for (int i=0; ibasic_func(i, m_testPointM, m_dimension)); } - Benchmark::rotate(m_testPointM, m_testPoint, m_M[i], m_dimension); - m_fmax[i] = fabs(theJob->basic_func(i, m_testPointM, m_dimension)); - } - theJob->fmax = m_fmax; + theJob->fmax = m_fmax; } // F25RotatedHybridComposition4Bound @@ -117,95 +128,103 @@ F25RotatedHybridComposition4Bound::F25RotatedHybridComposition4Bound(int dimensi /** * Destructor */ -F25RotatedHybridComposition4Bound::~F25RotatedHybridComposition4Bound() { - - for (int i=0; i #include -class F25RotatedHybridComposition4Bound : public TestFunc { +class F25RotatedHybridComposition4Bound : public TestFunc +{ private: - // Fixed (class) parameters - static const string FUNCTION_NAME; - static const string DEFAULT_FILE_DATA; - static const string DEFAULT_FILE_MX_PREFIX; - static const string DEFAULT_FILE_MX_SUFFIX; - - // Number of functions - static const int NUM_FUNC = 10; - - // Shifted global optimum - double ** m_o; - double *** m_M; - static const double m_sigma[NUM_FUNC]; - static const double m_lambda[NUM_FUNC]; - static const double m_func_biases[NUM_FUNC]; - double * m_testPoint; - double * m_testPointM; - double * m_fmax; - - // In order to avoid excessive memory allocation, - // a fixed memory buffer is allocated for each function object. - double * m_w; - double ** m_z; - double ** m_zM; - - class MyHCJob : public HCJob { - public: - MyHCJob(int numFunc); - double basic_func(int func_no, double* x, int length); - }; - - MyHCJob * theJob; - - string getFileMxName(string prefix, int dimension, string suffix); + // Fixed (class) parameters + static const std::string FUNCTION_NAME; + static const std::string DEFAULT_FILE_DATA; + static const std::string DEFAULT_FILE_MX_PREFIX; + static const std::string DEFAULT_FILE_MX_SUFFIX; + + // Number of functions + static const int NUM_FUNC = 10; + + // Shifted global optimum + double ** m_o; + double *** m_M; + static const double m_sigma[NUM_FUNC]; + static const double m_lambda[NUM_FUNC]; + static const double m_func_biases[NUM_FUNC]; + double * m_testPoint; + double * m_testPointM; + double * m_fmax; + + // In order to avoid excessive memory allocation, + // a fixed memory buffer is allocated for each function object. + double * m_w; + double ** m_z; + double ** m_zM; + + class MyHCJob : public HCJob + { + public: + MyHCJob(int numFunc); + double basic_func(int func_no, double* x, int length); + }; + + MyHCJob * theJob; + + std::string getFileMxName(std::string prefix, int dimension, std::string suffix); public: - F25RotatedHybridComposition4Bound(int dimension, double bias); - F25RotatedHybridComposition4Bound(int dimension, double bias, string file_data, string file_m); - ~F25RotatedHybridComposition4Bound(); + F25RotatedHybridComposition4Bound(int dimension, double bias); + F25RotatedHybridComposition4Bound(int dimension, double bias, std::string file_data, std::string file_m); + ~F25RotatedHybridComposition4Bound(); - double f (double * x); + double f (double * x); }; // F25RotatedHybridComposition4Bound diff --git a/src/problems/singleObjective/cec2005Competition/HCJob.cpp b/src/problems/singleObjective/cec2005Competition/HCJob.cpp index c2f3927..618f963 100644 --- a/src/problems/singleObjective/cec2005Competition/HCJob.cpp +++ b/src/problems/singleObjective/cec2005Competition/HCJob.cpp @@ -21,21 +21,24 @@ #include +#include "JMetalHeader.h" /** * Constructor. */ -HCJob::HCJob(int numFunc) { - sigma = new double[numFunc]; - biases = new double[numFunc]; - lambda = new double[numFunc]; +HCJob::HCJob(int numFunc) +{ + sigma = snew double[numFunc]; + biases = snew double[numFunc]; + lambda = snew double[numFunc]; } // HCJob /** * Destructor */ -HCJob::~HCJob() { - delete [] sigma; - delete [] biases; - delete [] lambda; +HCJob::~HCJob() +{ + delete [] sigma; + delete [] biases; + delete [] lambda; } diff --git a/src/problems/singleObjective/cec2005Competition/HCJob.h b/src/problems/singleObjective/cec2005Competition/HCJob.h index 8442e1c..7029327 100644 --- a/src/problems/singleObjective/cec2005Competition/HCJob.h +++ b/src/problems/singleObjective/cec2005Competition/HCJob.h @@ -22,37 +22,38 @@ #ifndef __H_C_JOB__ #define __H_C_JOB__ -class HCJob { +class HCJob +{ public: - // Number of basic functions - int num_func; - // Number of dimensions - int num_dim; - - // Predefined constant - double C; - // Coverage range for each basic function - double* sigma; - // Biases for each basic function - double* biases; - // Stretch / compress each basic function - double* lambda; - // Estimated fmax - double* fmax; - // Shift global optimum for each basic function - double** o; - // Linear transformation matrix for each basic function - double*** M; - - // Working areas to avoid memory allocation operations - double* w; - double** z; - double** zM; - HCJob(int numFunc); - virtual ~HCJob(); - virtual double basic_func(int func_no, double* x, int length) = 0; + // Number of basic functions + int num_func; + // Number of dimensions + int num_dim; + + // Predefined constant + double C; + // Coverage range for each basic function + double* sigma; + // Biases for each basic function + double* biases; + // Stretch / compress each basic function + double* lambda; + // Estimated fmax + double* fmax; + // Shift global optimum for each basic function + double** o; + // Linear transformation matrix for each basic function + double*** M; + + // Working areas to avoid memory allocation operations + double* w; + double** z; + double** zM; + HCJob(int numFunc); + virtual ~HCJob(); + virtual double basic_func(int func_no, double* x, int length) = 0; }; // HCJob diff --git a/src/problems/singleObjective/cec2005Competition/TestFunc.cpp b/src/problems/singleObjective/cec2005Competition/TestFunc.cpp index e6c4a60..6f0d157 100644 --- a/src/problems/singleObjective/cec2005Competition/TestFunc.cpp +++ b/src/problems/singleObjective/cec2005Competition/TestFunc.cpp @@ -25,32 +25,38 @@ /** * Constructor. */ -TestFunc::TestFunc(int dimension, double bias) : TestFunc(dimension, bias, "undefined") { +TestFunc::TestFunc(int dimension, double bias) : TestFunc(dimension, bias, "undefined") +{ } // TestFunc /** * Constructor */ -TestFunc::TestFunc(int dimension, double bias, string func_name) { - m_dimension = dimension; - m_bias = bias; - m_func_name = func_name; +TestFunc::TestFunc(int dimension, double bias, std::string func_name) +{ + m_dimension = dimension; + m_bias = bias; + m_func_name = func_name; } // TestFunc /** * Destructor */ -TestFunc::~TestFunc() { +TestFunc::~TestFunc() +{ } // ~TestFunc -int TestFunc::dimension() { - return (m_dimension); +int TestFunc::dimension() +{ + return (m_dimension); } // dimension -double TestFunc::bias() { - return (m_bias); +double TestFunc::bias() +{ + return (m_bias); } // bias -string TestFunc::name() { - return (m_func_name); +std::string TestFunc::name() +{ + return (m_func_name); } // name diff --git a/src/problems/singleObjective/cec2005Competition/TestFunc.h b/src/problems/singleObjective/cec2005Competition/TestFunc.h index aa9f4f2..177a5bf 100644 --- a/src/problems/singleObjective/cec2005Competition/TestFunc.h +++ b/src/problems/singleObjective/cec2005Competition/TestFunc.h @@ -26,21 +26,22 @@ using namespace std; -class TestFunc { +class TestFunc +{ protected: - int m_dimension; - double m_bias; - string m_func_name; + int m_dimension; + double m_bias; + string m_func_name; public: - TestFunc(int dimension, double bias); - TestFunc(int dimension, double bias, string func_name); - virtual ~TestFunc(); - virtual double f(double * x) = 0; - int dimension(); - double bias(); - string name(); + TestFunc(int dimension, double bias); + TestFunc(int dimension, double bias, string func_name); + virtual ~TestFunc(); + virtual double f(double * x) = 0; + int dimension(); + double bias(); + string name(); }; // TestFunc diff --git a/src/qualityIndicator/CMakeLists.txt b/src/qualityIndicator/CMakeLists.txt new file mode 100644 index 0000000..ef24757 --- /dev/null +++ b/src/qualityIndicator/CMakeLists.txt @@ -0,0 +1,6 @@ +file(GLOB SOURCES "*.cpp" "*.h") +ListToString(SOURCES ";" ${SOURCES}) +LIST_APPEND("${SOURCES}") +add_subdirectory(fastHypervolume) +add_subdirectory(main) +add_subdirectory(util) \ No newline at end of file diff --git a/src/qualityIndicator/Epsilon.cpp b/src/qualityIndicator/Epsilon.cpp index 584306a..b24411b 100644 --- a/src/qualityIndicator/Epsilon.cpp +++ b/src/qualityIndicator/Epsilon.cpp @@ -26,16 +26,18 @@ * Constructor * Creates a new instance of a Epsilon object */ -Epsilon::Epsilon() { - utils_ = new MetricsUtil(); +Epsilon::Epsilon() +{ + utils_ = snew MetricsUtil(); } // Epsilon /** * Destructor */ -Epsilon::~Epsilon() { - delete utils_; +Epsilon::~Epsilon() +{ + delete utils_; } // ~Epsilon @@ -45,86 +47,95 @@ Epsilon::~Epsilon() { * @param a. Solution front * @return the value of the epsilon indicator */ -double Epsilon::epsilon(vector > b, vector > a, - int dim) { - - int i, j, k; - double eps, eps_j = 0.0, eps_k=0.0, eps_temp; - - dim_ = dim; - set_params() ; - - if (method_ == 0) - eps = -std::numeric_limits::max(); - else - eps= 0; - - for (i = 0; i < a.size(); i++) { - for (j = 0; j < b.size(); j++) { - for (k = 0; k < dim_; k++) { - switch (method_) { - case 0: - if (obj_[k] == 0) - eps_temp = b[j][k] - a[i][k]; - //eps_temp = b[j * dim_ + k] - a[i * dim_ + k]; - else - eps_temp = a[i][k] - b[j][k]; - //eps_temp = a[i * dim_ + k] - b[j * dim_ + k]; - break; - default: - if ( (a[i][k] < 0 && b[j][k] > 0) || - (a[i][k] > 0 && b[j][k] < 0) || - (a[i][k] == 0 || b[j][k] == 0)) { - //if ( (a[i * dim_ + k] < 0 && b[j * dim_ + k] > 0) || - // (a[i * dim_ + k] > 0 && b[j * dim_ + k] < 0) || - // (a[i * dim_ + k] == 0 || b[j * dim_ + k] == 0)) { - cout << "error in data file" << endl; - exit(-1); +double Epsilon::epsilon(MatrixOfDouble b, MatrixOfDouble a, + int dim) +{ + + int i, j, k; + double eps, eps_j = 0.0, eps_k=0.0, eps_temp; + + dim_ = dim; + set_params() ; + + if (method_ == 0) + eps = -std::numeric_limits::max(); + else + eps= 0; + + for (i = 0; i < a.size(); i++) + { + for (j = 0; j < b.size(); j++) + { + for (k = 0; k < dim_; k++) + { + switch (method_) + { + case 0: + if (obj_[k] == 0) + eps_temp = b[j][k] - a[i][k]; + //eps_temp = b[j * dim_ + k] - a[i * dim_ + k]; + else + eps_temp = a[i][k] - b[j][k]; + //eps_temp = a[i * dim_ + k] - b[j * dim_ + k]; + break; + default: + if ( (a[i][k] < 0 && b[j][k] > 0) || + (a[i][k] > 0 && b[j][k] < 0) || + (a[i][k] == 0 || b[j][k] == 0)) + { + //if ( (a[i * dim_ + k] < 0 && b[j * dim_ + k] > 0) || + // (a[i * dim_ + k] > 0 && b[j * dim_ + k] < 0) || + // (a[i * dim_ + k] == 0 || b[j * dim_ + k] == 0)) { + std::cout << "error in data file" << std::endl; + exit(-1); + } + if (obj_[k] == 0) + eps_temp = b[j][k] / a[i][k]; + //eps_temp = b[j * dim_ + k] / a[i * dim_ + k]; + else + eps_temp = a[i][k] / b[j][k]; + //eps_temp = a[i * dim_ + k] / b[j * dim_ + k]; + break; + } + if (k == 0) + eps_k = eps_temp; + else if (eps_k < eps_temp) + eps_k = eps_temp; } - if (obj_[k] == 0) - eps_temp = b[j][k] / a[i][k]; - //eps_temp = b[j * dim_ + k] / a[i * dim_ + k]; - else - eps_temp = a[i][k] / b[j][k]; - //eps_temp = a[i * dim_ + k] / b[j * dim_ + k]; - break; + if (j == 0) + eps_j = eps_k; + else if (eps_j > eps_k) + eps_j = eps_k; } - if (k == 0) - eps_k = eps_temp; - else if (eps_k < eps_temp) - eps_k = eps_temp; - } - if (j == 0) - eps_j = eps_k; - else if (eps_j > eps_k) - eps_j = eps_k; + if (i == 0) + eps = eps_j; + else if (eps < eps_j) + eps = eps_j; } - if (i == 0) - eps = eps_j; - else if (eps < eps_j) - eps = eps_j; - } - free_params(); - return eps; + free_params(); + return eps; } // epsilon /** * Established the params by default */ -void Epsilon::set_params() { - int i; - obj_ = new int[dim_]; - for (i = 0; i < dim_; i++) { - obj_[i] = 0; - } - method_ = 0; +void Epsilon::set_params() +{ + int i; + obj_ = snew int[dim_]; + for (i = 0; i < dim_; i++) + { + obj_[i] = 0; + } + method_ = 0; } // set_params /** * Free the reserved memory for the params */ -void Epsilon::free_params() { - delete [] obj_; +void Epsilon::free_params() +{ + delete [] obj_; } // set_params diff --git a/src/qualityIndicator/Epsilon.h b/src/qualityIndicator/Epsilon.h index 63ede22..6e0bef9 100644 --- a/src/qualityIndicator/Epsilon.h +++ b/src/qualityIndicator/Epsilon.h @@ -24,6 +24,7 @@ #include #include + /** * This class implements the unary epsilon additive indicator as proposed in * E. Zitzler, E. Thiele, L. Laummanns, M., Fonseca, C., and Grunert da Fonseca. @@ -34,26 +35,29 @@ * $java jmetal.qualityIndicator.Epsilon */ -class Epsilon { +using namespace JMetal; + +class Epsilon +{ private: - int dim_; // stores the number of objectives - int * obj_; // obj_[i]=0 means objective i is to be minimized. This code always supposes - //the minimization of all the objectives - int method_; // method_ = 0 means apply additive epsilon and method_ = 1 means multiplicative - // epsilon. This code always apply additive epsilon + int dim_; // stores the number of objectives + int * obj_; // obj_[i]=0 means objective i is to be minimized. This code always supposes + //the minimization of all the objectives + int method_; // method_ = 0 means apply additive epsilon and method_ = 1 means multiplicative + // epsilon. This code always apply additive epsilon - void set_params(); - void free_params(); + void set_params(); + void free_params(); public: - MetricsUtil * utils_; // stores a reference to qualityIndicatorUtils + MetricsUtil * utils_; // stores a reference to qualityIndicatorUtils - Epsilon(); - ~Epsilon(); - double epsilon(vector > b, vector< vector > a, int dim); + Epsilon(); + ~Epsilon(); + double epsilon(MatrixOfDouble b, MatrixOfDouble a, int dim); }; // Epsilon diff --git a/src/qualityIndicator/Fitness.cpp b/src/qualityIndicator/Fitness.cpp index fece2f8..6655879 100644 --- a/src/qualityIndicator/Fitness.cpp +++ b/src/qualityIndicator/Fitness.cpp @@ -26,16 +26,18 @@ * Constructor * Creates a new instance of a Fitness object */ -Fitness::Fitness() { - utils_ = new MetricsUtil(); +Fitness::Fitness() +{ + utils_ = snew MetricsUtil(); } // Fitness /** * Destructor */ -Fitness::~Fitness() { - delete utils_; +Fitness::~Fitness() +{ + delete utils_; } // ~Fitness @@ -45,18 +47,22 @@ Fitness::~Fitness() { * @param a. Solution front * @return the value of the epsilon indicator */ -void Fitness::fitness(vector > a, string file) { - std::fstream out(file.c_str(), std::ios::out | std::ios::app); - for (int i=0; i a, std::string file) +{ + std::fstream out(file.c_str(), std::ios::out | std::ios::app); + for (int i=0; i #include -using namespace std; -class Fitness { + +class Fitness +{ private: public: - MetricsUtil * utils_; // stores a reference to qualityIndicatorUtils + MetricsUtil * utils_; // stores a reference to qualityIndicatorUtils - Fitness(); - ~Fitness(); - void fitness(vector > a, string file); + Fitness(); + ~Fitness(); + void fitness(std::vector a, std::string file); }; // Fitness diff --git a/src/qualityIndicator/GenerationalDistance.cpp b/src/qualityIndicator/GenerationalDistance.cpp index 86ed277..9c33b4d 100644 --- a/src/qualityIndicator/GenerationalDistance.cpp +++ b/src/qualityIndicator/GenerationalDistance.cpp @@ -31,16 +31,18 @@ const double GenerationalDistance::pow_ = 2.0; * Constructor. * Creates a new instance of the generational distance metric. */ -GenerationalDistance::GenerationalDistance() { - utils_ = new MetricsUtil(); +GenerationalDistance::GenerationalDistance() +{ + utils_ = snew MetricsUtil(); } // GenerationalDistance /** * Destructor */ -GenerationalDistance::~GenerationalDistance() { - delete utils_; +GenerationalDistance::~GenerationalDistance() +{ + delete utils_; } // ~GenerationalDistance @@ -49,56 +51,57 @@ GenerationalDistance::~GenerationalDistance() { * @param front The front * @param trueParetoFront The true pareto front */ -double GenerationalDistance::generationalDistance(vector< vector > front, - vector< vector > trueParetoFront, int numberOfObjectives) { - - /** - * Stores the maximum values of true pareto front. - */ - vector maximumValue; - - /** - * Stores the minimum values of the true pareto front. - */ - vector minimumValue; - - /** - * Stores the normalized front. - */ - vector< vector > normalizedFront; - - /** - * Stores the normalized true Pareto front. - */ - vector< vector > normalizedParetoFront ; - - // STEP 1. Obtain the maximum and minimum values of the Pareto front - maximumValue = utils_->getMaximumValues(trueParetoFront, numberOfObjectives); - minimumValue = utils_->getMinimumValues(trueParetoFront, numberOfObjectives); - - // STEP 2. Get the normalized front and true Pareto fronts - normalizedFront = utils_->getNormalizedFront(front, - maximumValue, - minimumValue); - normalizedParetoFront = utils_->getNormalizedFront(trueParetoFront, - maximumValue, - minimumValue); - - // STEP 3. Sum the distances between each point of the front and the - // nearest point in the true Pareto front - double sum = 0.0; - for (int i = 0; i < front.size(); i++) - sum += pow(utils_->distanceToClosedPoint(normalizedFront[i], - normalizedParetoFront), - pow_); - - - // STEP 4. Obtain the sqrt of the sum - sum = pow(sum,1.0/pow_); - - // STEP 5. Divide the sum by the maximum number of points of the front - double generationalDistance = sum / normalizedFront.size(); - - return generationalDistance; +double GenerationalDistance::generationalDistance(MatrixOfDouble front, + MatrixOfDouble trueParetoFront, int numberOfObjectives) +{ + + /** + * Stores the maximum values of true pareto front. + */ + VectorOfDouble maximumValue; + + /** + * Stores the minimum values of the true pareto front. + */ + VectorOfDouble minimumValue; + + /** + * Stores the normalized front. + */ + MatrixOfDouble normalizedFront; + + /** + * Stores the normalized true Pareto front. + */ + MatrixOfDouble normalizedParetoFront ; + + // STEP 1. Obtain the maximum and minimum values of the Pareto front + maximumValue = utils_->getMaximumValues(trueParetoFront, numberOfObjectives); + minimumValue = utils_->getMinimumValues(trueParetoFront, numberOfObjectives); + + // STEP 2. Get the normalized front and true Pareto fronts + normalizedFront = utils_->getNormalizedFront(front, + maximumValue, + minimumValue); + normalizedParetoFront = utils_->getNormalizedFront(trueParetoFront, + maximumValue, + minimumValue); + + // STEP 3. Sum the distances between each point of the front and the + // nearest point in the true Pareto front + double sum = 0.0; + for (int i = 0; i < front.size(); i++) + sum += pow(utils_->distanceToClosedPoint(normalizedFront[i], + normalizedParetoFront), + pow_); + + + // STEP 4. Obtain the sqrt of the sum + sum = pow(sum,1.0/pow_); + + // STEP 5. Divide the sum by the maximum number of points of the front + double generationalDistance = sum / normalizedFront.size(); + + return generationalDistance; } // generationalDistance diff --git a/src/qualityIndicator/GenerationalDistance.h b/src/qualityIndicator/GenerationalDistance.h index 91be1b0..41de6ab 100644 --- a/src/qualityIndicator/GenerationalDistance.h +++ b/src/qualityIndicator/GenerationalDistance.h @@ -36,19 +36,20 @@ * Inst. Technol. (1998) */ -class GenerationalDistance { +class GenerationalDistance +{ private: - static const double pow_; + static const double pow_; public: - MetricsUtil * utils_; + MetricsUtil * utils_; - GenerationalDistance(); - ~GenerationalDistance(); - double generationalDistance(vector< vector > front, - vector< vector > trueParetoFront, int numberOfObjectives); + GenerationalDistance(); + ~GenerationalDistance(); + double generationalDistance(MatrixOfDouble front, + MatrixOfDouble trueParetoFront, int numberOfObjectives); }; diff --git a/src/qualityIndicator/Hypervolume.cpp b/src/qualityIndicator/Hypervolume.cpp index 42e3bc0..a0b186a 100644 --- a/src/qualityIndicator/Hypervolume.cpp +++ b/src/qualityIndicator/Hypervolume.cpp @@ -25,16 +25,18 @@ * Constructor * Creates a new instance of Hypervolume */ -Hypervolume::Hypervolume() { - utils_ = new MetricsUtil(); +Hypervolume::Hypervolume() +{ + utils_ = snew MetricsUtil(); } // Hypervolume /** * Destructor */ -Hypervolume::~Hypervolume() { - delete utils_; +Hypervolume::~Hypervolume() +{ + delete utils_; } // ~Hypervolume @@ -42,27 +44,31 @@ Hypervolume::~Hypervolume() { * returns true if 'point1' dominates 'points2' with respect to the * to the first 'noObjectives' objectives */ -bool Hypervolume::dominates(double* point1, double* point2, int noObjectives) { +bool Hypervolume::dominates(double* point1, double* point2, int noObjectives) +{ - int i; - bool betterInAnyObjective = false; + int i; + bool betterInAnyObjective = false; - for (i = 0; i < noObjectives && point1[i] >= point2[i]; i++) { - if (point1[i] > point2[i]) { - betterInAnyObjective = true; - } // if - } // for + for (i = 0; i < noObjectives && point1[i] >= point2[i]; i++) + { + if (point1[i] > point2[i]) + { + betterInAnyObjective = true; + } // if + } // for - return ((i >= noObjectives) && betterInAnyObjective); + return ((i >= noObjectives) && betterInAnyObjective); } // dominates -void Hypervolume::swap(double** front, int i, int j) { +void Hypervolume::swap(double** front, int i, int j) +{ - double* temp = front[i]; - front[i] = front[j]; - front[j] = temp; + double* temp = front[i]; + front[i] = front[j]; + front[j] = temp; } // swap @@ -74,36 +80,44 @@ void Hypervolume::swap(double** front, int i, int j) { * the nondominated points; n is returned */ int Hypervolume::filterNondominatedSet(double** front, int noPoints, - int noObjectives) { - - int i, j; - int n; - - n = noPoints; - i = 0; - - while (i < n) { - j = i + 1; - while (j < n) { - if (dominates(front[i], front[j], noObjectives)) { - /* remove point 'j' */ - n--; - swap(front, j, n); - } else if (dominates(front[j], front[i], noObjectives)) { - /* remove point 'i'; ensure that the point copied to index 'i' - is considered in the next outer loop (thus, decrement i) */ - n--; - swap(front, i, n); - i--; - break; - } else { - j++; - } + int noObjectives) +{ + + int i, j; + int n; + + n = noPoints; + i = 0; + + while (i < n) + { + j = i + 1; + while (j < n) + { + if (dominates(front[i], front[j], noObjectives)) + { + /* remove point 'j' */ + n--; + swap(front, j, n); + } + else if (dominates(front[j], front[i], noObjectives)) + { + /* remove point 'i'; ensure that the point copied to index 'i' + is considered in the next outer loop (thus, decrement i) */ + n--; + swap(front, i, n); + i--; + break; + } + else + { + j++; + } + } // while + i++; } // while - i++; - } // while - return n; + return n; } // filterNondominatedSet @@ -113,25 +127,29 @@ int Hypervolume::filterNondominatedSet(double** front, int noPoints, * points referenced in 'front[0..noPoints-1]' */ double Hypervolume::surfaceUnchangedTo(double** front, int noPoints, - int objective) { + int objective) +{ - int i; - double minValue, value; + int i; + double minValue, value; - if (noPoints < 1) { - cout << "run-time error" << endl; - exit(-1); - } + if (noPoints < 1) + { + std::cout << "run-time error" << std::endl; + exit(-1); + } - minValue = front[0][objective]; - for (i = 1; i < noPoints; i++) { - value = front[i][objective]; - if (value < minValue) { - minValue = value; + minValue = front[0][objective]; + for (i = 1; i < noPoints; i++) + { + value = front[i][objective]; + if (value < minValue) + { + minValue = value; + } } - } - - return minValue; + + return minValue; } // surfaceUnchangedTo @@ -143,59 +161,68 @@ double Hypervolume::surfaceUnchangedTo(double** front, int noPoints, * 'front[0..n-1]' contains the remaining points; 'n' is returned */ int Hypervolume::reduceNondominatedSet(double** front, int noPoints, - int objective, double threshold) { + int objective, double threshold) +{ - int n; - int i; + int n; + int i; - n = noPoints; - for (i = 0; i < n; i++) { - if (front[i][objective] <= threshold) { - n--; - swap(front, i, n); - } // if - } // for + n = noPoints; + for (i = 0; i < n; i++) + { + if (front[i][objective] <= threshold) + { + n--; + swap(front, i, n); + } // if + } // for - return n; + return n; } // ReduceNondominatedSet double Hypervolume::calculateHypervolume(double** front, int noPoints, - int noObjectives) { - - int n; - double volume, distance; - - volume = 0; - distance = 0; - n = noPoints; - while (n > 0) { - - int noNondominatedPoints; - double tempVolume, tempDistance; + int noObjectives) +{ + + int n; + double volume, distance; + + volume = 0; + distance = 0; + n = noPoints; + while (n > 0) + { + + int noNondominatedPoints; + double tempVolume, tempDistance; + + noNondominatedPoints = filterNondominatedSet(front, n, noObjectives - 1); + tempVolume = 0; + if (noObjectives < 3) + { + if (noNondominatedPoints < 1) + { + std::cout << "run-time error" << std::endl; + exit(-1); + } // if + tempVolume = front[0][0]; + } + else + { + tempVolume = calculateHypervolume(front, + noNondominatedPoints, + noObjectives - 1); + } // if + + tempDistance = surfaceUnchangedTo(front, n, noObjectives - 1); + volume += tempVolume * (tempDistance - distance); + distance = tempDistance; + n = reduceNondominatedSet(front, n, noObjectives - 1, distance); + } // while - noNondominatedPoints = filterNondominatedSet(front, n, noObjectives - 1); - tempVolume = 0; - if (noObjectives < 3) { - if (noNondominatedPoints < 1) { - cout << "run-time error" << endl; - exit(-1); - } // if - tempVolume = front[0][0]; - } else { - tempVolume = calculateHypervolume(front, - noNondominatedPoints, - noObjectives - 1); - } // if - - tempDistance = surfaceUnchangedTo(front, n, noObjectives - 1); - volume += tempVolume * (tempDistance - distance); - distance = tempDistance; - n = reduceNondominatedSet(front, n, noObjectives - 1, distance); - } // while - - return volume; + return volume; } // calculateHypervolume @@ -204,35 +231,41 @@ double Hypervolume::calculateHypervolume(double** front, int noPoints, * merge two fronts */ double** Hypervolume::mergeFronts(double** front1, int sizeFront1, - double** front2, int sizeFront2, int noObjectives) { - - int i, j; - int noPoints = sizeFront1 + sizeFront2; - double** frontPtr =0; - - /* allocate memory */ - frontPtr =new double*[noPoints]; - for (int y=0; y< noPoints; ++y) { - frontPtr[y] = new double[noObjectives]; - } - - /* copy points */ - noPoints = 0; - for (i = 0; i < sizeFront1; i++) { - for (j = 0; j < noObjectives; j++) { - frontPtr[noPoints][j] = front1[i][j]; + double** front2, int sizeFront2, int noObjectives) +{ + + int i, j; + int noPoints = sizeFront1 + sizeFront2; + double** frontPtr =0; + + /* allocate memory */ + frontPtr =snew double*[noPoints]; + for (int y=0; y< noPoints; ++y) + { + frontPtr[y] = snew double[noObjectives]; } - noPoints++; - } - for (i = 0; i < sizeFront2; i++) { - for (j = 0; j < noObjectives; j++) { - frontPtr[noPoints][j] = front2[i][j]; + + /* copy points */ + noPoints = 0; + for (i = 0; i < sizeFront1; i++) + { + for (j = 0; j < noObjectives; j++) + { + frontPtr[noPoints][j] = front1[i][j]; + } + noPoints++; + } + for (i = 0; i < sizeFront2; i++) + { + for (j = 0; j < noObjectives; j++) + { + frontPtr[noPoints][j] = front2[i][j]; + } + noPoints++; } - noPoints++; - } - - return frontPtr; - + + return frontPtr; + } // mergeFronts @@ -243,57 +276,61 @@ double** Hypervolume::mergeFronts(double** front1, int sizeFront1, * @param paretoTrueFront The true pareto front * @param numberOfObjectives Number of objectives of the pareto front */ -double Hypervolume::hypervolume(vector< vector > paretoFront, - vector< vector > paretoTrueFront, int numberOfObjectives) { - - /** - * Stores the maximum values of true pareto front. - */ - vector maximumValues; - - /** - * Stores the minimum values of the true pareto front. - */ - vector minimumValues; - - /** - * Stores the normalized front. - */ - vector< vector > normalizedFront; - - /** - * Stores the inverted front. Needed for minimization problems - */ - vector< vector > invertedFront; - - // STEP 1. Obtain the maximum and minimum values of the Pareto front - maximumValues = utils_->getMaximumValues(paretoTrueFront, numberOfObjectives); - minimumValues = utils_->getMinimumValues(paretoTrueFront, numberOfObjectives); - - // STEP 2. Get the normalized front - normalizedFront = utils_->getNormalizedFront(paretoFront, maximumValues, minimumValues); - - // STEP 3. Inverse the pareto front. This is needed because of the original - //metric by Zitzler is for maximization problems - invertedFront = utils_->invertedFront(normalizedFront); - - /*Makes a copy of invertedFront in pointer of pointer format*/ - double ** invertedFront2 = new double*[invertedFront.size()]; - for (int i = 0; i < invertedFront.size(); i++) { - invertedFront2[i] = new double[invertedFront[i].size()]; - for (int j = 0; j < invertedFront[i].size(); j++) { - invertedFront2[i][j] = invertedFront[i][j]; +double Hypervolume::hypervolume(MatrixOfDouble paretoFront, + MatrixOfDouble paretoTrueFront, int numberOfObjectives) +{ + + /** + * Stores the maximum values of true pareto front. + */ + VectorOfDouble maximumValues; + + /** + * Stores the minimum values of the true pareto front. + */ + VectorOfDouble minimumValues; + + /** + * Stores the normalized front. + */ + MatrixOfDouble normalizedFront; + + /** + * Stores the inverted front. Needed for minimization problems + */ + MatrixOfDouble invertedFront; + + // STEP 1. Obtain the maximum and minimum values of the Pareto front + maximumValues = utils_->getMaximumValues(paretoTrueFront, numberOfObjectives); + minimumValues = utils_->getMinimumValues(paretoTrueFront, numberOfObjectives); + + // STEP 2. Get the normalized front + normalizedFront = utils_->getNormalizedFront(paretoFront, maximumValues, minimumValues); + + // STEP 3. Inverse the pareto front. This is needed because of the original + //metric by Zitzler is for maximization problems + invertedFront = utils_->invertedFront(normalizedFront); + + /*Makes a copy of invertedFront in pointer of pointer format*/ + double ** invertedFront2 = snew double*[invertedFront.size()]; + for (int i = 0; i < invertedFront.size(); i++) + { + invertedFront2[i] = snew double[invertedFront[i].size()]; + for (int j = 0; j < invertedFront[i].size(); j++) + { + invertedFront2[i][j] = invertedFront[i][j]; + } } - } - - // STEP4. The hypervolume (control is passed to java version of Zitzler code) - double hv=this->calculateHypervolume(invertedFront2,invertedFront.size(),numberOfObjectives); - - for( int y = 0 ; y < invertedFront.size() ; y++ ) { - delete [] invertedFront2[y] ; - } - delete [] invertedFront2; - - return hv; + + // STEP4. The hypervolume (control is passed to java version of Zitzler code) + double hv=this->calculateHypervolume(invertedFront2,invertedFront.size(),numberOfObjectives); + + for( int y = 0 ; y < invertedFront.size() ; y++ ) + { + delete [] invertedFront2[y] ; + } + delete [] invertedFront2; + + return hv; }// hypervolume diff --git a/src/qualityIndicator/Hypervolume.h b/src/qualityIndicator/Hypervolume.h index 2282dd3..3880b8e 100644 --- a/src/qualityIndicator/Hypervolume.h +++ b/src/qualityIndicator/Hypervolume.h @@ -26,7 +26,7 @@ #include #include -using namespace std; + /** * This class implements the hypervolume indicator. The code is a C++ version @@ -38,29 +38,30 @@ using namespace std; * pp. 257-271, 1999. */ -class Hypervolume { +class Hypervolume +{ private: - bool dominates(double * point1, double * point2, int noObjectives); - void swap(double** front, int i, int j); - int filterNondominatedSet(double** front, int noPoints, int noObjectives); - double surfaceUnchangedTo(double ** front, int noPoints, int objective); - int reduceNondominatedSet(double** front, int noPoints, int objective, - double threshold); - double** mergeFronts(double** front1, int sizeFront1, double** front2, - int sizeFront2, int noObjectives); + bool dominates(double * point1, double * point2, int noObjectives); + void swap(double** front, int i, int j); + int filterNondominatedSet(double** front, int noPoints, int noObjectives); + double surfaceUnchangedTo(double ** front, int noPoints, int objective); + int reduceNondominatedSet(double** front, int noPoints, int objective, + double threshold); + double** mergeFronts(double** front1, int sizeFront1, double** front2, + int sizeFront2, int noObjectives); public: - - MetricsUtil * utils_; - Hypervolume(); - ~Hypervolume(); + MetricsUtil * utils_; + + Hypervolume(); + ~Hypervolume(); - double calculateHypervolume(double** front, int noPoints, int noObjectives); - double hypervolume(vector< vector > paretoFront, - vector< vector > paretoTrueFront, int numberOfObjectives); + double calculateHypervolume(double** front, int noPoints, int noObjectives); + double hypervolume(MatrixOfDouble paretoFront, + MatrixOfDouble paretoTrueFront, int numberOfObjectives); }; diff --git a/src/qualityIndicator/InvertedGenerationalDistance.cpp b/src/qualityIndicator/InvertedGenerationalDistance.cpp index 63ccc2f..f6db325 100644 --- a/src/qualityIndicator/InvertedGenerationalDistance.cpp +++ b/src/qualityIndicator/InvertedGenerationalDistance.cpp @@ -31,16 +31,18 @@ const double InvertedGenerationalDistance::pow_ = 2.0; * Constructor. * Creates a new instance of the generational distance metric. */ -InvertedGenerationalDistance::InvertedGenerationalDistance() { - utils_ = new MetricsUtil(); +InvertedGenerationalDistance::InvertedGenerationalDistance() +{ + utils_ = snew MetricsUtil(); } // InvertedGenerationalDistance /** * Destructor */ -InvertedGenerationalDistance::~InvertedGenerationalDistance() { - delete utils_; +InvertedGenerationalDistance::~InvertedGenerationalDistance() +{ + delete utils_; } // ~InvertedGenerationalDistance @@ -50,56 +52,57 @@ InvertedGenerationalDistance::~InvertedGenerationalDistance() { * @param trueParetoFront The true pareto front */ double InvertedGenerationalDistance::invertedGenerationalDistance( - vector< vector > front, vector< vector > trueParetoFront, - int numberOfObjectives) { - - /** - * Stores the maximum values of true pareto front. - */ - vector maximumValue; - - /** - * Stores the minimum values of the true pareto front. - */ - vector minimumValue; - - /** - * Stores the normalized front. - */ - vector< vector > normalizedFront; - - /** - * Stores the normalized true Pareto front. - */ - vector< vector > normalizedParetoFront ; - - // STEP 1. Obtain the maximum and minimum values of the Pareto front - maximumValue = utils_->getMaximumValues(trueParetoFront, numberOfObjectives); - minimumValue = utils_->getMinimumValues(trueParetoFront, numberOfObjectives); - - // STEP 2. Get the normalized front and true Pareto fronts - normalizedFront = utils_->getNormalizedFront(front, - maximumValue, - minimumValue); - normalizedParetoFront = utils_->getNormalizedFront(trueParetoFront, - maximumValue, - minimumValue); - - // STEP 3. Sum the distances between each point of the true Pareto front and - // the nearest point in the true Pareto front - double sum = 0.0; - for (int i = 0; i < normalizedParetoFront.size(); i++) - sum += pow(utils_->distanceToClosedPoint(normalizedParetoFront[i], - normalizedFront), - pow_); - - - // STEP 4. Obtain the sqrt of the sum - sum = pow(sum,1.0/pow_); - - // STEP 5. Divide the sum by the maximum number of points of the front - double generationalDistance = sum / normalizedParetoFront.size(); - - return generationalDistance; + MatrixOfDouble front, MatrixOfDouble trueParetoFront, + int numberOfObjectives) +{ + + /** + * Stores the maximum values of true pareto front. + */ + VectorOfDouble maximumValue; + + /** + * Stores the minimum values of the true pareto front. + */ + VectorOfDouble minimumValue; + + /** + * Stores the normalized front. + */ + MatrixOfDouble normalizedFront; + + /** + * Stores the normalized true Pareto front. + */ + MatrixOfDouble normalizedParetoFront ; + + // STEP 1. Obtain the maximum and minimum values of the Pareto front + maximumValue = utils_->getMaximumValues(trueParetoFront, numberOfObjectives); + minimumValue = utils_->getMinimumValues(trueParetoFront, numberOfObjectives); + + // STEP 2. Get the normalized front and true Pareto fronts + normalizedFront = utils_->getNormalizedFront(front, + maximumValue, + minimumValue); + normalizedParetoFront = utils_->getNormalizedFront(trueParetoFront, + maximumValue, + minimumValue); + + // STEP 3. Sum the distances between each point of the true Pareto front and + // the nearest point in the true Pareto front + double sum = 0.0; + for (int i = 0; i < normalizedParetoFront.size(); i++) + sum += pow(utils_->distanceToClosedPoint(normalizedParetoFront[i], + normalizedFront), + pow_); + + + // STEP 4. Obtain the sqrt of the sum + sum = pow(sum,1.0/pow_); + + // STEP 5. Divide the sum by the maximum number of points of the front + double generationalDistance = sum / normalizedParetoFront.size(); + + return generationalDistance; } // generationalDistance diff --git a/src/qualityIndicator/InvertedGenerationalDistance.h b/src/qualityIndicator/InvertedGenerationalDistance.h index e78eb77..7c0f4b7 100644 --- a/src/qualityIndicator/InvertedGenerationalDistance.h +++ b/src/qualityIndicator/InvertedGenerationalDistance.h @@ -36,19 +36,20 @@ * Inst. Technol. (1998) */ -class InvertedGenerationalDistance { +class InvertedGenerationalDistance +{ private: - static const double pow_; + static const double pow_; public: - MetricsUtil * utils_; + MetricsUtil * utils_; - InvertedGenerationalDistance(); - ~InvertedGenerationalDistance(); - double invertedGenerationalDistance(vector< vector > front, - vector< vector > trueParetoFront, int numberOfObjectives); + InvertedGenerationalDistance(); + ~InvertedGenerationalDistance(); + double invertedGenerationalDistance(MatrixOfDouble front, + MatrixOfDouble trueParetoFront, int numberOfObjectives); }; diff --git a/src/qualityIndicator/QualityIndicator.cpp b/src/qualityIndicator/QualityIndicator.cpp index f19252f..2b529f3 100644 --- a/src/qualityIndicator/QualityIndicator.cpp +++ b/src/qualityIndicator/QualityIndicator.cpp @@ -27,23 +27,25 @@ * @param paretoFrontFile */ QualityIndicator::QualityIndicator(Problem * problem, - string paretoFrontFile) { - problem_ = problem; - dim_ = problem_->getNumberOfObjectives(); - utilities_ = new MetricsUtil(); - trueParetoFront_ = utilities_->readNonDominatedSolutionSet(paretoFrontFile); - Hypervolume * hv = new Hypervolume(); - trueParetoFrontHypervolume_ = hv->hypervolume(trueParetoFront_->writeObjectivesToMatrix(), - trueParetoFront_->writeObjectivesToMatrix(), problem_->getNumberOfObjectives()); - delete hv; + std::string paretoFrontFile) +{ + problem_ = problem; + dim_ = problem_->getNumberOfObjectives(); + utilities_ = new MetricsUtil(); + trueParetoFront_ = utilities_->readNonDominatedSolutionSet(paretoFrontFile); + Hypervolume * hv = new Hypervolume(); + trueParetoFrontHypervolume_ = hv->hypervolume(trueParetoFront_->writeObjectivesToMatrix(), + trueParetoFront_->writeObjectivesToMatrix(), problem_->getNumberOfObjectives()); + delete hv; } // Constructor /** * Destructor */ -QualityIndicator::~QualityIndicator() { - delete utilities_; +QualityIndicator::~QualityIndicator() +{ + delete utilities_; } // ~QualityIndicator @@ -52,13 +54,14 @@ QualityIndicator::~QualityIndicator() { * @param solutionSet * @return The value of the hypervolume indicator */ -double QualityIndicator::getHypervolume(SolutionSet * solutionSet) { - Hypervolume * hv = new Hypervolume(); - double res = hv->hypervolume(solutionSet->writeObjectivesToMatrix(), - trueParetoFront_->writeObjectivesToMatrix(), - dim_); - delete hv; - return res; +double QualityIndicator::getHypervolume(SolutionSet * solutionSet) +{ + Hypervolume * hv = new Hypervolume(); + double res = hv->hypervolume(solutionSet->writeObjectivesToMatrix(), + trueParetoFront_->writeObjectivesToMatrix(), + dim_); + delete hv; + return res; } // getHypervolume @@ -66,8 +69,9 @@ double QualityIndicator::getHypervolume(SolutionSet * solutionSet) { * Returns the hypervolume of the true Pareto front * @return The hypervolume of the true Pareto front */ -double QualityIndicator::getTrueParetoFrontHypervolume() { - return trueParetoFrontHypervolume_ ; +double QualityIndicator::getTrueParetoFrontHypervolume() +{ + return trueParetoFrontHypervolume_ ; } // getTrueParetoFrontHypervolume @@ -76,14 +80,15 @@ double QualityIndicator::getTrueParetoFrontHypervolume() { * @param solutionSet * @return The value of the hypervolume indicator */ -double QualityIndicator::getIGD(SolutionSet * solutionSet) { - InvertedGenerationalDistance * igd = new InvertedGenerationalDistance(); - double res = igd->invertedGenerationalDistance( - solutionSet->writeObjectivesToMatrix(), - trueParetoFront_->writeObjectivesToMatrix(), - dim_); - delete igd; - return res; +double QualityIndicator::getIGD(SolutionSet * solutionSet) +{ + InvertedGenerationalDistance * igd = new InvertedGenerationalDistance(); + double res = igd->invertedGenerationalDistance( + solutionSet->writeObjectivesToMatrix(), + trueParetoFront_->writeObjectivesToMatrix(), + dim_); + delete igd; + return res; } // getIGD @@ -92,13 +97,14 @@ double QualityIndicator::getIGD(SolutionSet * solutionSet) { * @param solutionSet * @return The value of the hypervolume indicator */ -double QualityIndicator::getGD(SolutionSet * solutionSet) { - GenerationalDistance * gd = new GenerationalDistance(); - double res = gd->generationalDistance(solutionSet->writeObjectivesToMatrix(), - trueParetoFront_->writeObjectivesToMatrix(), - dim_); - delete gd; - return res; +double QualityIndicator::getGD(SolutionSet * solutionSet) +{ + GenerationalDistance * gd = new GenerationalDistance(); + double res = gd->generationalDistance(solutionSet->writeObjectivesToMatrix(), + trueParetoFront_->writeObjectivesToMatrix(), + dim_); + delete gd; + return res; } // getGD @@ -107,13 +113,14 @@ double QualityIndicator::getGD(SolutionSet * solutionSet) { * @param solutionSet * @return The value of the hypervolume indicator */ -double QualityIndicator::getSpread(SolutionSet * solutionSet) { - Spread * s = new Spread(); - double res = s->spread(solutionSet->writeObjectivesToMatrix(), - trueParetoFront_->writeObjectivesToMatrix(), - dim_); - delete s; - return res; +double QualityIndicator::getSpread(SolutionSet * solutionSet) +{ + Spread * s = new Spread(); + double res = s->spread(solutionSet->writeObjectivesToMatrix(), + trueParetoFront_->writeObjectivesToMatrix(), + dim_); + delete s; + return res; } // getSpread @@ -122,11 +129,12 @@ double QualityIndicator::getSpread(SolutionSet * solutionSet) { * @param solutionSet * @return The value of the hypervolume indicator */ -double QualityIndicator::getEpsilon(SolutionSet * solutionSet) { - Epsilon * e = new Epsilon(); - double res = e->epsilon(solutionSet->writeObjectivesToMatrix(), - trueParetoFront_->writeObjectivesToMatrix(), - dim_); - delete e; - return res; +double QualityIndicator::getEpsilon(SolutionSet * solutionSet) +{ + Epsilon * e = new Epsilon(); + double res = e->epsilon(solutionSet->writeObjectivesToMatrix(), + trueParetoFront_->writeObjectivesToMatrix(), + dim_); + delete e; + return res; } // getEpsilon diff --git a/src/qualityIndicator/QualityIndicator.h b/src/qualityIndicator/QualityIndicator.h index aa37fd4..82be59b 100644 --- a/src/qualityIndicator/QualityIndicator.h +++ b/src/qualityIndicator/QualityIndicator.h @@ -31,24 +31,25 @@ #include #include -class QualityIndicator { +class QualityIndicator +{ private: - SolutionSet * trueParetoFront_; - double trueParetoFrontHypervolume_; - Problem * problem_; - int dim_; - MetricsUtil * utilities_; + SolutionSet * trueParetoFront_; + double trueParetoFrontHypervolume_; + Problem * problem_; + int dim_; + MetricsUtil * utilities_; public: - QualityIndicator(Problem * problem, string paretoFrontFile); - ~QualityIndicator(); - double getHypervolume(SolutionSet * solutionSet); - double getTrueParetoFrontHypervolume(); - double getIGD(SolutionSet * solutionSet); - double getGD(SolutionSet * solutionSet); - double getSpread(SolutionSet * solutionSet); - double getEpsilon(SolutionSet * solutionSet); + QualityIndicator(Problem * problem, std::string paretoFrontFile); + ~QualityIndicator(); + double getHypervolume(SolutionSet * solutionSet); + double getTrueParetoFrontHypervolume(); + double getIGD(SolutionSet * solutionSet); + double getGD(SolutionSet * solutionSet); + double getSpread(SolutionSet * solutionSet); + double getEpsilon(SolutionSet * solutionSet); }; diff --git a/src/qualityIndicator/Spread.cpp b/src/qualityIndicator/Spread.cpp index 4ccd35f..a2dab1b 100644 --- a/src/qualityIndicator/Spread.cpp +++ b/src/qualityIndicator/Spread.cpp @@ -26,33 +26,37 @@ * Constructor * Creates a new instance of a Spread object */ -Spread::Spread() { - utils_ = new MetricsUtil(); +Spread::Spread() +{ + utils_ = new MetricsUtil(); } // Spread /** * Destructor */ -Spread::~Spread() { - delete utils_; +Spread::~Spread() +{ + delete utils_; } // ~Spread -bool Spread::compareFront(vector pointOne, vector pointTwo) { +bool Spread::compareFront(VectorOfDouble pointOne, VectorOfDouble pointTwo) +{ - int value; - bool result = false; + int value; + bool result = false; - LexicoGraphicalComparator * c = new LexicoGraphicalComparator(); - value = c->compare(&pointOne, &pointTwo); - delete c; + LexicoGraphicalComparator * c = new LexicoGraphicalComparator(); + value = c->compare(&pointOne, &pointTwo); + delete c; - if (value == -1) { - result = true; - } + if (value == -1) + { + result = true; + } - return result; + return result; } // compareFront @@ -64,75 +68,79 @@ bool Spread::compareFront(vector pointOne, vector pointTwo) { * @param trueParetoFront The true pareto front. * @param numberOfObjectives The number of objectives. */ -double Spread::spread(vector > front, - vector > trueParetoFront, int numberOfObjectives) { - - /** - * Stores the maximum values of true pareto front. - */ - vector maximumValue ; - - /** - * Stores the minimum values of the true pareto front. - */ - vector minimumValue ; - - /** - * Stores the normalized front. - */ - vector > normalizedFront ; - - /** - * Stores the normalized true Pareto front. - */ - vector > normalizedParetoFront ; - - // STEP 1. Obtain the maximum and minimum values of the Pareto front - maximumValue = utils_->getMaximumValues(trueParetoFront, numberOfObjectives); - minimumValue = utils_->getMinimumValues(trueParetoFront, numberOfObjectives); - - // STEP 2. Get the normalized front and true Pareto fronts - normalizedFront = utils_->getNormalizedFront(front, - maximumValue, - minimumValue); - normalizedParetoFront = utils_->getNormalizedFront(trueParetoFront, - maximumValue, - minimumValue); - - // STEP 3. Sort normalizedFront and normalizedParetoFront; - sort(normalizedFront.begin(), normalizedFront.end(), Spread::compareFront); - sort(normalizedParetoFront.begin(), normalizedParetoFront.end(), Spread::compareFront); - - int numberOfPoints = normalizedFront.size(); - // int numberOfTruePoints = normalizedParetoFront.length; - - // STEP 4. Compute df and dl (See specifications in Deb's description of - // the metric) - double df = utils_->distance(normalizedFront[0],normalizedParetoFront[0]); - double dl = utils_->distance(normalizedFront[normalizedFront.size()-1], - normalizedParetoFront[normalizedParetoFront.size()-1]); - - double mean = 0.0; - double diversitySum = df + dl; - - // STEP 5. Calculate the mean of distances between points i and (i - 1). - // (the poins are in lexicografical order) - for (int i = 0; i < (normalizedFront.size()-1); i++) { - mean += utils_->distance(normalizedFront[i],normalizedFront[i+1]); - } // for - - mean = mean / (double)(numberOfPoints - 1); - - // STEP 6. If there are more than a single point, continue computing the - // metric. In other case, return the worse value (1.0, see metric's - // description). - if (numberOfPoints > 1) { - for (int i = 0; i < (numberOfPoints -1); i++) { - diversitySum += fabs(utils_->distance(normalizedFront[i], - normalizedFront[i+1]) - mean); +double Spread::spread(std::vector front, + std::vector trueParetoFront, int numberOfObjectives) +{ + + /** + * Stores the maximum values of true pareto front. + */ + VectorOfDouble maximumValue ; + + /** + * Stores the minimum values of the true pareto front. + */ + VectorOfDouble minimumValue ; + + /** + * Stores the normalized front. + */ + std::vector normalizedFront ; + + /** + * Stores the normalized true Pareto front. + */ + std::vector normalizedParetoFront ; + + // STEP 1. Obtain the maximum and minimum values of the Pareto front + maximumValue = utils_->getMaximumValues(trueParetoFront, numberOfObjectives); + minimumValue = utils_->getMinimumValues(trueParetoFront, numberOfObjectives); + + // STEP 2. Get the normalized front and true Pareto fronts + normalizedFront = utils_->getNormalizedFront(front, + maximumValue, + minimumValue); + normalizedParetoFront = utils_->getNormalizedFront(trueParetoFront, + maximumValue, + minimumValue); + + // STEP 3. Sort normalizedFront and normalizedParetoFront; + sort(normalizedFront.begin(), normalizedFront.end(), Spread::compareFront); + sort(normalizedParetoFront.begin(), normalizedParetoFront.end(), Spread::compareFront); + + int numberOfPoints = normalizedFront.size(); + // int numberOfTruePoints = normalizedParetoFront.length; + + // STEP 4. Compute df and dl (See specifications in Deb's description of + // the metric) + double df = utils_->distance(normalizedFront[0],normalizedParetoFront[0]); + double dl = utils_->distance(normalizedFront[normalizedFront.size()-1], + normalizedParetoFront[normalizedParetoFront.size()-1]); + + double mean = 0.0; + double diversitySum = df + dl; + + // STEP 5. Calculate the mean of distances between points i and (i - 1). + // (the poins are in lexicografical order) + for (int i = 0; i < (normalizedFront.size()-1); i++) + { + mean += utils_->distance(normalizedFront[i],normalizedFront[i+1]); } // for - return diversitySum / (df + dl + (numberOfPoints-1)*mean); - } - else - return 1.0; + + mean = mean / (double)(numberOfPoints - 1); + + // STEP 6. If there are more than a single point, continue computing the + // metric. In other case, return the worse value (1.0, see metric's + // description). + if (numberOfPoints > 1) + { + for (int i = 0; i < (numberOfPoints -1); i++) + { + diversitySum += fabs(utils_->distance(normalizedFront[i], + normalizedFront[i+1]) - mean); + } // for + return diversitySum / (df + dl + (numberOfPoints-1)*mean); + } + else + return 1.0; } // spread diff --git a/src/qualityIndicator/Spread.h b/src/qualityIndicator/Spread.h index 598e07a..c6c0dfb 100644 --- a/src/qualityIndicator/Spread.h +++ b/src/qualityIndicator/Spread.h @@ -38,19 +38,20 @@ using namespace std; * on Evol. Computation 6 (2002) 182-197 */ -class Spread { +class Spread +{ private: - static bool compareFront(vector pointOne, vector pointTwo); + static bool compareFront(vector pointOne, vector pointTwo); public: - MetricsUtil * utils_; + MetricsUtil * utils_; - Spread(); - ~Spread(); - double spread (vector< vector > front, - vector< vector > trueParetoFront, int numberOfObjectives); + Spread(); + ~Spread(); + double spread (vector< vector > front, + vector< vector > trueParetoFront, int numberOfObjectives); }; // Spread diff --git a/src/qualityIndicator/fastHypervolume/CMakeLists.txt b/src/qualityIndicator/fastHypervolume/CMakeLists.txt new file mode 100644 index 0000000..294ec59 --- /dev/null +++ b/src/qualityIndicator/fastHypervolume/CMakeLists.txt @@ -0,0 +1,3 @@ +file(GLOB SOURCES "*.cpp" "*.h") +ListToString(SOURCES ";" ${SOURCES}) +LIST_APPEND("${SOURCES}") \ No newline at end of file diff --git a/src/qualityIndicator/fastHypervolume/FastHypervolume.cpp b/src/qualityIndicator/fastHypervolume/FastHypervolume.cpp index b338d7b..e25a52f 100644 --- a/src/qualityIndicator/fastHypervolume/FastHypervolume.cpp +++ b/src/qualityIndicator/fastHypervolume/FastHypervolume.cpp @@ -25,74 +25,90 @@ * Constructor * Creates a new instance of FastHypervolume */ -FastHypervolume::FastHypervolume() { - referencePoint_ = NULL; - numberOfObjectives_ = 0; +FastHypervolume::FastHypervolume() +{ + referencePoint_ = nullptr; + numberOfObjectives_ = 0; } // FastHypervolume /** * Constructor * Creates a new instance of FastHypervolume */ -FastHypervolume::FastHypervolume(double offset) { - referencePoint_ = NULL; - numberOfObjectives_ = 0; - offset_ = offset; +FastHypervolume::FastHypervolume(double offset) +{ + referencePoint_ = nullptr; + numberOfObjectives_ = 0; + offset_ = offset; } // FastHypervolume /** * Destructor */ -FastHypervolume::~FastHypervolume() { +FastHypervolume::~FastHypervolume() +{ } // ~FastHypervolume -double FastHypervolume::computeHypervolume(SolutionSet* solutionSet) { - double hv; - if (solutionSet->size() == 0) { - hv = 0.0; - } else { - updateReferencePoint(solutionSet); - if (numberOfObjectives_ == 2) { - Comparator * comparator = - new ObjectiveComparator(numberOfObjectives_ - 1, true); - solutionSet->sort(comparator); - delete comparator; - hv = get2DHV(solutionSet); - } else { - /* - updateReferencePoint(solutionSet); - Front front = new Front(solutionSet.size(), numberOfObjectives_, solutionSet); - hv = new WFGHV(numberOfObjectives_, solutionSet.size(), referencePoint_).getHV(front); - */ - cerr << "Fast Hypervolume only works with two objectives for now." << endl; +double FastHypervolume::computeHypervolume(SolutionSet* solutionSet) +{ + double hv = 0.0; + if (solutionSet->size() == 0) + { + hv = 0.0; + } + else + { + updateReferencePoint(solutionSet); + if (numberOfObjectives_ == 2) + { + Comparator * comparator = + snew ObjectiveComparator(numberOfObjectives_ - 1, true); + solutionSet->sort(comparator); + delete comparator; + hv = get2DHV(solutionSet); + } + else + { + /* + updateReferencePoint(solutionSet); + Front front = new Front(solutionSet.size(), numberOfObjectives_, solutionSet); + hv = new WFGHV(numberOfObjectives_, solutionSet.size(), referencePoint_).getHV(front); + */ + cerr << "Fast Hypervolume only works with two objectives for now." << std::endl; + } } - } - return hv; + return hv; } // computeHypervolume /** * Updates the reference point */ -void FastHypervolume::updateReferencePoint(SolutionSet * solutionSet) { - double * maxObjectives = new double[numberOfObjectives_]; - for (int i = 0; i < numberOfObjectives_; i++) { - maxObjectives[i] = 0; - } - - for (int i = 0; i < solutionSet->size(); i++) { - for (int j = 0; j < numberOfObjectives_; j++) { - if (maxObjectives[j] < solutionSet->get(i)->getObjective(j)) { - maxObjectives[j] = solutionSet->get(i)->getObjective(j); - } +void FastHypervolume::updateReferencePoint(SolutionSet * solutionSet) +{ + double * maxObjectives = snew double[numberOfObjectives_]; + for (int i = 0; i < numberOfObjectives_; i++) + { + maxObjectives[i] = 0; } - } - for (int i = 0; i < referencePoint_->getNumberOfObjectives(); i++) { - referencePoint_->setObjective(i, maxObjectives[i] + offset_); - } + for (int i = 0; i < solutionSet->size(); i++) + { + for (int j = 0; j < numberOfObjectives_; j++) + { + if (maxObjectives[j] < solutionSet->get(i)->getObjective(j)) + { + maxObjectives[j] = solutionSet->get(i)->getObjective(j); + } + } + } - delete [] maxObjectives; + for (int i = 0; i < referencePoint_->getNumberOfObjectives(); i++) + { + referencePoint_->setObjective(i, maxObjectives[i] + offset_); + } + + delete [] maxObjectives; } // updateReferencePoint /** @@ -102,55 +118,64 @@ void FastHypervolume::updateReferencePoint(SolutionSet * solutionSet) { * * @return */ -double FastHypervolume::get2DHV(SolutionSet * solutionSet) { - double hv = 0.0; - if (solutionSet->size() > 0) { - hv = fabs((solutionSet->get(0)->getObjective(0) - referencePoint_->getObjective(0)) * - (solutionSet->get(0)->getObjective(1) - referencePoint_->getObjective(1))); - - for (int i = 1; i < solutionSet->size(); i++) { - double tmp = - fabs((solutionSet->get(i)->getObjective(0) - referencePoint_->getObjective(0)) * - (solutionSet->get(i)->getObjective(1) - solutionSet->get(i-1)->getObjective(1))); - hv += tmp; +double FastHypervolume::get2DHV(SolutionSet * solutionSet) +{ + double hv = 0.0; + if (solutionSet->size() > 0) + { + hv = fabs((solutionSet->get(0)->getObjective(0) - referencePoint_->getObjective(0)) * + (solutionSet->get(0)->getObjective(1) - referencePoint_->getObjective(1))); + + for (int i = 1; i < solutionSet->size(); i++) + { + double tmp = + fabs((solutionSet->get(i)->getObjective(0) - referencePoint_->getObjective(0)) * + (solutionSet->get(i)->getObjective(1) - solutionSet->get(i-1)->getObjective(1))); + hv += tmp; + } } - } - return hv; + return hv; } // get2DHV -void FastHypervolume::computeHVContributions(SolutionSet * solutionSet) { - double * contributions = new double[solutionSet->size()]; - double solutionSetHV = 0; - - numberOfObjectives_ = solutionSet->get(0)->getNumberOfObjectives(); - referencePoint_ = new Solution(numberOfObjectives_); - - solutionSetHV = computeHypervolume(solutionSet); - - for (int i = 0; i < solutionSet->size(); i++) { - Solution * currentPoint = solutionSet->get(i); - solutionSet->remove(i); - - if (numberOfObjectives_ == 2) { - //updateReferencePoint(solutionSet); - //solutionSet.sort(new ObjectiveComparator(numberOfObjectives_-1, true)); - contributions[i] = solutionSetHV - get2DHV(solutionSet); - } else { - /* - Front front = new Front(solutionSet.size(), numberOfObjectives_, solutionSet); - double hv = - new WFGHV(numberOfObjectives_, solutionSet.size(), referencePoint_).getHV(front); - contributions[i] = solutionSetHV - hv; - */ - cerr << "Fast Hypervolume only works with two objectives for now." << endl; +void FastHypervolume::computeHVContributions(SolutionSet * solutionSet) +{ + double * contributions = snew double[solutionSet->size()]; + double solutionSetHV = 0; + + numberOfObjectives_ = solutionSet->get(0)->getNumberOfObjectives(); + referencePoint_ = snew Solution(numberOfObjectives_); + + solutionSetHV = computeHypervolume(solutionSet); + + for (int i = 0; i < solutionSet->size(); i++) + { + Solution * currentPoint = solutionSet->get(i); + solutionSet->remove(i); + + if (numberOfObjectives_ == 2) + { + //updateReferencePoint(solutionSet); + //solutionSet.sort(new ObjectiveComparator(numberOfObjectives_-1, true)); + contributions[i] = solutionSetHV - get2DHV(solutionSet); + } + else + { + /* + Front front = new Front(solutionSet.size(), numberOfObjectives_, solutionSet); + double hv = + new WFGHV(numberOfObjectives_, solutionSet.size(), referencePoint_).getHV(front); + contributions[i] = solutionSetHV - hv; + */ + cerr << "Fast Hypervolume only works with two objectives for now." << std::endl; + } + solutionSet->add(i, currentPoint); } - solutionSet->add(i, currentPoint); - } - for (int i = 0; i < solutionSet->size(); i++) { - solutionSet->get(i)->setCrowdingDistance(contributions[i]); - } + for (int i = 0; i < solutionSet->size(); i++) + { + solutionSet->get(i)->setCrowdingDistance(contributions[i]); + } - delete [] contributions; - delete referencePoint_; + delete [] contributions; + delete referencePoint_; } // computeHVContributions diff --git a/src/qualityIndicator/fastHypervolume/FastHypervolume.h b/src/qualityIndicator/fastHypervolume/FastHypervolume.h index 450c737..61b31db 100644 --- a/src/qualityIndicator/fastHypervolume/FastHypervolume.h +++ b/src/qualityIndicator/fastHypervolume/FastHypervolume.h @@ -27,31 +27,32 @@ //#include #include -using namespace std; -class FastHypervolume { + +class FastHypervolume +{ private: - Solution * referencePoint_; - int numberOfObjectives_; - double offset_ = 20.0; + Solution * referencePoint_; + int numberOfObjectives_; + double offset_ = 20.0; - void updateReferencePoint(SolutionSet * solutionSet); - double get2DHV(SolutionSet * solutionSet); - double computeHypervolume(SolutionSet * solutionSet); + void updateReferencePoint(SolutionSet * solutionSet); + double get2DHV(SolutionSet * solutionSet); + double computeHypervolume(SolutionSet * solutionSet); - // double computeSolutionHVContribution(SolutionSet * solutionSet, - // int solutionIndex, double solutionSetHV); + // double computeSolutionHVContribution(SolutionSet * solutionSet, + // int solutionIndex, double solutionSetHV); public: - FastHypervolume(); - FastHypervolume(double offset); - ~FastHypervolume(); + FastHypervolume(); + FastHypervolume(double offset); + ~FastHypervolume(); - void computeHVContributions(SolutionSet * solutionSet); + void computeHVContributions(SolutionSet * solutionSet); }; diff --git a/src/qualityIndicator/fastHypervolume/FastHypervolumeArchive.cpp b/src/qualityIndicator/fastHypervolume/FastHypervolumeArchive.cpp index 9736220..c897862 100644 --- a/src/qualityIndicator/fastHypervolume/FastHypervolumeArchive.cpp +++ b/src/qualityIndicator/fastHypervolume/FastHypervolumeArchive.cpp @@ -33,28 +33,31 @@ * @param numberOfObjectives The number of objectives. */ FastHypervolumeArchive::FastHypervolumeArchive(int maxSize, int numberOfObjectives) -: Archive(maxSize) { - this->maxSize = maxSize; - this->objectives = numberOfObjectives; - this->dominance = new DominanceComparator(); - this->equals = new EqualSolutions(); - this->referencePoint = new Solution(objectives) ; - for (int i = 0; i < objectives; i++) { - referencePoint->setObjective(i, std::numeric_limits::max()); - } - crowdingDistance_ = new CrowdingComparator(); + : Archive(maxSize) +{ + this->maxSize = maxSize; + this->objectives = numberOfObjectives; + this->dominance = snew DominanceComparator(); + this->equals = snew EqualSolutions(); + this->referencePoint = snew Solution(objectives) ; + for (int i = 0; i < objectives; i++) + { + referencePoint->setObjective(i, std::numeric_limits::max()); + } + crowdingDistance_ = snew CrowdingComparator(); } // FastHypervolumeArchive /** * Destructor. */ -FastHypervolumeArchive::~FastHypervolumeArchive() { - cout << "DELETING FASTHYPERVOLUMEARCHIVE" << endl; - delete dominance; - delete equals; - delete referencePoint; - delete crowdingDistance_; +FastHypervolumeArchive::~FastHypervolumeArchive() +{ + std::cout << "DELETING FASTHYPERVOLUMEARCHIVE" << std::endl; + delete dominance; + delete equals; + delete referencePoint; + delete crowdingDistance_; } // ~FastHypervolumeArchive @@ -69,53 +72,67 @@ FastHypervolumeArchive::~FastHypervolumeArchive() { * @return true if the Solution has been inserted, false * otherwise. */ -bool FastHypervolumeArchive::add(Solution *solution){ - int flag = 0; - int i = 0; - Solution *aux; //Store an solution temporally +bool FastHypervolumeArchive::add(Solution *solution) +{ + int flag = 0; + int i = 0; + Solution *aux; //Store an solution temporally - while (i < solutionsList_.size()){ - aux = solutionsList_[i]; + while (i < solutionsList_.size()) + { + aux = solutionsList_[i]; - flag = dominance->compare(solution,aux); - if (flag == 1) { // The solution to add is dominated - return false; // Discard the new solution - } else if (flag == -1) { // A solution in the archive is dominated - // Remove it from the population - delete aux; - solutionsList_.erase(solutionsList_.begin() + i); - } else { - if (equals->compare(aux,solution)==0) { - // There is an equal solution in the population - return false; // Discard the new solution - } // if - i++; + flag = dominance->compare(solution,aux); + if (flag == 1) // The solution to add is dominated + { + return false; // Discard the new solution + } + else if (flag == -1) // A solution in the archive is dominated + { + // Remove it from the population + delete aux; + solutionsList_.erase(solutionsList_.begin() + i); + } + else + { + if (equals->compare(aux,solution)==0) + { + // There is an equal solution in the population + return false; // Discard the new solution + } // if + i++; + } } - } - // Insert the solution into the archive - bool res = true; - solutionsList_.push_back(solution); - if (size() > maxSize) { // The archive is full - computeHVContribution(); - int indexWorst_ = indexWorst(crowdingDistance_); - if (solution == solutionsList_[indexWorst_]) { - res = false; - } else { - delete solutionsList_[indexWorst_]; + // Insert the solution into the archive + bool res = true; + solutionsList_.push_back(solution); + if (size() > maxSize) // The archive is full + { + computeHVContribution(); + int indexWorst_ = indexWorst(crowdingDistance_); + if (solution == solutionsList_[indexWorst_]) + { + res = false; + } + else + { + delete solutionsList_[indexWorst_]; + } + remove(indexWorst_); } - remove(indexWorst_); - } - return res; + return res; } // add /** * This method forces to compute the contribution of each solution */ -void FastHypervolumeArchive::computeHVContribution() { - if (size() > 2) { // The contribution can be updated - FastHypervolume *fastHV = new FastHypervolume(); - fastHV->computeHVContributions(this); - delete fastHV; - } +void FastHypervolumeArchive::computeHVContribution() +{ + if (size() > 2) // The contribution can be updated + { + FastHypervolume *fastHV = snew FastHypervolume(); + fastHV->computeHVContributions(this); + delete fastHV; + } } // computeHVContribution diff --git a/src/qualityIndicator/fastHypervolume/FastHypervolumeArchive.h b/src/qualityIndicator/fastHypervolume/FastHypervolumeArchive.h index cecf16d..b2b98ff 100644 --- a/src/qualityIndicator/fastHypervolume/FastHypervolumeArchive.h +++ b/src/qualityIndicator/fastHypervolume/FastHypervolumeArchive.h @@ -32,66 +32,67 @@ /** * This class implements a bounded archive based on the hypervolume quality indicator */ -class FastHypervolumeArchive : public Archive { +class FastHypervolumeArchive : public Archive +{ private: - /** - * Stores the maximum size of the archive. - */ - int maxSize; + /** + * Stores the maximum size of the archive. + */ + int maxSize; - /** - * stores the number of the objectives. - */ - int objectives; + /** + * stores the number of the objectives. + */ + int objectives; - /** - * Stores a Comparator for dominance checking. - */ - Comparator *dominance; + /** + * Stores a Comparator for dominance checking. + */ + Comparator *dominance; - /** - * Stores a Comparator for equality checking (in the objective - * space). - */ - Comparator *equals; + /** + * Stores a Comparator for equality checking (in the objective + * space). + */ + Comparator *equals; - Comparator *crowdingDistance_; + Comparator *crowdingDistance_; - Solution *referencePoint; + Solution *referencePoint; public: - /** - * Constructor. - * @param maxSize The maximum size of the archive. - * @param numberOfObjectives The number of objectives. - */ - FastHypervolumeArchive(int maxSize, int numberOfObjectives); - - /** - * Destructor. - */ - ~FastHypervolumeArchive(); - - /** - * Adds a Solution to the archive. If the Solution - * is dominated by any member of the archive, then it is discarded. If the - * Solution dominates some members of the archive, these are - * removed. If the archive is full and the Solution has to be - * inserted, the solution contributing the least to the HV of the solution set - * is discarded. - * @param solution The Solution - * @return true if the Solution has been inserted, false - * otherwise. - */ - bool add(Solution *solution); - - /** - * This method forces to compute the contribution of each solution - */ - void computeHVContribution(); + /** + * Constructor. + * @param maxSize The maximum size of the archive. + * @param numberOfObjectives The number of objectives. + */ + FastHypervolumeArchive(int maxSize, int numberOfObjectives); + + /** + * Destructor. + */ + ~FastHypervolumeArchive(); + + /** + * Adds a Solution to the archive. If the Solution + * is dominated by any member of the archive, then it is discarded. If the + * Solution dominates some members of the archive, these are + * removed. If the archive is full and the Solution has to be + * inserted, the solution contributing the least to the HV of the solution set + * is discarded. + * @param solution The Solution + * @return true if the Solution has been inserted, false + * otherwise. + */ + bool add(Solution *solution); + + /** + * This method forces to compute the contribution of each solution + */ + void computeHVContribution(); }; diff --git a/src/qualityIndicator/main/CMakeLists.txt b/src/qualityIndicator/main/CMakeLists.txt new file mode 100644 index 0000000..294ec59 --- /dev/null +++ b/src/qualityIndicator/main/CMakeLists.txt @@ -0,0 +1,3 @@ +file(GLOB SOURCES "*.cpp" "*.h") +ListToString(SOURCES ";" ${SOURCES}) +LIST_APPEND("${SOURCES}") \ No newline at end of file diff --git a/src/qualityIndicator/main/Epsilon_main.cpp b/src/qualityIndicator/main/Epsilon_main.cpp index 6ff8fbc..6a0dc50 100644 --- a/src/qualityIndicator/main/Epsilon_main.cpp +++ b/src/qualityIndicator/main/Epsilon_main.cpp @@ -23,7 +23,7 @@ #include -using namespace std; + /** * This method can be invoked from the command line. Three params are required: @@ -31,26 +31,28 @@ using namespace std; * 2) the name of the file containing the true Pareto front * 3) the number of objectives */ -int main(int argc, char ** argv) { - if (argc < 4) { - cerr << "Error using delta. Type: \n Epsilon " << - " " << endl; - exit(-1); - } - - //Create a new instance of the metric - Epsilon * qualityIndicator = new Epsilon(); - //Read the front from the files - vector< vector > solutionFront = - qualityIndicator->utils_->readFront(argv[1]); - vector< vector > trueFront = - qualityIndicator->utils_->readFront(argv[2]); - - //Obtain delta value - double value = qualityIndicator->epsilon(solutionFront, - trueFront, atoi(argv[3])); - - delete qualityIndicator; - - cout << value << endl; +int main(int argc, char ** argv) +{ + if (argc < 4) + { + cerr << "Error using delta. Type: \n Epsilon " << + " " << std::endl; + exit(-1); + } + + //Create a new instance of the metric + Epsilon * qualityIndicator = snew Epsilon(); + //Read the front from the files + MatrixOfDouble solutionFront = + qualityIndicator->utils_->readFront(argv[1]); + MatrixOfDouble trueFront = + qualityIndicator->utils_->readFront(argv[2]); + + //Obtain delta value + double value = qualityIndicator->epsilon(solutionFront, + trueFront, atoi(argv[3])); + + delete qualityIndicator; + + std::cout << value << std::endl; } // main diff --git a/src/qualityIndicator/main/GenerationalDistance_main.cpp b/src/qualityIndicator/main/GenerationalDistance_main.cpp index 6707d1b..064f273 100644 --- a/src/qualityIndicator/main/GenerationalDistance_main.cpp +++ b/src/qualityIndicator/main/GenerationalDistance_main.cpp @@ -23,7 +23,7 @@ #include -using namespace std; + /** * This method can be invoked from the command line. Three params are required: @@ -31,26 +31,28 @@ using namespace std; * 2) the name of the file containing the true Pareto front * 3) the number of objectives */ -int main(int argc, char ** argv) { - if (argc < 4) { - cerr << "Error using delta. Type: \n GenerationalDistance " << - " " << endl; - exit(-1); - } - - //Create a new instance of the metric - GenerationalDistance * qualityIndicator = new GenerationalDistance(); - //Read the front from the files - vector< vector > solutionFront = - qualityIndicator->utils_->readFront(argv[1]); - vector< vector > trueFront = - qualityIndicator->utils_->readFront(argv[2]); - - //Obtain delta value - double value = qualityIndicator->generationalDistance(solutionFront, - trueFront, atoi(argv[3])); - - delete qualityIndicator; - - cout << value << endl; +int main(int argc, char ** argv) +{ + if (argc < 4) + { + cerr << "Error using delta. Type: \n GenerationalDistance " << + " " << std::endl; + exit(-1); + } + + //Create a new instance of the metric + GenerationalDistance * qualityIndicator = snew GenerationalDistance(); + //Read the front from the files + MatrixOfDouble solutionFront = + qualityIndicator->utils_->readFront(argv[1]); + MatrixOfDouble trueFront = + qualityIndicator->utils_->readFront(argv[2]); + + //Obtain delta value + double value = qualityIndicator->generationalDistance(solutionFront, + trueFront, atoi(argv[3])); + + delete qualityIndicator; + + std::cout << value << std::endl; } // main diff --git a/src/qualityIndicator/main/Hypervolume_main.cpp b/src/qualityIndicator/main/Hypervolume_main.cpp index cb43f60..33240c8 100644 --- a/src/qualityIndicator/main/Hypervolume_main.cpp +++ b/src/qualityIndicator/main/Hypervolume_main.cpp @@ -23,7 +23,7 @@ #include -using namespace std; + /** * This method can be invoked from the command line. Three params are required: @@ -31,26 +31,28 @@ using namespace std; * 2) the name of the file containing the true Pareto front * 3) the number of objectives */ -int main(int argc, char ** argv) { - if (argc < 4) { - cerr << "Error using delta. Type: \n Hypervolume " << - " " << endl; - exit(-1); - } - - //Create a new instance of the metric - Hypervolume * qualityIndicator = new Hypervolume(); - //Read the front from the files - vector< vector > solutionFront = - qualityIndicator->utils_->readFront(argv[1]); - vector< vector > trueFront = - qualityIndicator->utils_->readFront(argv[2]); - - //Obtain delta value - double value = qualityIndicator->hypervolume(solutionFront, - trueFront, atoi(argv[3])); - - delete qualityIndicator; - - cout << value << endl; +int main(int argc, char ** argv) +{ + if (argc < 4) + { + cerr << "Error using delta. Type: \n Hypervolume " << + " " << std::endl; + exit(-1); + } + + //Create a new instance of the metric + Hypervolume * qualityIndicator = snew Hypervolume(); + //Read the front from the files + MatrixOfDouble solutionFront = + qualityIndicator->utils_->readFront(argv[1]); + MatrixOfDouble trueFront = + qualityIndicator->utils_->readFront(argv[2]); + + //Obtain delta value + double value = qualityIndicator->hypervolume(solutionFront, + trueFront, atoi(argv[3])); + + delete qualityIndicator; + + std::cout << value << std::endl; } // main diff --git a/src/qualityIndicator/main/InvertedGenerationalDistance_main.cpp b/src/qualityIndicator/main/InvertedGenerationalDistance_main.cpp index 489d418..c6c4f87 100644 --- a/src/qualityIndicator/main/InvertedGenerationalDistance_main.cpp +++ b/src/qualityIndicator/main/InvertedGenerationalDistance_main.cpp @@ -23,7 +23,7 @@ #include -using namespace std; + /** * This method can be invoked from the command line. Three params are required: @@ -31,27 +31,29 @@ using namespace std; * 2) the name of the file containing the true Pareto front * 3) the number of objectives */ -int main(int argc, char ** argv) { - if (argc < 4) { - cerr << "Error using delta. Type: \n InvertedGenerationalDistance " << - " " << endl; - exit(-1); - } - - //Create a new instance of the metric - InvertedGenerationalDistance * qualityIndicator = - new InvertedGenerationalDistance(); - //Read the front from the files - vector< vector > solutionFront = - qualityIndicator->utils_->readFront(argv[1]); - vector< vector > trueFront = - qualityIndicator->utils_->readFront(argv[2]); - - //Obtain delta value - double value = qualityIndicator->invertedGenerationalDistance( - solutionFront, trueFront, atoi(argv[3])); - - delete qualityIndicator; - - cout << value << endl; +int main(int argc, char ** argv) +{ + if (argc < 4) + { + cerr << "Error using delta. Type: \n InvertedGenerationalDistance " << + " " << std::endl; + exit(-1); + } + + //Create a new instance of the metric + InvertedGenerationalDistance * qualityIndicator = + snew InvertedGenerationalDistance(); + //Read the front from the files + MatrixOfDouble solutionFront = + qualityIndicator->utils_->readFront(argv[1]); + MatrixOfDouble trueFront = + qualityIndicator->utils_->readFront(argv[2]); + + //Obtain delta value + double value = qualityIndicator->invertedGenerationalDistance( + solutionFront, trueFront, atoi(argv[3])); + + delete qualityIndicator; + + std::cout << value << std::endl; } // main diff --git a/src/qualityIndicator/main/Spread_main.cpp b/src/qualityIndicator/main/Spread_main.cpp index eb53a0a..e40da82 100644 --- a/src/qualityIndicator/main/Spread_main.cpp +++ b/src/qualityIndicator/main/Spread_main.cpp @@ -31,26 +31,28 @@ using namespace std; * 2) the name of the file containing the true Pareto front * 3) the number of objectives */ -int main(int argc, char ** argv) { - if (argc < 4) { - cerr << "Error using delta. Type: \n Spread " << - " " << endl; - exit(-1); - } - - //Create a new instance of the metric - Spread * qualityIndicator = new Spread(); - //Read the front from the files - vector< vector > solutionFront = - qualityIndicator->utils_->readFront(argv[1]); - vector< vector > trueFront = - qualityIndicator->utils_->readFront(argv[2]); - - //Obtain delta value - double value = qualityIndicator->spread(solutionFront, trueFront, - atoi(argv[3])); - - delete qualityIndicator; - - cout << value << endl; +int main(int argc, char ** argv) +{ + if (argc < 4) + { + cerr << "Error using delta. Type: \n Spread " << + " " << endl; + exit(-1); + } + + //Create a new instance of the metric + Spread * qualityIndicator = new Spread(); + //Read the front from the files + vector< vector > solutionFront = + qualityIndicator->utils_->readFront(argv[1]); + vector< vector > trueFront = + qualityIndicator->utils_->readFront(argv[2]); + + //Obtain delta value + double value = qualityIndicator->spread(solutionFront, trueFront, + atoi(argv[3])); + + delete qualityIndicator; + + cout << value << endl; } // main diff --git a/src/qualityIndicator/util/CMakeLists.txt b/src/qualityIndicator/util/CMakeLists.txt new file mode 100644 index 0000000..294ec59 --- /dev/null +++ b/src/qualityIndicator/util/CMakeLists.txt @@ -0,0 +1,3 @@ +file(GLOB SOURCES "*.cpp" "*.h") +ListToString(SOURCES ";" ${SOURCES}) +LIST_APPEND("${SOURCES}") \ No newline at end of file diff --git a/src/qualityIndicator/util/LexicoGraphicalComparator.cpp b/src/qualityIndicator/util/LexicoGraphicalComparator.cpp index a5279d1..937c20e 100644 --- a/src/qualityIndicator/util/LexicoGraphicalComparator.cpp +++ b/src/qualityIndicator/util/LexicoGraphicalComparator.cpp @@ -20,7 +20,9 @@ #include +#include "JMetalHeader.h" +using namespace JMetal; /** * The compare method compare the objects o1 and o2. @@ -28,23 +30,30 @@ * @param o2 An object that reference a double[] * @return -1 if o1 < o1, 1 if o1 > o2 or 0 in other case. */ -int LexicoGraphicalComparator::compare(void * o1, void * o2) { - //Cast to vector o1 and o2. - vector pointOne = * (vector *) o1; - vector pointTwo = * (vector *) o2; +int LexicoGraphicalComparator::compare(void * o1, void * o2) +{ + //Cast to VectorOfDouble o1 and o2. + VectorOfDouble pointOne = * (VectorOfDouble *) o1; + VectorOfDouble pointTwo = * (VectorOfDouble *) o2; - //To determine the first i, that pointOne[i] != pointTwo[i]; - int index = 0; - while ((index < pointOne.size()) && (index < pointTwo.size()) && - pointOne[index] == pointTwo[index]) { - index++; - } - if ((index >= pointOne.size()) || (index >= pointTwo.size() )) { + //To determine the first i, that pointOne[i] != pointTwo[i]; + int index = 0; + while ((index < pointOne.size()) && (index < pointTwo.size()) && + pointOne[index] == pointTwo[index]) + { + index++; + } + if ((index >= pointOne.size()) || (index >= pointTwo.size() )) + { + return 0; + } + else if (pointOne[index] < pointTwo[index]) + { + return -1; + } + else if (pointOne[index] > pointTwo[index]) + { + return 1; + } return 0; - } else if (pointOne[index] < pointTwo[index]) { - return -1; - } else if (pointOne[index] > pointTwo[index]) { - return 1; - } - return 0; } // compare diff --git a/src/qualityIndicator/util/LexicoGraphicalComparator.h b/src/qualityIndicator/util/LexicoGraphicalComparator.h index a1efc13..4fea8a6 100644 --- a/src/qualityIndicator/util/LexicoGraphicalComparator.h +++ b/src/qualityIndicator/util/LexicoGraphicalComparator.h @@ -22,12 +22,12 @@ #define __LEXICOGRAPHICALCOMPARATOR__ #include -#include -class LexicoGraphicalComparator : public Comparator { +class LexicoGraphicalComparator : public Comparator +{ public: - int compare(void * o1, void * o2); + int compare(void * o1, void * o2); }; diff --git a/src/qualityIndicator/util/MetricsUtil.cpp b/src/qualityIndicator/util/MetricsUtil.cpp index 841cc5c..242049e 100644 --- a/src/qualityIndicator/util/MetricsUtil.cpp +++ b/src/qualityIndicator/util/MetricsUtil.cpp @@ -22,7 +22,7 @@ #include -using namespace std; + /** @@ -30,38 +30,43 @@ using namespace std; * @param path The path to the file that contains the pareto front * @return double [][] whit the pareto front **/ -vector< vector > MetricsUtil::readFront(string path) { +MatrixOfDouble MetricsUtil::readFront(std::string path) +{ - vector< vector > front; + MatrixOfDouble front; - std::ifstream in(path.c_str()); - if( !in ) { - cout << "Error trying to read Pareto Front file: " << path << endl; - exit(-1); - } + std::ifstream in(path.c_str()); + if( !in ) + { + std::cout << "Error trying to read Pareto Front file: " << path << std::endl; + exit(-1); + } - string line; - while( getline(in, line ) ) { + std::string line; + while( getline(in, line ) ) + { - vector list; + VectorOfDouble list; - istringstream iss(line); + istringstream iss(line); - while (iss) { - string token; - iss >> token; - if (token.compare("")!=0) { - //cout << "Substring: " << token << endl; - list.push_back(atof(token.c_str())); - } - } - front.push_back(list); + while (iss) + { + std::string token; + iss >> token; + if (token.compare("")!=0) + { + //std::cout << "Substring: " << token << std::endl; + list.push_back(atof(token.c_str())); + } + } + front.push_back(list); - } + } - in.close(); + in.close(); - return front; + return front; } // readFront @@ -70,27 +75,32 @@ vector< vector > MetricsUtil::readFront(string path) { * front * @param front The pareto front * @param noObjectives Number of objectives in the pareto front - * @return vector A vector of noOjectives values with the maximum values + * @return VectorOfDouble A vector of noOjectives values with the maximum values * for each objective **/ -vector MetricsUtil::getMaximumValues(vector< vector > front, - int noObjectives) { +VectorOfDouble MetricsUtil::getMaximumValues(MatrixOfDouble front, + int noObjectives) +{ - vector maximumValue; + VectorOfDouble maximumValue; - for (int i = 0; i < noObjectives; i++) { - maximumValue.push_back(-std::numeric_limits::max()); - } + for (int i = 0; i < noObjectives; i++) + { + maximumValue.push_back(-std::numeric_limits::max()); + } - for (int i =0; i < front.size(); i++ ) { - for (int j = 0; j < front[i].size(); j++) { - if (front[i][j] > maximumValue[j]) { - maximumValue[j] = front[i][j]; - } - } - } + for (int i =0; i < front.size(); i++ ) + { + for (int j = 0; j < front[i].size(); j++) + { + if (front[i][j] > maximumValue[j]) + { + maximumValue[j] = front[i][j]; + } + } + } - return maximumValue; + return maximumValue; } // getMaximumValues @@ -99,27 +109,32 @@ vector MetricsUtil::getMaximumValues(vector< vector > front, * front * @param front The pareto front * @param noObjectives Number of objectives in the pareto front - * @return vector A vector of noOjectives values with the minimum values + * @return VectorOfDouble A vector of noOjectives values with the minimum values * for each objective **/ -vector MetricsUtil::getMinimumValues(vector< vector > front, - int noObjectives) { +VectorOfDouble MetricsUtil::getMinimumValues(MatrixOfDouble front, + int noObjectives) +{ - vector minimumValue; + VectorOfDouble minimumValue; - for (int i = 0; i < noObjectives; i++) { - minimumValue.push_back(std::numeric_limits::max()); - } + for (int i = 0; i < noObjectives; i++) + { + minimumValue.push_back(std::numeric_limits::max()); + } - for (int i =0; i < front.size(); i++ ) { - for (int j = 0; j < front[i].size(); j++) { - if (front[i][j] < minimumValue[j]) { - minimumValue[j] = front[i][j]; - } + for (int i =0; i < front.size(); i++ ) + { + for (int j = 0; j < front[i].size(); j++) + { + if (front[i][j] < minimumValue[j]) + { + minimumValue[j] = front[i][j]; + } + } } - } - return minimumValue; + return minimumValue; } // getMinimumValues @@ -131,39 +146,44 @@ vector MetricsUtil::getMinimumValues(vector< vector > front, * @param b A point * @return The euclidean distance between the points **/ -double MetricsUtil::distance(vector a, vector b) { +double MetricsUtil::distance(VectorOfDouble a, VectorOfDouble b) +{ - double distance = 0.0; + double distance = 0.0; - for (int i = 0; i < a.size(); i++) { - distance += pow(a[i]-b[i],2.0); - } + for (int i = 0; i < a.size(); i++) + { + distance += pow(a[i]-b[i],2.0); + } - return sqrt(distance); + return sqrt(distance); } // distance /** * Gets the distance between a point and the nearest one in - * a given front (the front is given as vector< vector >) + * a given front (the front is given as MatrixOfDouble) * @param point The point * @param front The front that contains the other points to calculate the * distances * @return The minimum distance between the point and the front **/ -double MetricsUtil::distanceToClosedPoint(vector point, - vector< vector > front) { - - double minDistance = distance(point,front[0]); - - for (int i = 1; i < front.size(); i++) { - double aux = distance(point,front[i]); - if (aux < minDistance) { - minDistance = aux; +double MetricsUtil::distanceToClosedPoint(VectorOfDouble point, + MatrixOfDouble front) +{ + + double minDistance = distance(point,front[0]); + + for (int i = 1; i < front.size(); i++) + { + double aux = distance(point,front[i]); + if (aux < minDistance) + { + minDistance = aux; + } } - } - return minDistance; + return minDistance; } // distanceToClosedPoint @@ -177,19 +197,22 @@ double MetricsUtil::distanceToClosedPoint(vector point, * @return The minimun distances greater than zero between the point and * the front */ -double MetricsUtil::distanceToNearestPoint(vector point, - vector< vector > front) { - - double minDistance = std::numeric_limits::max(); - - for (int i = 0; i < front.size(); i++) { - double aux = distance(point,front[i]); - if ((aux < minDistance) && (aux > 0.0)) { - minDistance = aux; +double MetricsUtil::distanceToNearestPoint(VectorOfDouble point, + MatrixOfDouble front) +{ + + double minDistance = std::numeric_limits::max(); + + for (int i = 0; i < front.size(); i++) + { + double aux = distance(point,front[i]); + if ((aux < minDistance) && (aux > 0.0)) + { + minDistance = aux; + } } - } - return minDistance; + return minDistance; } // distanceToNearestPoint @@ -203,22 +226,25 @@ double MetricsUtil::distanceToNearestPoint(vector point, * @param minimumValue The minimum values allowed * @return the normalized pareto front **/ -vector< vector > MetricsUtil::getNormalizedFront(vector< vector > front, - vector maximumValue, vector minimumValue) { - - vector< vector > normalizedFront; - - for (int i = 0; i < front.size();i++) { - vector list; - for (int j = 0; j < front[i].size(); j++) { - //normalizedFront[i][j] = (front[i][j] - minimumValue[j]) / - // (maximumValue[j] - minimumValue[j]); - list.push_back((front[i][j] - minimumValue[j]) / (maximumValue[j] - minimumValue[j])); +MatrixOfDouble MetricsUtil::getNormalizedFront(MatrixOfDouble front, + VectorOfDouble maximumValue, VectorOfDouble minimumValue) +{ + + MatrixOfDouble normalizedFront; + + for (int i = 0; i < front.size(); i++) + { + VectorOfDouble list; + for (int j = 0; j < front[i].size(); j++) + { + //normalizedFront[i][j] = (front[i][j] - minimumValue[j]) / + // (maximumValue[j] - minimumValue[j]); + list.push_back((front[i][j] - minimumValue[j]) / (maximumValue[j] - minimumValue[j])); + } + normalizedFront.push_back(list); } - normalizedFront.push_back(list); - } - return normalizedFront; + return normalizedFront; } // getNormalizedFront @@ -229,25 +255,33 @@ vector< vector > MetricsUtil::getNormalizedFront(vector< vector * @param front The pareto front to inverse * @return The inverted pareto front **/ -vector< vector > MetricsUtil::invertedFront(vector< vector > front) { - - vector< vector > invertedFront; - - for (int i = 0; i < front.size(); i++) { - vector list; - for (int j = 0; j < front[i].size(); j++) { - if (front[i][j] <= 1.0 && front[i][j]>= 0.0) { - list.push_back(1.0 - front[i][j]); - } else if (front[i][j] > 1.0) { - list.push_back(0.0); - } else if (front[i][j] < 0.0) { - list.push_back(1.0); - } - } - invertedFront.push_back(list); - } - - return invertedFront; +MatrixOfDouble MetricsUtil::invertedFront(MatrixOfDouble front) +{ + + MatrixOfDouble invertedFront; + + for (int i = 0; i < front.size(); i++) + { + VectorOfDouble list; + for (int j = 0; j < front[i].size(); j++) + { + if (front[i][j] <= 1.0 && front[i][j]>= 0.0) + { + list.push_back(1.0 - front[i][j]); + } + else if (front[i][j] > 1.0) + { + list.push_back(0.0); + } + else if (front[i][j] < 0.0) + { + list.push_back(1.0); + } + } + invertedFront.push_back(list); + } + + return invertedFront; } // invertedFront @@ -257,41 +291,47 @@ vector< vector > MetricsUtil::invertedFront(vector< vector > fro * @param path The path of the file containing the data * @return A solution set */ -SolutionSet * MetricsUtil::readNonDominatedSolutionSet(string path) { - - std::ifstream in(path.c_str()); - if( !in ) { - cout << "Error trying to read non dominated solutions file: " - << path << endl; - exit(-1); - } // if - - NonDominatedSolutionList * solutionSet = new NonDominatedSolutionList(); - string line; - - while( getline(in, line ) ) { - - vector list; - istringstream iss(line); - while (iss) { - string token; - iss >> token; - if (token.compare("")!=0) { - //cout << "Substring: " << token << endl; - list.push_back(atof(token.c_str())); - } // if - } // while +SolutionSet * MetricsUtil::readNonDominatedSolutionSet(std::string path) +{ + + std::ifstream in(path.c_str()); + if( !in ) + { + std::cout << "Error trying to read non dominated solutions file: " + << path << std::endl; + exit(-1); + } // if + + NonDominatedSolutionList * solutionSet = snew NonDominatedSolutionList(); + std::string line; + + while( getline(in, line ) ) + { + + VectorOfDouble list; + istringstream iss(line); + while (iss) + { + std::string token; + iss >> token; + if (token.compare("")!=0) + { + //std::cout << "Substring: " << token << std::endl; + list.push_back(atof(token.c_str())); + } // if + } // while + + Solution * solution = snew Solution(list.size()); + for (int i=0; isetObjective(i,list[i]); + } //for + solutionSet->add(solution); - Solution * solution = new Solution(list.size()); - for (int i=0; isetObjective(i,list[i]); - } //for - solutionSet->add(solution); - - } // while + } // while - in.close(); - return solutionSet; + in.close(); + return solutionSet; } // readNonDominatedSolutionSet @@ -302,38 +342,44 @@ SolutionSet * MetricsUtil::readNonDominatedSolutionSet(string path) { * @param path The path of the file containing the data * @return A solution set */ -void MetricsUtil::readNonDominatedSolutionSet(string path, NonDominatedSolutionList * solutionSet) { - - std::ifstream in(path.c_str()); - if( !in ) { - cout << "Error trying to read non dominated solutions file: " - << path << endl; - exit(-1); - } // if - - string line; - - while( getline(in, line ) ) { - - vector list; - istringstream iss(line); - while (iss) { - string token; - iss >> token; - if (token.compare("")!=0) { - //cout << "Substring: " << token << endl; - list.push_back(atof(token.c_str())); - } // if - } // while +void MetricsUtil::readNonDominatedSolutionSet(std::string path, NonDominatedSolutionList * solutionSet) +{ + + std::ifstream in(path.c_str()); + if( !in ) + { + std::cout << "Error trying to read non dominated solutions file: " + << path << std::endl; + exit(-1); + } // if + + std::string line; + + while( getline(in, line ) ) + { + + VectorOfDouble list; + istringstream iss(line); + while (iss) + { + std::string token; + iss >> token; + if (token.compare("")!=0) + { + //std::cout << "Substring: " << token << std::endl; + list.push_back(atof(token.c_str())); + } // if + } // while + + Solution * solution = snew Solution(list.size()); + for (int i=0; isetObjective(i,list[i]); + } //for + solutionSet->add(solution); - Solution * solution = new Solution(list.size()); - for (int i=0; isetObjective(i,list[i]); - } //for - solutionSet->add(solution); - - } // while + } // while - in.close(); + in.close(); } // readNonDominatedSolutionSet diff --git a/src/qualityIndicator/util/MetricsUtil.h b/src/qualityIndicator/util/MetricsUtil.h index 239b696..60d0481 100644 --- a/src/qualityIndicator/util/MetricsUtil.h +++ b/src/qualityIndicator/util/MetricsUtil.h @@ -21,38 +21,38 @@ #ifndef __METRICSUTIL__ #define __METRICSUTIL__ +#include "JMetalHeader.h" #include -#include #include #include #include #include -#include #include #include #include -using namespace std; +using namespace JMetal; /** * @class MetricsUtil * @brief This class provides some utilities to compute quality indicators **/ -class MetricsUtil { +class MetricsUtil +{ public: - vector< vector > readFront(string path); - vector getMaximumValues(vector< vector > front, int noObjectives); - vector getMinimumValues(vector< vector > front, int noObjectives); - double distance(vector a, vector b); - double distanceToClosedPoint(vector point, vector< vector > front); - double distanceToNearestPoint(vector point, vector< vector > front); - vector< vector > getNormalizedFront(vector< vector > front, - vector maximumValue, vector minimumValue); - vector< vector > invertedFront(vector< vector > front); - SolutionSet * readNonDominatedSolutionSet(string path); - void readNonDominatedSolutionSet(string path, NonDominatedSolutionList * solutionSet); + MatrixOfDouble readFront(std::string path); + VectorOfDouble getMaximumValues(MatrixOfDouble front, int noObjectives); + VectorOfDouble getMinimumValues(MatrixOfDouble front, int noObjectives); + double distance(VectorOfDouble a, VectorOfDouble b); + double distanceToClosedPoint(VectorOfDouble point, MatrixOfDouble front); + double distanceToNearestPoint(VectorOfDouble point, MatrixOfDouble front); + MatrixOfDouble getNormalizedFront(MatrixOfDouble front, + VectorOfDouble maximumValue, VectorOfDouble minimumValue); + MatrixOfDouble invertedFront(MatrixOfDouble front); + SolutionSet * readNonDominatedSolutionSet(std::string path); + void readNonDominatedSolutionSet(std::string path, NonDominatedSolutionList * solutionSet); }; #endif /* __METRICSUTIL__ */ diff --git a/src/util/AdaptiveGrid.cpp b/src/util/AdaptiveGrid.cpp index 983ce38..59af53c 100644 --- a/src/util/AdaptiveGrid.cpp +++ b/src/util/AdaptiveGrid.cpp @@ -19,7 +19,7 @@ // along with this program. If not, see . #include "AdaptiveGrid.h" -using namespace std; + /** * Constructor. @@ -28,18 +28,19 @@ using namespace std; * @param objetives Number of objectives of the problem. */ -AdaptiveGrid::AdaptiveGrid(int bisections, int objetives) { - bisections_ = bisections; - objectives_ = objetives ; - lowerLimits_ = new double[objectives_]; - upperLimits_ = new double[objectives_]; - divisionSize_ = new double[objectives_]; +AdaptiveGrid::AdaptiveGrid(int bisections, int objetives) +{ + bisections_ = bisections; + objectives_ = objetives ; + lowerLimits_ = snew double[objectives_]; + upperLimits_ = snew double[objectives_]; + divisionSize_ = snew double[objectives_]; - sizehypercubes_ = (int)pow(2.0,bisections_*objectives_); // Size int * + sizehypercubes_ = (int)pow(2.0,bisections_*objectives_); // Size int * - hypercubes_ = new int[sizehypercubes_]; - for (int i = 0; i < sizehypercubes_;i++) - hypercubes_[i] = 0; + hypercubes_ = snew int[sizehypercubes_]; + for (int i = 0; i < sizehypercubes_; i++) + hypercubes_[i] = 0; }//AdaptativeGrid @@ -48,27 +49,33 @@ AdaptiveGrid::AdaptiveGrid(int bisections, int objetives) { * SolutionSet. * @param solutionSet The SolutionSet considered. */ -void AdaptiveGrid::updateLimits(SolutionSet * solutionSet){ +void AdaptiveGrid::updateLimits(SolutionSet * solutionSet) +{ //Init the lower and upper limits - for (int obj = 0; obj < objectives_; obj++){ - //Set the lower limits to the max real - lowerLimits_[obj] = numeric_limits::max( ); - //Set the upper limits to the min real - upperLimits_[obj] = numeric_limits::min( ); ; + for (int obj = 0; obj < objectives_; obj++) + { + //Set the lower limits to the max real + lowerLimits_[obj] = numeric_limits::max( ); + //Set the upper limits to the min real + upperLimits_[obj] = numeric_limits::min( ); ; } // for //Find the max and min limits of objetives into the population - for (int ind = 0; ind < solutionSet->size(); ind++){ - Solution * tmpIndividual = solutionSet->get(ind); - for (int obj = 0; obj < objectives_; obj++) { - if (tmpIndividual->getObjective(obj) < lowerLimits_[obj]) { - lowerLimits_[obj] = tmpIndividual->getObjective(obj); - } - if (tmpIndividual->getObjective(obj) > upperLimits_[obj]) { - upperLimits_[obj] = tmpIndividual->getObjective(obj); - } - } // for + for (int ind = 0; ind < solutionSet->size(); ind++) + { + Solution * tmpIndividual = solutionSet->get(ind); + for (int obj = 0; obj < objectives_; obj++) + { + if (tmpIndividual->getObjective(obj) < lowerLimits_[obj]) + { + lowerLimits_[obj] = tmpIndividual->getObjective(obj); + } + if (tmpIndividual->getObjective(obj) > upperLimits_[obj]) + { + upperLimits_[obj] = tmpIndividual->getObjective(obj); + } + } // for } // for }//updateLimits @@ -80,21 +87,23 @@ void AdaptiveGrid::updateLimits(SolutionSet * solutionSet){ * @param solutionSet The SolutionSet considered. */ -void AdaptiveGrid::addSolutionSet(SolutionSet * solutionSet){ +void AdaptiveGrid::addSolutionSet(SolutionSet * solutionSet) +{ //Calculate the location of all individuals and update the grid mostPopulated_ = 0; int location_; - for (int ind = 0; ind < solutionSet->size();ind++){ - location_ = location(solutionSet->get(ind)); - hypercubes_[location_]++; - if (hypercubes_[location_] > hypercubes_[mostPopulated_]) - mostPopulated_ = location_; + for (int ind = 0; ind < solutionSet->size(); ind++) + { + location_ = location(solutionSet->get(ind)); + hypercubes_[location_]++; + if (hypercubes_[location_] > hypercubes_[mostPopulated_]) + mostPopulated_ = location_; } // for //The grid has been updated, so also update ocuppied's hypercubes calculateOccupied(); - } // addSolutionSet +} // addSolutionSet /** @@ -102,23 +111,26 @@ void AdaptiveGrid::addSolutionSet(SolutionSet * solutionSet){ * in a specific SolutionSet. * @param solutionSet The SolutionSet. */ -void AdaptiveGrid::updateGrid(SolutionSet * solutionSet){ +void AdaptiveGrid::updateGrid(SolutionSet * solutionSet) +{ //Update lower and upper limits updateLimits(solutionSet); //Calculate the division size - for (int obj = 0; obj < objectives_; obj++){ - divisionSize_[obj] = upperLimits_[obj] - lowerLimits_[obj]; + for (int obj = 0; obj < objectives_; obj++) + { + divisionSize_[obj] = upperLimits_[obj] - lowerLimits_[obj]; } // for //Clean the hypercubes - for (int i = 0; i < sizehypercubes_;i++) { - hypercubes_[i] = 0; + for (int i = 0; i < sizehypercubes_; i++) + { + hypercubes_[i] = 0; } //Add the population addSolutionSet(solutionSet); - } //updateGrid +} //updateGrid /** @@ -129,235 +141,270 @@ void AdaptiveGrid::updateGrid(SolutionSet * solutionSet){ * @param solution Solution considered to update the grid. * @param solutionSet SolutionSet used to update the grid. */ -void AdaptiveGrid::updateGrid(Solution * solution, SolutionSet * solutionSet, int eval){ +void AdaptiveGrid::updateGrid(Solution * solution, SolutionSet * solutionSet, int eval) +{ int location_ = location(solution); - if (location_ == -1) {//Re-build the Adaptative-Grid - //Update lower and upper limits - updateLimits(solutionSet); - - //Actualize the lower and upper limits whit the individual - for (int obj = 0; obj < objectives_; obj++){ - if (solution->getObjective(obj) < lowerLimits_[obj]) - lowerLimits_[obj] = solution->getObjective(obj); - if (solution->getObjective(obj) > upperLimits_[obj]) - upperLimits_[obj] = solution->getObjective(obj); - } // for - - //Calculate the division size - for (int obj = 0; obj < objectives_; obj++){ - divisionSize_[obj] = upperLimits_[obj] - lowerLimits_[obj]; - } + if (location_ == -1) //Re-build the Adaptative-Grid + { + //Update lower and upper limits + updateLimits(solutionSet); + + //Actualize the lower and upper limits whit the individual + for (int obj = 0; obj < objectives_; obj++) + { + if (solution->getObjective(obj) < lowerLimits_[obj]) + lowerLimits_[obj] = solution->getObjective(obj); + if (solution->getObjective(obj) > upperLimits_[obj]) + upperLimits_[obj] = solution->getObjective(obj); + } // for - //Clean the hypercube - for (int i = 0; i < sizehypercubes_; i++) { - hypercubes_[i] = 0; - } + //Calculate the division size + for (int obj = 0; obj < objectives_; obj++) + { + divisionSize_[obj] = upperLimits_[obj] - lowerLimits_[obj]; + } - //add the population - addSolutionSet(solutionSet); + //Clean the hypercube + for (int i = 0; i < sizehypercubes_; i++) + { + hypercubes_[i] = 0; + } + + //add the population + addSolutionSet(solutionSet); } // if - } //updateGrid +} //updateGrid /** * Calculates the hypercube of a solution. * @param solution The Solution. */ -int AdaptiveGrid::location(Solution * solution){ +int AdaptiveGrid::location(Solution * solution) +{ //Create a int [] to store the range of each objetive - int * position = new int[objectives_]; + int * position = snew int[objectives_]; //Calculate the position for each objetive - for (int obj = 0; obj < objectives_; obj++) { - - position[obj] = 0; //Inicialize - - if ((solution->getObjective(obj) > upperLimits_[obj]) - || (solution->getObjective(obj) < lowerLimits_[obj])) - return -1; - else if (solution->getObjective(obj) ==lowerLimits_[obj]) - position[obj] = 0; - else if (solution->getObjective(obj) ==upperLimits_[obj]) - position[obj] = ((int)pow(2.0,bisections_))-1; - else { - double tmpSize = divisionSize_[obj]; - double value = solution->getObjective(obj); - double account = lowerLimits_[obj]; - int ranges = (int) pow(2.0,bisections_); - for (int b = 0; b < bisections_; b++){ - tmpSize /= 2.0; - ranges /= 2; - if (value > (account + tmpSize)){ - position[obj] += ranges; - account += tmpSize; - } // if - } // for - } // if + for (int obj = 0; obj < objectives_; obj++) + { + + position[obj] = 0; //Inicialize + + if ((solution->getObjective(obj) > upperLimits_[obj]) + || (solution->getObjective(obj) < lowerLimits_[obj])) + { + delete [] position; + return -1; + } + else if (solution->getObjective(obj) ==lowerLimits_[obj]) + position[obj] = 0; + else if (solution->getObjective(obj) ==upperLimits_[obj]) + position[obj] = ((int)pow(2.0,bisections_))-1; + else + { + double tmpSize = divisionSize_[obj]; + double value = solution->getObjective(obj); + double account = lowerLimits_[obj]; + int ranges = (int) pow(2.0,bisections_); + for (int b = 0; b < bisections_; b++) + { + tmpSize /= 2.0; + ranges /= 2; + if (value > (account + tmpSize)) + { + position[obj] += ranges; + account += tmpSize; + } // if + } // for + } // if } //Calcualate the location into the hypercubes int location = 0; - for (int obj = 0; obj < objectives_; obj++) { - location += position[obj] * (int)pow(2.0,obj * bisections_); - } + for (int obj = 0; obj < objectives_; obj++) + { + location += position[obj] * (int)pow(2.0,obj * bisections_); + } + delete [] position; return location; - } //location +} //location /** * Returns the value of the most populated hypercube. * @return The hypercube with the maximum number of solutions. */ -int AdaptiveGrid::getMostPopulated(){ +int AdaptiveGrid::getMostPopulated() +{ return mostPopulated_; - } // getMostPopulated +} // getMostPopulated - /** - * Returns the number of solutions into a specific hypercube. - * @param location Number of the hypercube. - * @return The number of solutions into a specific hypercube. - */ -int AdaptiveGrid::getLocationDensity(int location){ - return hypercubes_[location]; - } //getLocationDensity +/** +* Returns the number of solutions into a specific hypercube. +* @param location Number of the hypercube. +* @return The number of solutions into a specific hypercube. +*/ +int AdaptiveGrid::getLocationDensity(int location) +{ + return hypercubes_[location]; +} //getLocationDensity - /** - * Decreases the number of solutions into a specific hypercube. - * @param location Number of hypercube. - */ -void AdaptiveGrid::removeSolution(int location) { +/** +* Decreases the number of solutions into a specific hypercube. +* @param location Number of hypercube. +*/ +void AdaptiveGrid::removeSolution(int location) +{ //Decrease the solutions in the location specified. hypercubes_[location]--; //Update the most poblated hypercube if (location == mostPopulated_) - for (int i = 0; i < sizehypercubes_;i++) - if (hypercubes_[i] > hypercubes_[mostPopulated_]) - mostPopulated_ = i; + for (int i = 0; i < sizehypercubes_; i++) + if (hypercubes_[i] > hypercubes_[mostPopulated_]) + mostPopulated_ = i; //If hypercubes[location] now becomes to zero, then update ocupped hypercubes if (hypercubes_[location]==0) - calculateOccupied(); - } //removeSolution + calculateOccupied(); +} //removeSolution /** * Increases the number of solutions into a specific hypercube. * @param location Number of hypercube. */ -void AdaptiveGrid::addSolution(int location) { +void AdaptiveGrid::addSolution(int location) +{ //Increase the solutions in the location specified. hypercubes_[location]++; //Update the most poblated hypercube if (hypercubes_[location] > hypercubes_[mostPopulated_]) - mostPopulated_ = location; + mostPopulated_ = location; //if hypercubes[location] becomes to one, then recalculate //the occupied hypercubes if (hypercubes_[location] == 1) - calculateOccupied(); - } //addSolution + calculateOccupied(); +} //addSolution - /** - * Returns the number of bi-divisions performed in each objective. - * @return the number of bi-divisions. - */ - int AdaptiveGrid::getBisections() { +/** +* Returns the number of bi-divisions performed in each objective. +* @return the number of bi-divisions. +*/ +int AdaptiveGrid::getBisections() +{ return bisections_; - } //getBisections - - /** - * Retunrns a String representing the grid. - * @return The String. - */ - string AdaptiveGrid::toString() { - stringstream result; +} //getBisections + +/** + * Retunrns a String representing the grid. + * @return The String. + */ +std::string AdaptiveGrid::toString() +{ + stringstream result; result << "Grid\n"; - for (int obj = 0; obj < objectives_; obj++){ - result << "Objective " << obj << " " << lowerLimits_[obj] << " - " << upperLimits_[obj] << "\n"; + for (int obj = 0; obj < objectives_; obj++) + { + result << "Objective " << obj << " " << lowerLimits_[obj] << " - " << upperLimits_[obj] << "\n"; } // for return result.str(); - } // toString +} // toString - /** - * Returns a random hypercube using a rouleteWheel method. - * @return the number of the selected hypercube. - */ -int AdaptiveGrid::rouletteWheel(){ +/** + * Returns a random hypercube using a rouleteWheel method. +* @return the number of the selected hypercube. +*/ +int AdaptiveGrid::rouletteWheel() +{ //Calculate the inverse sum double inverseSum = 0.0; - for (int i = 0; i < sizehypercubes_; i++) { - if (hypercubes_[i] > 0) { - inverseSum += 1.0 / (double)hypercubes_[i]; - } + for (int i = 0; i < sizehypercubes_; i++) + { + if (hypercubes_[i] > 0) + { + inverseSum += 1.0 / (double)hypercubes_[i]; + } } //Calculate a random value between 0 and sumaInversa double random = PseudoRandom::randDouble(0.0,inverseSum); int hypercube = 0; double accumulatedSum = 0.0; - while (hypercube < sizehypercubes_){ - if (hypercubes_[hypercube] > 0) { - accumulatedSum += 1.0 / (double)hypercubes_[hypercube]; - } // if - - if (accumulatedSum > random) { - return hypercube; - } // if - - hypercube++; + while (hypercube < sizehypercubes_) + { + if (hypercubes_[hypercube] > 0) + { + accumulatedSum += 1.0 / (double)hypercubes_[hypercube]; + } // if + + if (accumulatedSum > random) + { + return hypercube; + } // if + + hypercube++; } // while return hypercube; - } //rouletteWheel +} //rouletteWheel - /** - * Calculates the number of hypercubes having one or more solutions. - * return the number of hypercubes with more than zero solutions. - */ -int AdaptiveGrid::calculateOccupied(){ +/** +* Calculates the number of hypercubes having one or more solutions. +* return the number of hypercubes with more than zero solutions. +*/ +int AdaptiveGrid::calculateOccupied() +{ int total = 0; - for (int i = 0; i < sizehypercubes_; i++) { - if (hypercubes_[i] > 0) { - total++; - } // if + for (int i = 0; i < sizehypercubes_; i++) + { + if (hypercubes_[i] > 0) + { + total++; + } // if } // for occupiedsize_ = total; - occupied_ = new int[occupiedsize_]; + occupied_ = snew int[occupiedsize_]; int base = 0; - for (int i = 0; i < sizehypercubes_;i++){ - if (hypercubes_[i] > 0){ - occupied_[base] = i; - base++; - } // if + for (int i = 0; i < sizehypercubes_; i++) + { + if (hypercubes_[i] > 0) + { + occupied_[base] = i; + base++; + } // if } // for return total; - } //calculateOcuppied +} //calculateOcuppied - /** - * Returns the number of hypercubes with more than zero solutions. - * @return the number of hypercubes with more than zero solutions. - */ -int AdaptiveGrid::occupiedHypercubes(){ +/** + * Returns the number of hypercubes with more than zero solutions. + * @return the number of hypercubes with more than zero solutions. + */ +int AdaptiveGrid::occupiedHypercubes() +{ return occupiedsize_; - } // occupiedHypercubes +} // occupiedHypercubes - /** - * Returns a random hypercube that has more than zero solutions. - * @return The hypercube. - */ -int AdaptiveGrid:: randomOccupiedHypercube(){ +/** + * Returns a random hypercube that has more than zero solutions. + * @return The hypercube. + */ +int AdaptiveGrid:: randomOccupiedHypercube() +{ int rand = PseudoRandom::randInt(0,occupiedsize_-1); return occupied_[rand]; - } //randomOccupiedHypercube +} //randomOccupiedHypercube diff --git a/src/util/AdaptiveGrid.h b/src/util/AdaptiveGrid.h index 648b814..d9d631d 100644 --- a/src/util/AdaptiveGrid.h +++ b/src/util/AdaptiveGrid.h @@ -32,73 +32,74 @@ /** * This class implements some utilities for calculating distances */ -class AdaptiveGrid { +class AdaptiveGrid +{ private: - /** - * Number of bi-divisions of the objective space - */ - int bisections_; + /** + * Number of bi-divisions of the objective space + */ + int bisections_; - /** - * Objectives of the problem - */ - int objectives_; + /** + * Objectives of the problem + */ + int objectives_; - /** - * Number of solutions into a specific hypercube in the adaptative grid - */ - int * hypercubes_; + /** + * Number of solutions into a specific hypercube in the adaptative grid + */ + int * hypercubes_; - int sizehypercubes_; - /** - * - * Grid lower bounds - */ - double * lowerLimits_; + int sizehypercubes_; + /** + * + * Grid lower bounds + */ + double * lowerLimits_; - /** - * Grid upper bounds - */ - double * upperLimits_; + /** + * Grid upper bounds + */ + double * upperLimits_; - /** - * Size of hypercube for each dimension - */ - double * divisionSize_; + /** + * Size of hypercube for each dimension + */ + double * divisionSize_; - /** - * Hypercube with maximum number of solutions - */ - int mostPopulated_; + /** + * Hypercube with maximum number of solutions + */ + int mostPopulated_; - /** - * Indicates when an hypercube has solutions - */ - int * occupied_; + /** + * Indicates when an hypercube has solutions + */ + int * occupied_; - int occupiedsize_; + int occupiedsize_; - void updateLimits(SolutionSet * solutionSet); + void updateLimits(SolutionSet * solutionSet); public: - AdaptiveGrid(int bisections, int objetives); - - void addSolutionSet(SolutionSet * solutionSet); - void updateGrid(SolutionSet * solutionSet); - void updateGrid(Solution * solution, SolutionSet * solutionSet, int eval); - int location(Solution * solution); - int getMostPopulated(); - int getLocationDensity(int location); - void removeSolution(int location); - void addSolution(int location); - int getBisections(); - string toString(); - int rouletteWheel(); - int calculateOccupied(); - int occupiedHypercubes(); - int randomOccupiedHypercube(); + AdaptiveGrid(int bisections, int objetives); + + void addSolutionSet(SolutionSet * solutionSet); + void updateGrid(SolutionSet * solutionSet); + void updateGrid(Solution * solution, SolutionSet * solutionSet, int eval); + int location(Solution * solution); + int getMostPopulated(); + int getLocationDensity(int location); + void removeSolution(int location); + void addSolution(int location); + int getBisections(); + std::string toString(); + int rouletteWheel(); + int calculateOccupied(); + int occupiedHypercubes(); + int randomOccupiedHypercube(); }; diff --git a/src/util/AdaptiveRandomNeighborhood.cpp b/src/util/AdaptiveRandomNeighborhood.cpp index a9b19ff..66e7f22 100644 --- a/src/util/AdaptiveRandomNeighborhood.cpp +++ b/src/util/AdaptiveRandomNeighborhood.cpp @@ -31,19 +31,21 @@ * Constructor. * Defines a neighborhood of a given size. */ -AdaptiveRandomNeighborhood::AdaptiveRandomNeighborhood(SolutionSet * solutionSet, int numberOfRandomNeighbours) { - solutionSet_ = solutionSet; - numberOfRandomNeighbours_ = numberOfRandomNeighbours; - //problem_ = solutionSet_->get(0)->getProblem() ; - - //list_ = new int * [solutionSet_->size()]; - - for (int i = 0; i < solutionSet_->size(); i++) { - //list_[i] = new int [] - vector list_i; - list_i.push_back(i); - list_.push_back(list_i); - } +AdaptiveRandomNeighborhood::AdaptiveRandomNeighborhood(SolutionSet * solutionSet, int numberOfRandomNeighbours) +{ + solutionSet_ = solutionSet; + numberOfRandomNeighbours_ = numberOfRandomNeighbours; + //problem_ = solutionSet_->get(0)->getProblem() ; + + //list_ = snew int * [solutionSet_->size()]; + + for (int i = 0; i < solutionSet_->size(); i++) + { + //list_[i] = snew int [] + VectorOfInteger list_i; + list_i.push_back(i); + list_.push_back(list_i); + } // if(std::find(v.begin(), v.end(), x) != v.end()) { // /* v contains x */ @@ -51,90 +53,111 @@ AdaptiveRandomNeighborhood::AdaptiveRandomNeighborhood(SolutionSet * solutionSet // /* v does not contain x */ // } - //cout << "list: " << list_ << endl; - for (int i = 0; i < solutionSet_->size(); i++) { - //list_.at(i).push_back(i); - for (int j = 0; j < numberOfRandomNeighbours_; j++) { - int random = PseudoRandom::randInt(0, solutionSet_->size() - 1); - //cout << "i: " << i >> " random: " << random << " listb: " << list_at(random) << endl; - //if (!list_.at(random).contains((Integer) i)) - if (find(list_.at(random).begin(), list_.at(random).end(), i) == list_.at(random).end()) { - list_.at(random).push_back(i); - } + //std::cout << "list: " << list_ << std::endl; + for (int i = 0; i < solutionSet_->size(); i++) + { + //list_.at(i).push_back(i); + for (int j = 0; j < numberOfRandomNeighbours_; j++) + { + int random = PseudoRandom::randInt(0, solutionSet_->size() - 1); + //std::cout << "i: " << i >> " random: " << random << " listb: " << list_at(random) << std::endl; + //if (!list_.at(random).contains((Integer) i)) + if (find(list_.at(random).begin(), list_.at(random).end(), i) == list_.at(random).end()) + { + list_.at(random).push_back(i); + } + } } - } - //cout << "L: " << list_ << endl; - cout << "L:" << endl; - for (int i = 0; i < list_.size(); i++) { - cout << "\t["; - for (int j = 0; j < list_.at(i).size(); j++) { - cout << list_.at(i).at(j); - if (j < list_.at(i).size()-1) { - cout << ","; - } else { - cout << "]" << endl; - } + //std::cout << "L: " << list_ << std::endl; + std::cout << "L:" << std::endl; + for (int i = 0; i < list_.size(); i++) + { + std::cout << "\t["; + for (int j = 0; j < list_.at(i).size(); j++) + { + std::cout << list_.at(i).at(j); + if (j < list_.at(i).size()-1) + { + std::cout << ","; + } + else + { + std::cout << "]" << std::endl; + } + } } - } } -vector AdaptiveRandomNeighborhood::getNeighbors(int i) { - if (i > list_.size()) { - cerr << "Error in AdaptiveRandomNeighborhood.getNeighbors" - << "the parameter " << i << " is less than " << list_.size() - << endl; - exit(-1); - } - return list_.at(i); +VectorOfInteger AdaptiveRandomNeighborhood::getNeighbors(int i) +{ + if (i > list_.size()) + { + cerr << "Error in AdaptiveRandomNeighborhood.getNeighbors" + << "the parameter " << i << " is less than " << list_.size() + << std::endl; + exit(-1); + } + return list_.at(i); } -int AdaptiveRandomNeighborhood::getNumberOfRandomNeighbours() { - return numberOfRandomNeighbours_; +int AdaptiveRandomNeighborhood::getNumberOfRandomNeighbours() +{ + return numberOfRandomNeighbours_; } -SolutionSet * AdaptiveRandomNeighborhood::getBestFitnessSolutionInNeighborhood(Comparator * comparator) { - SolutionSet * result = new SolutionSet(); - for (int i = 0; i < list_.size(); i++) { - Solution * bestSolution = solutionSet_->get(list_.at(i).at(0)); - for (int j = 1; j < list_.at(i).size(); j++) { - if (comparator->compare(bestSolution, solutionSet_->get(list_.at(i).at(j))) > 0) { - bestSolution = solutionSet_->get(list_.at(i).at(j)); - } +SolutionSet * AdaptiveRandomNeighborhood::getBestFitnessSolutionInNeighborhood(Comparator * comparator) +{ + SolutionSet * result = snew SolutionSet(); + for (int i = 0; i < list_.size(); i++) + { + Solution * bestSolution = solutionSet_->get(list_.at(i).at(0)); + for (int j = 1; j < list_.at(i).size(); j++) + { + if (comparator->compare(bestSolution, solutionSet_->get(list_.at(i).at(j))) > 0) + { + bestSolution = solutionSet_->get(list_.at(i).at(j)); + } + } + result->add(bestSolution); } - result->add(bestSolution); - } - return result; + return result; } -vector> AdaptiveRandomNeighborhood::getNeighborhood() { - return list_; +MatrixOfInteger AdaptiveRandomNeighborhood::getNeighborhood() +{ + return list_; } -void AdaptiveRandomNeighborhood::recompute() { - list_.clear(); +void AdaptiveRandomNeighborhood::recompute() +{ + list_.clear(); - for (int i = 0; i < solutionSet_->size(); i++) { - //list_[i] = new int [] - vector list_i; - list_i.push_back(i); - list_.push_back(list_i); - } + for (int i = 0; i < solutionSet_->size(); i++) + { + //list_[i] = snew int [] + VectorOfInteger list_i; + list_i.push_back(i); + list_.push_back(list_i); + } - for (int i = 0; i < solutionSet_->size(); i++) { - for (int j = 0; j < numberOfRandomNeighbours_; j++) { - int random = PseudoRandom::randInt(0, solutionSet_->size() - 1); - //if (!list_.at(random).contains((Integer) i)) - if (find(list_.at(random).begin(), list_.at(random).end(), i) == list_.at(random).end()) { - list_.at(random).push_back(i); - } + for (int i = 0; i < solutionSet_->size(); i++) + { + for (int j = 0; j < numberOfRandomNeighbours_; j++) + { + int random = PseudoRandom::randInt(0, solutionSet_->size() - 1); + //if (!list_.at(random).contains((Integer) i)) + if (find(list_.at(random).begin(), list_.at(random).end(), i) == list_.at(random).end()) + { + list_.at(random).push_back(i); + } + } } - } } diff --git a/src/util/AdaptiveRandomNeighborhood.h b/src/util/AdaptiveRandomNeighborhood.h index 617060a..c3ae50d 100644 --- a/src/util/AdaptiveRandomNeighborhood.h +++ b/src/util/AdaptiveRandomNeighborhood.h @@ -25,34 +25,24 @@ #include #include #include - -#include #include -//#include - -using namespace std; /** * Class representing an adaptive random neighborhood */ -class AdaptiveRandomNeighborhood { - -private: - - SolutionSet * solutionSet_; - vector> list_; - int numberOfRandomNeighbours_; - +class AdaptiveRandomNeighborhood +{ +protected: + SolutionSet * solutionSet_ = nullptr; + MatrixOfInteger list_; + int numberOfRandomNeighbours_; public: - - AdaptiveRandomNeighborhood(SolutionSet * solutionSet, int numberOfRandomNeighbours); - vector getNeighbors(int i); - int getNumberOfRandomNeighbours(); - SolutionSet * getBestFitnessSolutionInNeighborhood(Comparator * comparator); - vector> getNeighborhood(); - void recompute(); - //string toString(); - + AdaptiveRandomNeighborhood(SolutionSet * solutionSet, int numberOfRandomNeighbours); + VectorOfInteger getNeighbors(int i); + int getNumberOfRandomNeighbours(); + SolutionSet * getBestFitnessSolutionInNeighborhood(Comparator * comparator); + MatrixOfInteger getNeighborhood(); + void recompute(); }; // AdaptiveRandomNeighborhood #endif /* __ADAPTIVE_RANDOM_NEIGHBORHOOD__ */ diff --git a/src/util/CMakeLists.txt b/src/util/CMakeLists.txt new file mode 100644 index 0000000..e33bba1 --- /dev/null +++ b/src/util/CMakeLists.txt @@ -0,0 +1,6 @@ +file(GLOB SOURCES "*.cpp" "*.h") +ListToString(SOURCES ";" ${SOURCES}) +LIST_APPEND("${SOURCES}") +add_subdirectory(archive) +add_subdirectory(comparators) +add_subdirectory(wrapper) \ No newline at end of file diff --git a/src/util/Distance.cpp b/src/util/Distance.cpp index 25cfb4e..00b159c 100644 --- a/src/util/Distance.cpp +++ b/src/util/Distance.cpp @@ -32,8 +32,9 @@ /** * Constructor. */ -Distance::Distance() { - //do nothing. +Distance::Distance() +{ + //do nothing. } // Distance @@ -43,29 +44,33 @@ Distance::Distance() { * @param solutionSet The SolutionSet. * @return a matrix with distances. */ -double ** Distance::distanceMatrix(SolutionSet * solutionSet) { - Solution * solutionI; - Solution * solutionJ; - - //The matrix of distances - int size = solutionSet->size(); - double ** distance;// = new double [size][size]; - for (int i = 0; i < solutionSet->size(); i++){ - distance[i] = new double[size]; - } - //-> Calculate the distances - for (int i = 0; i < solutionSet->size(); i++){ - distance[i][i] = 0.0; - solutionI = solutionSet->get(i); - for (int j = i + 1; j < solutionSet->size(); j++){ - solutionJ = solutionSet->get(j); - distance[i][j] = this->distanceBetweenObjectives(solutionI,solutionJ); - distance[j][i] = distance[i][j]; +double ** Distance::distanceMatrix(SolutionSet * solutionSet) +{ + Solution * solutionI; + Solution * solutionJ; + + //The matrix of distances + int size = solutionSet->size(); + double ** distance = nullptr;// = snew double [size][size]; + for (int i = 0; i < solutionSet->size(); i++) + { + distance[i] = snew double[size]; + } + //-> Calculate the distances + for (int i = 0; i < solutionSet->size(); i++) + { + distance[i][i] = 0.0; + solutionI = solutionSet->get(i); + for (int j = i + 1; j < solutionSet->size(); j++) + { + solutionJ = solutionSet->get(j); + distance[i][j] = this->distanceBetweenObjectives(solutionI,solutionJ); + distance[j][i] = distance[i][j]; + } // for } // for - } // for - //->Return the matrix of distances - return distance; + //->Return the matrix of distances + return distance; } // distanceMatrix @@ -77,19 +82,21 @@ double ** Distance::distanceMatrix(SolutionSet * solutionSet) { * @return The minimum distance between solution and the set. */ double Distance::distanceToSolutionSetInObjectiveSpace(Solution *solution, - SolutionSet * solutionSet) { - //At start point the distance is the max - double distance = std::numeric_limits::max(); - - // found the min distance respect to population - for (int i = 0; i < solutionSet->size();i++){ - double aux = this->distanceBetweenObjectives(solution,solutionSet->get(i)); - if (aux < distance) - distance = aux; - } // for - - //->Return the best distance - return distance; + SolutionSet * solutionSet) +{ + //At start point the distance is the max + double distance = std::numeric_limits::max(); + + // found the min distance respect to population + for (int i = 0; i < solutionSet->size(); i++) + { + double aux = this->distanceBetweenObjectives(solution,solutionSet->get(i)); + if (aux < distance) + distance = aux; + } // for + + //->Return the best distance + return distance; } // distanceToSolutionSetinObjectiveSpace @@ -101,19 +108,21 @@ double Distance::distanceToSolutionSetInObjectiveSpace(Solution *solution, * @return The minimum distance between solution and the set. */ double Distance::distanceToSolutionSetInSolutionSpace(Solution * solution, - SolutionSet * solutionSet) { - //At start point the distance is the max - double distance = std::numeric_limits::max(); - - // found the min distance respect to population - for (int i = 0; i < solutionSet->size(); i++) { - double aux = this->distanceBetweenSolutions(solution,solutionSet->get(i)); - if (aux < distance) - distance = aux; - } // for - - //->Return the best distance - return distance; + SolutionSet * solutionSet) +{ + //At start point the distance is the max + double distance = std::numeric_limits::max(); + + // found the min distance respect to population + for (int i = 0; i < solutionSet->size(); i++) + { + double aux = this->distanceBetweenSolutions(solution,solutionSet->get(i)); + if (aux < distance) + distance = aux; + } // for + + //->Return the best distance + return distance; } // distanceToSolutionSetInSolutionSpace @@ -123,22 +132,24 @@ double Distance::distanceToSolutionSetInSolutionSpace(Solution * solution, * @param solutionJ The second Solution. * @return the distance between solutions. */ -double Distance::distanceBetweenSolutions(Solution * solutionI, Solution * solutionJ) { - //->Obtain his decision variables - Variable ** decisionVariableI = solutionI->getDecisionVariables(); - Variable ** decisionVariableJ = solutionJ->getDecisionVariables(); - - double diff; //Auxiliar var - double distance = 0.0; - //-> Calculate the Euclidean distance - for (int i = 0; i < solutionI->getNumberOfVariables(); i++){ - diff = decisionVariableI[i]->getValue() - - decisionVariableJ[i]->getValue(); - distance += pow(diff,2.0); - } // for - - //-> Return the euclidean distance - return sqrt(distance); +double Distance::distanceBetweenSolutions(Solution * solutionI, Solution * solutionJ) +{ + //->Obtain his decision variables + Variable ** decisionVariableI = solutionI->getDecisionVariables(); + Variable ** decisionVariableJ = solutionJ->getDecisionVariables(); + + double diff; //Auxiliar var + double distance = 0.0; + //-> Calculate the Euclidean distance + for (int i = 0; i < solutionI->getNumberOfVariables(); i++) + { + diff = decisionVariableI[i]->getValue() - + decisionVariableJ[i]->getValue(); + distance += pow(diff,2.0); + } // for + + //-> Return the euclidean distance + return sqrt(distance); } // distanceBetweenSolutions @@ -148,17 +159,19 @@ double Distance::distanceBetweenSolutions(Solution * solutionI, Solution * solut * @param solutionJ The second Solution. * @return the distance between solutions in objective space. */ -double Distance::distanceBetweenObjectives(Solution * solutionI, Solution * solutionJ) { - double diff; //Auxiliar var - double distance = 0.0; - //-> Calculate the euclidean distance - for (int nObj = 0; nObj < solutionI->getNumberOfObjectives(); nObj++){ - diff = solutionI->getObjective(nObj) - solutionJ->getObjective(nObj); - distance += pow(diff,2.0); - } // for - - //Return the euclidean distance - return sqrt(distance); +double Distance::distanceBetweenObjectives(Solution * solutionI, Solution * solutionJ) +{ + double diff; //Auxiliar var + double distance = 0.0; + //-> Calculate the euclidean distance + for (int nObj = 0; nObj < solutionI->getNumberOfObjectives(); nObj++) + { + diff = solutionI->getObjective(nObj) - solutionJ->getObjective(nObj); + distance += pow(diff,2.0); + } // for + + //Return the euclidean distance + return sqrt(distance); } // distanceBetweenObjectives @@ -167,58 +180,64 @@ double Distance::distanceBetweenObjectives(Solution * solutionI, Solution * solu * @param solutionSet The SolutionSet. * @param nObjs Number of objectives. */ -void Distance::crowdingDistanceAssignment(SolutionSet * solutionSet, int nObjs) { - int size = solutionSet->size(); - - if (size == 0) - return; - - if (size == 1) { - solutionSet->get(0)->setCrowdingDistance(std::numeric_limits::max()); - return; - } // if - - if (size == 2) { - solutionSet->get(0)->setCrowdingDistance(std::numeric_limits::max()); - solutionSet->get(1)->setCrowdingDistance(std::numeric_limits::max()); - return; - } // if - - //Use a new SolutionSet to evite alter original solutionSet - SolutionSet * front = new SolutionSet(size); - for (int i = 0; i < size; i++){ - front->add(solutionSet->get(i)); - } - - for (int i = 0; i < size; i++) - front->get(i)->setCrowdingDistance(0.0); - - double objetiveMaxn; - double objetiveMinn; - double distance; - - for (int i = 0; isort(c); - delete c; - objetiveMinn = front->get(0)->getObjective(i); - objetiveMaxn = front->get(front->size()-1)->getObjective(i); - - //Set de crowding distance - front->get(0)->setCrowdingDistance(std::numeric_limits::max()); - front->get(size-1)->setCrowdingDistance(std::numeric_limits::max()); - - for (int j = 1; j < size-1; j++) { - distance = front->get(j+1)->getObjective(i) - front->get(j-1)->getObjective(i); - distance = distance / (objetiveMaxn - objetiveMinn); - distance += front->get(j)->getCrowdingDistance(); - front->get(j)->setCrowdingDistance(distance); +void Distance::crowdingDistanceAssignment(SolutionSet * solutionSet, int nObjs) +{ + int size = solutionSet->size(); + + if (size == 0) + return; + + if (size == 1) + { + solutionSet->get(0)->setCrowdingDistance(std::numeric_limits::max()); + return; + } // if + + if (size == 2) + { + solutionSet->get(0)->setCrowdingDistance(std::numeric_limits::max()); + solutionSet->get(1)->setCrowdingDistance(std::numeric_limits::max()); + return; + } // if + + //Use a new SolutionSet to evite alter original solutionSet + SolutionSet * front = snew SolutionSet(size); + for (int i = 0; i < size; i++) + { + front->add(solutionSet->get(i)); + } + + for (int i = 0; i < size; i++) + front->get(i)->setCrowdingDistance(0.0); + + double objetiveMaxn; + double objetiveMinn; + double distance; + + for (int i = 0; isort(c); + delete c; + objetiveMinn = front->get(0)->getObjective(i); + objetiveMaxn = front->get(front->size()-1)->getObjective(i); + + //Set de crowding distance + front->get(0)->setCrowdingDistance(std::numeric_limits::max()); + front->get(size-1)->setCrowdingDistance(std::numeric_limits::max()); + + for (int j = 1; j < size-1; j++) + { + distance = front->get(j+1)->getObjective(i) - front->get(j-1)->getObjective(i); + distance = distance / (objetiveMaxn - objetiveMinn); + distance += front->get(j)->getCrowdingDistance(); + front->get(j)->setCrowdingDistance(distance); + } // for } // for - } // for - front->clear(); - delete front; + front->clear(); + delete front; } // crowdingDistanceAssignment diff --git a/src/util/Distance.h b/src/util/Distance.h index 2ed6d3a..ea0e470 100644 --- a/src/util/Distance.h +++ b/src/util/Distance.h @@ -29,24 +29,25 @@ #include #include -using namespace std; + /** * This class implements some utilities for calculating distances */ -class Distance { +class Distance +{ public: - Distance(); - double ** distanceMatrix(SolutionSet * solutionSet); - double distanceToSolutionSetInObjectiveSpace(Solution * solution, - SolutionSet * solutionSet); - double distanceToSolutionSetInSolutionSpace(Solution * solution, - SolutionSet * solutionSet); - double distanceBetweenSolutions(Solution * solutionI, Solution * solutionJ); - double distanceBetweenObjectives(Solution * solutionI, Solution * solutionJ); - void crowdingDistanceAssignment(SolutionSet * solutionSet, int nObjs); + Distance(); + double ** distanceMatrix(SolutionSet * solutionSet); + double distanceToSolutionSetInObjectiveSpace(Solution * solution, + SolutionSet * solutionSet); + double distanceToSolutionSetInSolutionSpace(Solution * solution, + SolutionSet * solutionSet); + double distanceBetweenSolutions(Solution * solutionI, Solution * solutionJ); + double distanceBetweenObjectives(Solution * solutionI, Solution * solutionJ); + void crowdingDistanceAssignment(SolutionSet * solutionSet, int nObjs); }; diff --git a/src/util/NonDominatedSolutionList.cpp b/src/util/NonDominatedSolutionList.cpp index ec9fe4d..eab00ad 100644 --- a/src/util/NonDominatedSolutionList.cpp +++ b/src/util/NonDominatedSolutionList.cpp @@ -28,10 +28,11 @@ * a Pareto dominance comparator. */ NonDominatedSolutionList::NonDominatedSolutionList() -: SolutionSet() { + : SolutionSet() +{ - dominance = new DominanceComparator(); - equal = new SolutionComparator(); + dominance = snew DominanceComparator(); + equal = snew SolutionComparator(); } // NonDominatedList @@ -43,10 +44,11 @@ NonDominatedSolutionList::NonDominatedSolutionList() * @param dominance The comparator for dominance checking. */ NonDominatedSolutionList::NonDominatedSolutionList(Comparator *dominance) -: SolutionSet() { + : SolutionSet() +{ - this->dominance = dominance; - this->equal = new SolutionComparator(); + this->dominance = dominance; + this->equal = new SolutionComparator(); } // NonDominatedList @@ -54,10 +56,11 @@ NonDominatedSolutionList::NonDominatedSolutionList(Comparator *dominance) /** * Destructor. */ -NonDominatedSolutionList::~NonDominatedSolutionList() { +NonDominatedSolutionList::~NonDominatedSolutionList() +{ - delete dominance; - delete equal; + delete dominance; + delete equal; } // ~NonDominatedSolutionList @@ -69,33 +72,40 @@ NonDominatedSolutionList::~NonDominatedSolutionList() { * The decision variables can be null if the solution is read from a file; in * that case, the domination tests are omitted */ -bool NonDominatedSolutionList::add(Solution *solution) { - - int i = 0; - Solution * aux; //Store an solution temporally - - while (i < solutionsList_.size()) { - aux = solutionsList_[i]; - int flag = dominance->compare(solution,aux); - - if (flag == -1) { // A solution in the list is dominated by the new one - delete aux; - solutionsList_.erase(solutionsList_.begin()+i); - } else if (flag == 0) { // Non-dominated solutions - /* - flag = equal_->compare(solution,aux); - if (flag == 0) { - return false; // The new solution is in the list - } - */ - i++; - } else if (flag == 1) { // The new solution is dominated - return false; - } - } // while - - //At this point, the solution is inserted into the list - solutionsList_.push_back(solution); - - return true; +bool NonDominatedSolutionList::add(Solution *solution) +{ + + int i = 0; + Solution * aux; //Store an solution temporally + + while (i < solutionsList_.size()) + { + aux = solutionsList_[i]; + int flag = dominance->compare(solution,aux); + + if (flag == -1) // A solution in the list is dominated by the new one + { + delete aux; + solutionsList_.erase(solutionsList_.begin()+i); + } + else if (flag == 0) // Non-dominated solutions + { + /* + flag = equal_->compare(solution,aux); + if (flag == 0) { + return false; // The new solution is in the list + } + */ + i++; + } + else if (flag == 1) // The new solution is dominated + { + return false; + } + } // while + + //At this point, the solution is inserted into the list + solutionsList_.push_back(solution); + + return true; } // add diff --git a/src/util/NonDominatedSolutionList.h b/src/util/NonDominatedSolutionList.h index 4d48694..f55ac06 100644 --- a/src/util/NonDominatedSolutionList.h +++ b/src/util/NonDominatedSolutionList.h @@ -30,18 +30,19 @@ * This class implements an unbound list of non-dominated solutions */ -class NonDominatedSolutionList : public SolutionSet { +class NonDominatedSolutionList : public SolutionSet +{ private: - Comparator * dominance; - Comparator * equal; + Comparator * dominance; + Comparator * equal; public: - NonDominatedSolutionList(); - NonDominatedSolutionList(Comparator *dominance); - ~NonDominatedSolutionList(); + NonDominatedSolutionList(); + NonDominatedSolutionList(Comparator *dominance); + ~NonDominatedSolutionList(); - bool add(Solution *solution); + bool add(Solution *solution); }; // NonDominatedSolutionList diff --git a/src/util/PermutationUtility.cpp b/src/util/PermutationUtility.cpp index 5f67280..5ccdb6b 100644 --- a/src/util/PermutationUtility.cpp +++ b/src/util/PermutationUtility.cpp @@ -19,36 +19,42 @@ // along with this program. If not, see . #include +#include "JMetalHeader.h" -int * PermutationUtility::intPermutation(int length) { +int * PermutationUtility::intPermutation(int length) +{ - int * aux = new int[length]; - int * result = new int[length]; + int * aux = snew int[length]; + int * result = snew int[length]; - // First, create an array from 0 to length - 1. - // Also is needed to create an random array of size length - for (int i = 0; i < length; i++) { - result[i] = i; - aux[i] = PseudoRandom::randInt(0,length-1); - } // for + // First, create an array from 0 to length - 1. + // Also is needed to create an random array of size length + for (int i = 0; i < length; i++) + { + result[i] = i; + aux[i] = PseudoRandom::randInt(0,length-1); + } // for - // Sort the random array with effect in result, and then we obtain a - // permutation array between 0 and length - 1 - for (int i = 0; i < length; i++) { - for (int j = i + 1; j < length; j++) { - if (aux[i] > aux[j]) { - int tmp; - tmp = aux[i]; - aux[i] = aux[j]; - aux[j] = tmp; - tmp = result[i]; - result[i] = result[j]; - result[j] = tmp; - } // if + // Sort the random array with effect in result, and then we obtain a + // permutation array between 0 and length - 1 + for (int i = 0; i < length; i++) + { + for (int j = i + 1; j < length; j++) + { + if (aux[i] > aux[j]) + { + int tmp; + tmp = aux[i]; + aux[i] = aux[j]; + aux[j] = tmp; + tmp = result[i]; + result[i] = result[j]; + result[j] = tmp; + } // if + } // for } // for - } // for - delete[] aux; + delete[] aux; - return result; + return result; } diff --git a/src/util/PermutationUtility.h b/src/util/PermutationUtility.h index 94bf4ea..2128222 100644 --- a/src/util/PermutationUtility.h +++ b/src/util/PermutationUtility.h @@ -23,10 +23,11 @@ #include -class PermutationUtility { +class PermutationUtility +{ public: - int * intPermutation(int length); + int * intPermutation(int length); }; diff --git a/src/util/PseudoRandom.cpp b/src/util/PseudoRandom.cpp index 488136b..e506966 100644 --- a/src/util/PseudoRandom.cpp +++ b/src/util/PseudoRandom.cpp @@ -22,49 +22,57 @@ #include -using namespace std; + /** - * This file is aimed at defining the interface for the random generator. + * This file is aimed at defining the interface for the random generator. * The idea is that all the random numbers will be generated using a single * random generator which will be accesible throug this interface. **/ -RandomGenerator * PseudoRandom::randomGenerator_ = NULL ; +RandomGenerator * PseudoRandom::randomGenerator_ = nullptr ; -PseudoRandom::PseudoRandom() { - //randomGenerator_ = NULL ; - if (PseudoRandom::randomGenerator_ == NULL) { - PseudoRandom::randomGenerator_ = new RandomGenerator(); - } +PseudoRandom::PseudoRandom() +{ + //randomGenerator_ = nullptr ; + if (PseudoRandom::randomGenerator_ == nullptr) + { + PseudoRandom::randomGenerator_ = new RandomGenerator(); + } } //static int PseudoRandom::randInt() { -// if (randomGenerator_ == NULL) { +// if (randomGenerator_ == nullptr) { // new PseudoRandom(); // } // return randomGenerator_->rando //} -double PseudoRandom::randDouble() { - if (PseudoRandom::randomGenerator_ == NULL) { - PseudoRandom::randomGenerator_ = new RandomGenerator(); - } - return PseudoRandom::randomGenerator_->rndreal(0.0,1.0); +double PseudoRandom::randDouble() +{ + if (PseudoRandom::randomGenerator_ == nullptr) + { + PseudoRandom::randomGenerator_ = new RandomGenerator(); + } + return PseudoRandom::randomGenerator_->rndreal(0.0,1.0); } -int PseudoRandom::randInt(int minBound, int maxBound) { - if (PseudoRandom::randomGenerator_ == NULL) { - PseudoRandom::randomGenerator_ = new RandomGenerator(); - } - return PseudoRandom::randomGenerator_->rnd(minBound,maxBound); +int PseudoRandom::randInt(int minBound, int maxBound) +{ + if (PseudoRandom::randomGenerator_ == nullptr) + { + PseudoRandom::randomGenerator_ = new RandomGenerator(); + } + return PseudoRandom::randomGenerator_->rnd(minBound,maxBound); } -double PseudoRandom::randDouble(double minBound, double maxBound) { - if (PseudoRandom::randomGenerator_ == NULL) { - PseudoRandom::randomGenerator_ = new RandomGenerator(); - } - return PseudoRandom::randomGenerator_->rndreal(minBound,maxBound); +double PseudoRandom::randDouble(double minBound, double maxBound) +{ + if (PseudoRandom::randomGenerator_ == nullptr) + { + PseudoRandom::randomGenerator_ = new RandomGenerator(); + } + return PseudoRandom::randomGenerator_->rndreal(minBound,maxBound); } @@ -76,19 +84,22 @@ double PseudoRandom::randDouble(double minBound, double maxBound) { * @param standardDeviation * @return A pseudo random number */ -double PseudoRandom::randNormal(double mean, double standardDeviation) { - double x1, x2, w, y1; - - do { - x1 = 2.0 * randDouble() - 1.0; - x2 = 2.0 * randDouble() - 1.0; - w = x1 * x1 + x2 * x2; - } while ( w >= 1.0); - - w = sqrt( (-2.0 * log(w)) / w ); - y1 = x1 * w; - y1 = y1 * standardDeviation + mean; - return y1; +double PseudoRandom::randNormal(double mean, double standardDeviation) +{ + double x1, x2, w, y1; + + do + { + x1 = 2.0 * randDouble() - 1.0; + x2 = 2.0 * randDouble() - 1.0; + w = x1 * x1 + x2 * x2; + } + while ( w >= 1.0); + + w = sqrt( (-2.0 * log(w)) / w ); + y1 = x1 * w; + y1 = y1 * standardDeviation + mean; + return y1; } @@ -98,31 +109,34 @@ double PseudoRandom::randNormal(double mean, double standardDeviation) { * @param dimension * @return A pseudo random point */ -double * PseudoRandom::randSphere(int dimension) { - int D = dimension ; - double * x = new double[dimension] ; +double * PseudoRandom::randSphere(int dimension) +{ + int D = dimension ; + double * x = snew double[dimension] ; - double length = 0 ; - for (int i = 0; i < dimension; i++) - x[i] = 0.0 ; + double length = 0 ; + for (int i = 0; i < dimension; i++) + x[i] = 0.0 ; - // --------- Step 1. Direction + // --------- Step 1. Direction - for (int i = 0; i < D; i++) { - x[i] = randNormal(0, 1) ; - length += length + x[i]*x[i] ; - } + for (int i = 0; i < D; i++) + { + x[i] = randNormal(0, 1) ; + length += length + x[i]*x[i] ; + } - length = sqrt(length) ; + length = sqrt(length) ; - // --------- Step 2. Random radius + // --------- Step 2. Random radius - double r = randDouble(0, 1) ; + double r = randDouble(0, 1) ; - for (int i = 0; i < D; i++) { - x[i]=r*x[i]/length; - } + for (int i = 0; i < D; i++) + { + x[i]=r*x[i]/length; + } - return x ; + return x ; } - + diff --git a/src/util/PseudoRandom.h b/src/util/PseudoRandom.h index 9099bc0..6cc4e2c 100644 --- a/src/util/PseudoRandom.h +++ b/src/util/PseudoRandom.h @@ -2,6 +2,7 @@ // // Author: // Esteban López-Camacho +// Sérgio Vieira // Antonio J. Nebro // Juan J. Durillo // @@ -23,28 +24,30 @@ #ifndef _PseudoRandom_h #define _PseudoRandom_h +#include "JMetalHeader.h" #include #include #include /** - * This file is aimed at defining the interface for the random generator. + * This file is aimed at defining the interface for the random generator. * The idea is that all the random numbers will be generated using a single * random generator which will be accesible throug this interface. **/ -class PseudoRandom { +class PseudoRandom +{ //private: public: - static RandomGenerator * randomGenerator_; - PseudoRandom(); + static RandomGenerator * randomGenerator_; + PseudoRandom(); public: - static double randDouble();// static int randInt(); - static int randInt(int minBound, int maxBound); - static double randDouble(double minBound, double maxBound); - static double randNormal(double mean, double standardDeviation); - static double * randSphere(int dimension); + static double randDouble();// static int randInt(); + static int randInt(int minBound, int maxBound); + static double randDouble(double minBound, double maxBound); + static double randNormal(double mean, double standardDeviation); + static double * randSphere(int dimension); }; diff --git a/src/util/RandomGenerator.cpp b/src/util/RandomGenerator.cpp index f217d84..318bcd5 100644 --- a/src/util/RandomGenerator.cpp +++ b/src/util/RandomGenerator.cpp @@ -31,106 +31,125 @@ using namespace std; * http://www.iitk.ac.in/kangal/codes/nsga2/nsga2-v1.1.tar **/ -RandomGenerator::RandomGenerator() { - srand(time(NULL)); - //srand(0); - //cout << (unsigned)time(0) << endl; - seed_ = ((double) rand() / (double) (RAND_MAX )); - //cout << "Seed value is: " << seed_ << endl; - - // seed_ = RAND_MAX; - // cout << "Seed value is: " << seed_ << endl; - - // seed_ = (double) ((float) (float) seed_ / (float) RAND_MAX); - // cout << "Seed value is: " << seed_ << endl; - - randomize(); +RandomGenerator::RandomGenerator() +{ + srand(time(nullptr)); + //srand(0); + //std::cout << (unsigned)time(0) << std::endl; + seed_ = ((double) rand() / (double) (RAND_MAX )); + //std::cout << "Seed value is: " << seed_ << std::endl; + + // seed_ = RAND_MAX; + // std::cout << "Seed value is: " << seed_ << std::endl; + + // seed_ = (double) ((float) (float) seed_ / (float) RAND_MAX); + // std::cout << "Seed value is: " << seed_ << std::endl; + + randomize(); } // RandomGenerator -int RandomGenerator::rnd (int low, int high) { - int res; - if (low >= high){ - res = low; - } else { - res = low + (int)(randomperc()*(high-low+1)); - if (res > high){ - res = high; +int RandomGenerator::rnd (int low, int high) +{ + int res; + if (low >= high) + { + res = low; + } + else + { + res = low + (int)(randomperc()*(high-low+1)); + if (res > high) + { + res = high; + } } - } - return (res); + return (res); } -double RandomGenerator::rndreal(double low, double high) { - return (low + (high - low) * randomperc()); +double RandomGenerator::rndreal(double low, double high) +{ + return (low + (high - low) * randomperc()); } -void RandomGenerator::randomize() { - int j1; +void RandomGenerator::randomize() +{ + int j1; - for (j1=0; j1<=54;j1++) { - oldrand_[j1] = .0; - } // for + for (j1=0; j1<=54; j1++) + { + oldrand_[j1] = .0; + } // for + + jrand_ = 0; + warmup_random(seed_); - jrand_ = 0; - warmup_random(seed_); - } // randomize -void RandomGenerator::warmup_random(double seed) { - int j1, i1; - double new_random, prev_random; - oldrand_[54] = seed; - new_random = 0.000000001; - prev_random = seed; - - for (j1=1; j1 <= 54; j1++) { - i1 = (21*j1)%54; - oldrand_[i1] = new_random; - new_random = prev_random - new_random; - - if (new_random < 0.0) { - new_random += 1.0; +void RandomGenerator::warmup_random(double seed) +{ + int j1, i1; + double new_random, prev_random; + oldrand_[54] = seed; + new_random = 0.000000001; + prev_random = seed; + + for (j1=1; j1 <= 54; j1++) + { + i1 = (21*j1)%54; + oldrand_[i1] = new_random; + new_random = prev_random - new_random; + + if (new_random < 0.0) + { + new_random += 1.0; + } + + prev_random = oldrand_[i1]; } - - prev_random = oldrand_[i1]; - } - advance_random(); - advance_random(); - advance_random(); - jrand_ = 0; + advance_random(); + advance_random(); + advance_random(); + jrand_ = 0; - return; + return; } -void RandomGenerator::advance_random() { - int j1; - double new_random; - for(j1=0; j1<24; j1++){ - new_random = oldrand_[j1]-oldrand_[j1+31]; - if(new_random<0.0){ - new_random = new_random+1.0; +void RandomGenerator::advance_random() +{ + int j1; + double new_random; + for(j1=0; j1<24; j1++) + { + new_random = oldrand_[j1]-oldrand_[j1+31]; + if(new_random<0.0) + { + new_random = new_random+1.0; + } + oldrand_[j1] = new_random; } - oldrand_[j1] = new_random; - } - for(j1=24; j1<55; j1++){ - new_random = oldrand_[j1]-oldrand_[j1-24]; - if(new_random<0.0){ - new_random = new_random+1.0; + for(j1=24; j1<55; j1++) + { + new_random = oldrand_[j1]-oldrand_[j1-24]; + if(new_random<0.0) + { + new_random = new_random+1.0; + } + oldrand_[j1] = new_random; } - oldrand_[j1] = new_random; - } } -double RandomGenerator::randomperc() { - jrand_++; - if(jrand_>=55){ - jrand_ = 1; - advance_random(); - } - return oldrand_[jrand_]; +double RandomGenerator::randomperc() +{ + jrand_++; + if(jrand_>=55) + { + jrand_ = 1; + advance_random(); + } + return oldrand_[jrand_]; } diff --git a/src/util/RandomGenerator.h b/src/util/RandomGenerator.h index 0306e28..abd29c8 100644 --- a/src/util/RandomGenerator.h +++ b/src/util/RandomGenerator.h @@ -33,23 +33,24 @@ * http://www.iitk.ac.in/kangal/codes/nsga2/nsga2-v1.1.tar **/ -class RandomGenerator { +class RandomGenerator +{ private: - double seed_; - double oldrand_[55]; - int jrand_; - void randomize(); - void warmup_random(double seed); - void advance_random(); - double randomperc(); - + double seed_; + double oldrand_[55]; + int jrand_; + void randomize(); + void warmup_random(double seed); + void advance_random(); + double randomperc(); + public: - RandomGenerator(void); - ~RandomGenerator(void); - int rnd (int low, int high); - double rndreal(double low, double high); - + RandomGenerator(void); + ~RandomGenerator(void); + int rnd (int low, int high); + double rndreal(double low, double high); + }; // RandomGenerator #endif diff --git a/src/util/Ranking.cpp b/src/util/Ranking.cpp index 32971e8..c0b245c 100644 --- a/src/util/Ranking.cpp +++ b/src/util/Ranking.cpp @@ -39,99 +39,117 @@ * Constructor. * @param solutionSet The SolutionSet to be ranked. */ -Ranking::Ranking (SolutionSet * solutionSet) { - - solutionSet_ = solutionSet; - dominance_ = new DominanceComparator(); - constraint_ = new OverallConstraintViolationComparator(); - - // dominateMe[i] contains the number of solutions dominating i - int * dominateMe = new int[solutionSet_->size()]; - - if (dominateMe == NULL) { - cout << "Fatal Problem: Cannot reserve memory in class Ranking" << endl; - exit(-1); - } - - // iDominate[k] contains the list of solutions dominated by k - vector * iDominate = new vector[solutionSet_->size()]; - - // front[i] contains the list of individuals belonging to the front i - vector * front = new vector[solutionSet_->size()+1]; - - // flagDominate is an auxiliar variable - int flagDominate; - - //-> Fast non dominated sorting algorithm - for (int p = 0; p < solutionSet_->size(); p++) { - dominateMe[p] = 0; - } - - // For all q individuals , calculate if p dominates q or vice versa - for (int p = 0; p < (solutionSet_->size() - 1); p++) { - for (int q = p + 1; q < solutionSet_->size(); q++) { - - flagDominate =constraint_->compare(solutionSet->get(p),solutionSet->get(q)); - if (flagDominate == 0) { - flagDominate =dominance_->compare(solutionSet->get(p),solutionSet->get(q)); - } // if - - if (flagDominate == -1) { - iDominate[p].push_back(q); - dominateMe[q]++; - } else if (flagDominate == 1) { - iDominate[q].push_back(p); - dominateMe[p]++; - } // if - +Ranking::Ranking (SolutionSet * solutionSet) +{ + + solutionSet_ = solutionSet; + dominance_ = new DominanceComparator(); + constraint_ = new OverallConstraintViolationComparator(); + + // dominateMe[i] contains the number of solutions dominating i + int * dominateMe = snew int[solutionSet_->size()]; + + if (dominateMe == nullptr) + { + std::cout << "Fatal Problem: Cannot reserve memory in class Ranking" << std::endl; + exit(-1); + } + + // iDominate[k] contains the list of solutions dominated by k + VectorOfInteger * iDominate = new VectorOfInteger[solutionSet_->size()]; + + // front[i] contains the list of individuals belonging to the front i + VectorOfInteger * front = new VectorOfInteger[solutionSet_->size()+1]; + + // flagDominate is an auxiliar variable + int flagDominate; + + //-> Fast non dominated sorting algorithm + for (int p = 0; p < solutionSet_->size(); p++) + { + dominateMe[p] = 0; + } + + // For all q individuals , calculate if p dominates q or vice versa + for (int p = 0; p < (solutionSet_->size() - 1); p++) + { + for (int q = p + 1; q < solutionSet_->size(); q++) + { + + flagDominate =constraint_->compare(solutionSet->get(p),solutionSet->get(q)); + if (flagDominate == 0) + { + flagDominate =dominance_->compare(solutionSet->get(p),solutionSet->get(q)); + } // if + + if (flagDominate == -1) + { + iDominate[p].push_back(q); + dominateMe[q]++; + } + else if (flagDominate == 1) + { + iDominate[q].push_back(p); + dominateMe[p]++; + } // if + + } // for } // for - } // for - - for (int p = 0; p < solutionSet_->size(); p++) { - // If nobody dominates p, p belongs to the first front - if (dominateMe[p] == 0) { - front[0].push_back(p); - solutionSet_->get(p)->setRank(0); - } // if - - } // for - - // Obtain the rest of fronts - int i = 0; - vector::iterator it1, it2; - while (front[i].size()!=0) { - i++; - for (it1=front[i-1].begin(); it1get(*it2)->setRank(i); + + for (int p = 0; p < solutionSet_->size(); p++) + { + // If nobody dominates p, p belongs to the first front + if (dominateMe[p] == 0) + { + front[0].push_back(p); + solutionSet_->get(p)->setRank(0); } // if - } // for + } // for - } // while - - ranking_ = new SolutionSet*[i]; - if (ranking_ == NULL) { - cout << "Fatal Error: Impossible to reserve memory in Ranking" << endl; - exit(-1); - } - - //0,1,2,....,i-1 are front, then i fronts - - numberOfSubfronts_ = i; - - for (int j = 0; j < i; j++) { - ranking_[j] = new SolutionSet(front[j].size()); - for (it1=front[j].begin(); it1add(new Solution(solutionSet_->get(*it1))); + + // Obtain the rest of fronts + int i = 0; + VectorOfInteger::iterator it1, it2; + while (front[i].size()!=0) + { + i++; + for (it1=front[i-1].begin(); it1get(*it2)->setRank(i); + } // if + } // for + } // for + } // while + + ranking_ = new SolutionSet*[i]; + if (ranking_ == nullptr) + { + std::cout << "Fatal Error: Impossible to reserve memory in Ranking" << std::endl; + exit(-1); + } + + //0,1,2,....,i-1 are front, then i fronts + + numberOfSubfronts_ = i; + + for (int j = 0; j < i; j++) + { + ranking_[j] = new SolutionSet(front[j].size()); + for (it1=front[j].begin(); it1add(new Solution(solutionSet_->get(*it1))); + } // for } // for - } // for - delete [] dominateMe; - delete [] iDominate; - delete [] front; + delete [] dominateMe; + delete [] iDominate; + delete [] front; } // Ranking @@ -139,13 +157,15 @@ Ranking::Ranking (SolutionSet * solutionSet) { /** * Destructor */ -Ranking::~Ranking() { - for (int i = 0; i < numberOfSubfronts_; i++) { - delete ranking_[i]; - } - delete [] ranking_; - delete dominance_; - delete constraint_; +Ranking::~Ranking() +{ + for (int i = 0; i < numberOfSubfronts_; i++) + { + delete ranking_[i]; + } + delete [] ranking_; + delete dominance_; + delete constraint_; } // ~Ranking @@ -154,14 +174,16 @@ Ranking::~Ranking() { * @param rank The rank * @return Object representing the SolutionSet. */ -SolutionSet * Ranking::getSubfront(int rank) { - return ranking_[rank]; +SolutionSet * Ranking::getSubfront(int rank) +{ + return ranking_[rank]; } // getSubFront /** * Returns the total number of subFronts founds. */ -int Ranking::getNumberOfSubfronts() { - return numberOfSubfronts_; +int Ranking::getNumberOfSubfronts() +{ + return numberOfSubfronts_; } // getNumberOfSubfronts diff --git a/src/util/Ranking.h b/src/util/Ranking.h index a2c33c0..8891f8f 100644 --- a/src/util/Ranking.h +++ b/src/util/Ranking.h @@ -38,20 +38,21 @@ * solutions, subset 1 contains the non-dominated solutions after removing those * belonging to subset 0, and so on. */ -class Ranking { +class Ranking +{ private: - SolutionSet * solutionSet_; - SolutionSet ** ranking_; - int numberOfSubfronts_; - DominanceComparator * dominance_; - OverallConstraintViolationComparator * constraint_; + SolutionSet * solutionSet_; + SolutionSet ** ranking_; + int numberOfSubfronts_; + DominanceComparator * dominance_; + OverallConstraintViolationComparator * constraint_; public: - Ranking (SolutionSet * solutionSet); - ~Ranking(); - SolutionSet * getSubfront(int rank); - int getNumberOfSubfronts(); + Ranking (SolutionSet * solutionSet); + ~Ranking(); + SolutionSet * getSubfront(int rank); + int getNumberOfSubfronts(); }; diff --git a/src/util/archive/AdaptiveGridArchive.cpp b/src/util/archive/AdaptiveGridArchive.cpp index cd0c3cc..83d5eed 100644 --- a/src/util/archive/AdaptiveGridArchive.cpp +++ b/src/util/archive/AdaptiveGridArchive.cpp @@ -20,20 +20,21 @@ #include - /** - * Constructor. - * - * @param maxSize The maximum size of the archive - * @param bisections The maximum number of bi-divisions for the adaptive - * grid. - * @param objectives The number of objectives. - */ +/** + * Constructor. + * + * @param maxSize The maximum size of the archive + * @param bisections The maximum number of bi-divisions for the adaptive + * grid. + * @param objectives The number of objectives. + */ AdaptiveGridArchive::AdaptiveGridArchive (int maxSize,int bisections, - int objectives) : Archive(maxSize) { + int objectives) : Archive(maxSize) +{ - maxSize_ = maxSize; - dominance_ = new DominanceComparator(); - grid_ = new AdaptiveGrid(bisections,objectives); + maxSize_ = maxSize; + dominance_ = snew DominanceComparator(); + grid_ = snew AdaptiveGrid(bisections,objectives); } /** @@ -48,74 +49,88 @@ AdaptiveGridArchive::AdaptiveGridArchive (int maxSize,int bisections, * otherwise. */ -bool AdaptiveGridArchive::add(Solution * solution, int eval) { - int i=0; - Solution * aux; //Store an solution temporally - - while (i < solutionsList_.size()){ - aux = solutionsList_[i]; - int flag = dominance_->compare(solution,aux); - if (flag == -1) { // The Individual to insert dominates other - solutionsList_.erase (solutionsList_.begin()+i); //Delete it from the archive - int location = grid_->location(aux); - if (grid_->getLocationDensity(location) > 1) {//The hypercube contains - grid_->removeSolution(location); //more than one individual - } else { - grid_->updateGrid(this); - } // else - } // if - else if (flag == 1) { // An Individual into the file dominates the - // solution to insert - return false; // The solution will not be inserted - } // else if - i++; - } // while - - // At this point, the solution may be inserted - if (size() == 0){ //The archive is empty - solutionsList_.push_back(solution); - grid_->updateGrid(this); - return true; - } // - - if (size() < maxSize_){ //The archive is not full - grid_->updateGrid(solution,this,eval); // Update the grid if applicable - int location ; - location= grid_->location(solution); // Get the location of the solution - grid_->addSolution(location); // Increment the density of the hypercube - solutionsList_.push_back(solution);// Add the solution to the list - return true; - } // if - - // At this point, the solution has to be inserted and the archive is full - grid_->updateGrid(solution,this,eval); - int location = grid_->location(solution); - if (location == grid_->getMostPopulated()) { // The solution is in the - // most populated hypercube - return false; // Not inserted - } - else { - // Remove an solution from most populated area - i=0; - bool removed = false; - - while (i < solutionsList_.size()){ - if (!removed) { - aux = solutionsList_[i]; - int location2 = grid_->location(aux); - if (location2 == grid_->getMostPopulated()) { - solutionsList_.erase (solutionsList_.begin()+i); - grid_->removeSolution(location2); - } // if - } // if - i++; - } // while - // A solution from most populated hypercube has been removed, - // insert now the solution - grid_->addSolution(location); - solutionsList_.push_back(solution); - } // else - return true; +bool AdaptiveGridArchive::add(Solution * solution, int eval) +{ + int i=0; + Solution * aux; //Store an solution temporally + + while (i < solutionsList_.size()) + { + aux = solutionsList_[i]; + int flag = dominance_->compare(solution,aux); + if (flag == -1) // The Individual to insert dominates other + { + solutionsList_.erase (solutionsList_.begin()+i); //Delete it from the archive + int location = grid_->location(aux); + if (grid_->getLocationDensity(location) > 1) //The hypercube contains + { + grid_->removeSolution(location); //more than one individual + } + else + { + grid_->updateGrid(this); + } // else + } // if + else if (flag == 1) // An Individual into the file dominates the + { + // solution to insert + return false; // The solution will not be inserted + } // else if + i++; + } // while + + // At this point, the solution may be inserted + if (size() == 0) //The archive is empty + { + solutionsList_.push_back(solution); + grid_->updateGrid(this); + return true; + } // + + if (size() < maxSize_) //The archive is not full + { + grid_->updateGrid(solution,this,eval); // Update the grid if applicable + int location ; + location= grid_->location(solution); // Get the location of the solution + grid_->addSolution(location); // Increment the density of the hypercube + solutionsList_.push_back(solution);// Add the solution to the list + return true; + } // if + + // At this point, the solution has to be inserted and the archive is full + grid_->updateGrid(solution,this,eval); + int location = grid_->location(solution); + if (location == grid_->getMostPopulated()) // The solution is in the + { + // most populated hypercube + return false; // Not inserted + } + else + { + // Remove an solution from most populated area + i=0; + bool removed = false; + + while (i < solutionsList_.size()) + { + if (!removed) + { + aux = solutionsList_[i]; + int location2 = grid_->location(aux); + if (location2 == grid_->getMostPopulated()) + { + solutionsList_.erase (solutionsList_.begin()+i); + grid_->removeSolution(location2); + } // if + } // if + i++; + } // while + // A solution from most populated hypercube has been removed, + // insert now the solution + grid_->addSolution(location); + solutionsList_.push_back(solution); + } // else + return true; } // add /** @@ -123,8 +138,9 @@ bool AdaptiveGridArchive::add(Solution * solution, int eval) { * @return the AdaptativeGrid */ -AdaptiveGrid * AdaptiveGridArchive::getGrid() { - return grid_; +AdaptiveGrid * AdaptiveGridArchive::getGrid() +{ + return grid_; } // AdaptativeGrid diff --git a/src/util/archive/AdaptiveGridArchive.h b/src/util/archive/AdaptiveGridArchive.h index d282a7d..33f1998 100644 --- a/src/util/archive/AdaptiveGridArchive.h +++ b/src/util/archive/AdaptiveGridArchive.h @@ -31,28 +31,29 @@ * This class implements an archive based on an adaptive grid used in PAES */ -class AdaptiveGridArchive : public Archive { +class AdaptiveGridArchive : public Archive +{ private: - /** - * Stores the adaptive grid - */ - AdaptiveGrid * grid_; + /** + * Stores the adaptive grid + */ + AdaptiveGrid * grid_; - /** - * Stores the maximum size of the archive - */ - int maxSize_; + /** + * Stores the maximum size of the archive + */ + int maxSize_; - /** - * Stores a Comparator for dominance checking - */ - Comparator * dominance_; + /** + * Stores a Comparator for dominance checking + */ + Comparator * dominance_; public: - AdaptiveGridArchive(int maxSize,int bisections, int objectives); - bool add(Solution * solution, int eval); - AdaptiveGrid * getGrid(); + AdaptiveGridArchive(int maxSize,int bisections, int objectives); + bool add(Solution * solution, int eval); + AdaptiveGrid * getGrid(); }; #endif /* ADAPTIVEGRIDARCHIVE_H_ */ diff --git a/src/util/archive/Archive.cpp b/src/util/archive/Archive.cpp index 6083de5..6b8b1a1 100644 --- a/src/util/archive/Archive.cpp +++ b/src/util/archive/Archive.cpp @@ -30,7 +30,8 @@ /** * Constructor. */ -Archive::Archive(int size) : SolutionSet(size) { - //do nothing. +Archive::Archive(int size) : SolutionSet(size) +{ + //do nothing. } // Archive diff --git a/src/util/archive/Archive.h b/src/util/archive/Archive.h index b10318e..ccdca42 100644 --- a/src/util/archive/Archive.h +++ b/src/util/archive/Archive.h @@ -26,10 +26,11 @@ /** * This class represents the super class for archive objects. */ -class Archive : public SolutionSet { +class Archive : public SolutionSet +{ public: - Archive(int size); + Archive(int size); }; diff --git a/src/util/archive/CMakeLists.txt b/src/util/archive/CMakeLists.txt new file mode 100644 index 0000000..294ec59 --- /dev/null +++ b/src/util/archive/CMakeLists.txt @@ -0,0 +1,3 @@ +file(GLOB SOURCES "*.cpp" "*.h") +ListToString(SOURCES ";" ${SOURCES}) +LIST_APPEND("${SOURCES}") \ No newline at end of file diff --git a/src/util/archive/CrowdingArchive.cpp b/src/util/archive/CrowdingArchive.cpp index 397c328..2063194 100644 --- a/src/util/archive/CrowdingArchive.cpp +++ b/src/util/archive/CrowdingArchive.cpp @@ -31,26 +31,28 @@ * @param numberOfObjectives The number of objectives. */ CrowdingArchive::CrowdingArchive(int maxSize, int numberOfObjectives) -: Archive(maxSize) { + : Archive(maxSize) +{ - this->maxSize = maxSize; - this->objectives = numberOfObjectives; - this->dominance = new DominanceComparator(); - this->equals = new EqualSolutions(); - this->crowdingDistance = new CrowdingDistanceComparator(); - this->distance = new Distance(); + this->maxSize = maxSize; + this->objectives = numberOfObjectives; + this->dominance = snew DominanceComparator(); + this->equals = snew EqualSolutions(); + this->crowdingDistance = snew CrowdingDistanceComparator(); + this->distance = snew Distance(); } // CrowdingArchive /** * Destructor. */ -CrowdingArchive::~CrowdingArchive() { +CrowdingArchive::~CrowdingArchive() +{ - delete dominance; - delete equals; - delete crowdingDistance; - delete distance; + delete dominance; + delete equals; + delete crowdingDistance; + delete distance; } // ~CrowdingArchive @@ -65,40 +67,52 @@ CrowdingArchive::~CrowdingArchive() { * @return true if the Solution has been inserted, false * otherwise. */ -bool CrowdingArchive::add(Solution *solution){ - int flag = 0; - int i = 0; - Solution * aux; //Store an solution temporally - while (i < solutionsList_.size()){ - aux = solutionsList_[i]; +bool CrowdingArchive::add(Solution *solution) +{ + int flag = 0; + int i = 0; + Solution * aux; //Store an solution temporally + while (i < solutionsList_.size()) + { + aux = solutionsList_[i]; - flag = dominance->compare(solution,aux); - if (flag == 1) { // The solution to add is dominated - return false; // Discard the new solution - } else if (flag == -1) { // A solution in the archive is dominated - // Remove it from the population - delete aux; - solutionsList_.erase (solutionsList_.begin()+i); - } else { - if (equals->compare(aux,solution)==0) { - // There is an equal solution in the population - return false; // Discard the new solution - } // if - i++; + flag = dominance->compare(solution,aux); + if (flag == 1) // The solution to add is dominated + { + return false; // Discard the new solution + } + else if (flag == -1) // A solution in the archive is dominated + { + // Remove it from the population + delete aux; + solutionsList_.erase (solutionsList_.begin()+i); + } + else + { + if (equals->compare(aux,solution)==0) + { + // There is an equal solution in the population + return false; // Discard the new solution + } // if + i++; + } } - } - // Insert the solution into the archive - bool res = true; - solutionsList_.push_back(solution); - if (size() > maxSize) { // The archive is full - distance->crowdingDistanceAssignment(this,objectives); - int indexWorst_ = indexWorst(crowdingDistance); - if (solution == solutionsList_[indexWorst_]) { - res = false; - } else { - delete solutionsList_[indexWorst_]; + // Insert the solution into the archive + bool res = true; + solutionsList_.push_back(solution); + if (size() > maxSize) // The archive is full + { + distance->crowdingDistanceAssignment(this,objectives); + int indexWorst_ = indexWorst(crowdingDistance); + if (solution == solutionsList_[indexWorst_]) + { + res = false; + } + else + { + delete solutionsList_[indexWorst_]; + } + remove(indexWorst_); } - remove(indexWorst_); - } - return res; + return res; } // add diff --git a/src/util/archive/CrowdingArchive.h b/src/util/archive/CrowdingArchive.h index 8f9cde1..c0cc819 100644 --- a/src/util/archive/CrowdingArchive.h +++ b/src/util/archive/CrowdingArchive.h @@ -33,20 +33,21 @@ * This class implements a bounded archive based on crowding distances (as * defined in NSGA-II). */ -class CrowdingArchive : public Archive { +class CrowdingArchive : public Archive +{ private: - int maxSize; - int objectives; - Comparator *dominance; - Comparator *equals; - Comparator *crowdingDistance; - Distance *distance; + int maxSize; + int objectives; + Comparator *dominance; + Comparator *equals; + Comparator *crowdingDistance; + Distance *distance; public: - CrowdingArchive(int maxSize, int numberOfObjectives); - ~CrowdingArchive(); - bool add(Solution *solution); + CrowdingArchive(int maxSize, int numberOfObjectives); + ~CrowdingArchive(); + bool add(Solution *solution); }; diff --git a/src/util/comparators/CMakeLists.txt b/src/util/comparators/CMakeLists.txt new file mode 100644 index 0000000..294ec59 --- /dev/null +++ b/src/util/comparators/CMakeLists.txt @@ -0,0 +1,3 @@ +file(GLOB SOURCES "*.cpp" "*.h") +ListToString(SOURCES ";" ${SOURCES}) +LIST_APPEND("${SOURCES}") \ No newline at end of file diff --git a/src/util/comparators/Comparator.h b/src/util/comparators/Comparator.h index 304a75a..509a07c 100644 --- a/src/util/comparators/Comparator.h +++ b/src/util/comparators/Comparator.h @@ -29,11 +29,12 @@ * @class DominanceComparator * @brief This class is aimed at representing a Solution **/ -class Comparator { +class Comparator +{ public: - virtual ~Comparator(); - virtual int compare(void * one, void * two) = 0; + virtual ~Comparator(); + virtual int compare(void * one, void * two) = 0; }; diff --git a/src/util/comparators/CrowdingComparator.cpp b/src/util/comparators/CrowdingComparator.cpp index 6f7eea3..132f849 100644 --- a/src/util/comparators/CrowdingComparator.cpp +++ b/src/util/comparators/CrowdingComparator.cpp @@ -27,16 +27,18 @@ /** * Constructor */ -CrowdingComparator::CrowdingComparator() : Comparator() { - comparator = new RankComparator(); +CrowdingComparator::CrowdingComparator() : Comparator() +{ + comparator = snew RankComparator(); } // CrowdingComparator /** * Destructor */ -CrowdingComparator::~CrowdingComparator() { - delete comparator; +CrowdingComparator::~CrowdingComparator() +{ + delete comparator; } // ~CrowdingComparator @@ -47,26 +49,27 @@ CrowdingComparator::~CrowdingComparator() { * @return -1, or 0, or 1 if o1 is less than, equal, or greater than o2, * respectively. **/ -int CrowdingComparator::compare(void *o1, void *o2) { +int CrowdingComparator::compare(void *o1, void *o2) +{ - if (o1 == NULL) - return 1; - else if (o2 == NULL) - return -1; + if (o1 == nullptr) + return 1; + else if (o2 == nullptr) + return -1; - int flagComparatorRank = comparator->compare(o1,o2); + int flagComparatorRank = comparator->compare(o1,o2); - if (flagComparatorRank != 0) - return flagComparatorRank; + if (flagComparatorRank != 0) + return flagComparatorRank; - /* His rank is equal, then distance crowding comparator */ - double distance1 = ((Solution *) o1)->getCrowdingDistance(); - double distance2 = ((Solution *) o2)->getCrowdingDistance(); - if (distance1 > distance2) - return -1; + /* His rank is equal, then distance crowding comparator */ + double distance1 = ((Solution *) o1)->getCrowdingDistance(); + double distance2 = ((Solution *) o2)->getCrowdingDistance(); + if (distance1 > distance2) + return -1; - if (distance1 < distance2) - return 1; + if (distance1 < distance2) + return 1; - return 0; + return 0; } // compare diff --git a/src/util/comparators/CrowdingComparator.h b/src/util/comparators/CrowdingComparator.h index 3c54f71..1f5d446 100644 --- a/src/util/comparators/CrowdingComparator.h +++ b/src/util/comparators/CrowdingComparator.h @@ -30,15 +30,16 @@ * This class implements a Comparator (a method for comparing * Solution objects) based on the crowding distance, as in NSGA-II. */ -class CrowdingComparator : public Comparator { +class CrowdingComparator : public Comparator +{ private: - Comparator * comparator; + Comparator * comparator; public: - CrowdingComparator(); - ~CrowdingComparator(); - int compare(void * o1, void * o2); + CrowdingComparator(); + ~CrowdingComparator(); + int compare(void * o1, void * o2); }; diff --git a/src/util/comparators/CrowdingDistanceComparator.cpp b/src/util/comparators/CrowdingDistanceComparator.cpp index b969825..0df9daa 100644 --- a/src/util/comparators/CrowdingDistanceComparator.cpp +++ b/src/util/comparators/CrowdingDistanceComparator.cpp @@ -29,21 +29,22 @@ * @return -1, or 0, or 1 if o1 is less than, equal, or greater than o2, * respectively. **/ -int CrowdingDistanceComparator::compare(void *o1, void *o2) { +int CrowdingDistanceComparator::compare(void *o1, void *o2) +{ - if (o1 == NULL) - return 1; - else if (o2 == NULL) - return -1; + if (o1 == nullptr) + return 1; + else if (o2 == nullptr) + return -1; - double distance1 = ((Solution *) o1)->getCrowdingDistance(); - double distance2 = ((Solution *) o2)->getCrowdingDistance(); - if (distance1 > distance2) - return -1; + double distance1 = ((Solution *) o1)->getCrowdingDistance(); + double distance2 = ((Solution *) o2)->getCrowdingDistance(); + if (distance1 > distance2) + return -1; - if (distance1 < distance2) - return 1; + if (distance1 < distance2) + return 1; - return 0; + return 0; } // compare diff --git a/src/util/comparators/CrowdingDistanceComparator.h b/src/util/comparators/CrowdingDistanceComparator.h index fa9101a..aa8e2d7 100644 --- a/src/util/comparators/CrowdingDistanceComparator.h +++ b/src/util/comparators/CrowdingDistanceComparator.h @@ -28,12 +28,13 @@ * This class implements a Comparator (a method for comparing * Solution objects) based on the crowding distance, as in NSGA-II. */ -class CrowdingDistanceComparator : public Comparator { +class CrowdingDistanceComparator : public Comparator +{ private: public: - int compare(void * o1, void * o2); + int compare(void * o1, void * o2); }; diff --git a/src/util/comparators/DominanceComparator.cpp b/src/util/comparators/DominanceComparator.cpp index fd35ae9..34011cd 100644 --- a/src/util/comparators/DominanceComparator.cpp +++ b/src/util/comparators/DominanceComparator.cpp @@ -4,7 +4,7 @@ // Juan J. Durillo // Antonio J. Nebro // Esteban López-Camacho -// +// // Copyright (c) 2011 Antonio J. Nebro, Juan J. Durillo // // This program is free software: you can redistribute it and/or modify @@ -16,7 +16,7 @@ // but WITHOUT ANY WARRANTY; without even the implied warranty of // MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the // GNU Lesser General Public License for more details. -// +// // You should have received a copy of the GNU Lesser General Public License // along with this program. If not, see . @@ -26,7 +26,7 @@ * @class DominanceComparator * @brief This class is aimed at implementing a Dominance comparator. It returns true if solution one dominates to solution two. It returns - false in other case. Author must notice that two solutions are + false in other case. Author must notice that two solutions are non dominated only if: !compare(one,two) = false and !compare(two,one) **/ @@ -34,16 +34,18 @@ /** * Constructor */ -DominanceComparator::DominanceComparator() : Comparator() { - overallConstraintViolationComparator_ = new OverallConstraintViolationComparator(); +DominanceComparator::DominanceComparator() : Comparator() +{ + overallConstraintViolationComparator_ = snew OverallConstraintViolationComparator(); } // DominanceComparator /** * Destructor */ -DominanceComparator::~DominanceComparator() { - delete overallConstraintViolationComparator_; +DominanceComparator::~DominanceComparator() +{ + delete overallConstraintViolationComparator_; } // ~DominanceComparator @@ -54,61 +56,73 @@ DominanceComparator::~DominanceComparator() { * @return -1, or 0, or 1 if o1 is less than, equal, or greater than o2, * respectively. **/ -int DominanceComparator::compare(void * o1, void * o2) { - - if (o1==NULL) - return 1; - else if (o2 == NULL) - return -1; - - Solution * one = (Solution *) o1; - Solution * two = (Solution *) o2; - - int dominate1 ; // dominate1 indicates if some objective of solution1 - // dominates the same objective in solution2. dominate2 - int dominate2 ; // is the complementary of dominate1. - - dominate1 = 0 ; - dominate2 = 0 ; - - int flag; //stores the result of the comparison - - if (one->getOverallConstraintViolation()!= - two->getOverallConstraintViolation() && - ((one->getOverallConstraintViolation() < 0) || - (two->getOverallConstraintViolation() < 0))){ - int returnValue = overallConstraintViolationComparator_->compare(one,two); - return returnValue; - } - - // Equal number of violated constraints. Applying a dominance Test then - double value1, value2; - for (int i = 0; i < one->getNumberOfObjectives(); i++) { - value1 = one->getObjective(i); - value2 = two->getObjective(i); - if (value1 < value2) { - flag = -1; - } else if (value1 > value2) { - flag = 1; - } else { - flag = 0; +int DominanceComparator::compare(void * o1, void * o2) +{ + + if (o1==nullptr) + return 1; + else if (o2 == nullptr) + return -1; + + Solution * one = (Solution *) o1; + Solution * two = (Solution *) o2; + + int dominate1 ; // dominate1 indicates if some objective of solution1 + // dominates the same objective in solution2. dominate2 + int dominate2 ; // is the complementary of dominate1. + + dominate1 = 0 ; + dominate2 = 0 ; + + int flag; //stores the result of the comparison + + if (one->getOverallConstraintViolation()!= + two->getOverallConstraintViolation() && + ((one->getOverallConstraintViolation() < 0) || + (two->getOverallConstraintViolation() < 0))) + { + int returnValue = overallConstraintViolationComparator_->compare(one,two); + return returnValue; } - if (flag == -1) { - dominate1 = 1; + // Equal number of violated constraints. Applying a dominance Test then + double value1, value2; + for (int i = 0; i < one->getNumberOfObjectives(); i++) + { + value1 = one->getObjective(i); + value2 = two->getObjective(i); + if (value1 < value2) + { + flag = -1; + } + else if (value1 > value2) + { + flag = 1; + } + else + { + flag = 0; + } + + if (flag == -1) + { + dominate1 = 1; + } + + if (flag == 1) + { + dominate2 = 1; + } } - if (flag == 1) { - dominate2 = 1; + if (dominate1 == dominate2) + { + return 0; //No one dominate the other + } + if (dominate1 == 1) + { + return -1; // solution1 dominate } - } - - if (dominate1 == dominate2) { - return 0; //No one dominate the other - } - if (dominate1 == 1) { - return -1; // solution1 dominate - } - return 1; // solution2 dominate + return 1; // solution2 dominate } // compare diff --git a/src/util/comparators/DominanceComparator.h b/src/util/comparators/DominanceComparator.h index f68a6bb..d52ac05 100644 --- a/src/util/comparators/DominanceComparator.h +++ b/src/util/comparators/DominanceComparator.h @@ -32,15 +32,16 @@ * Solution objects) based on a constraint violation test + * dominance checking, as in NSGA-II. */ -class DominanceComparator : public Comparator { +class DominanceComparator : public Comparator +{ private: - Comparator * overallConstraintViolationComparator_; + Comparator * overallConstraintViolationComparator_; public: - DominanceComparator(); - ~DominanceComparator(); - int compare(void *one, void *two); + DominanceComparator(); + ~DominanceComparator(); + int compare(void *one, void *two); }; #endif diff --git a/src/util/comparators/EpsilonDominanceComparator.cpp b/src/util/comparators/EpsilonDominanceComparator.cpp index af9859c..c52de16 100644 --- a/src/util/comparators/EpsilonDominanceComparator.cpp +++ b/src/util/comparators/EpsilonDominanceComparator.cpp @@ -2,7 +2,7 @@ // // Authors: // Esteban López-Camacho -// +// // Copyright (c) 2014 Antonio J. Nebro // // This program is free software: you can redistribute it and/or modify @@ -14,7 +14,7 @@ // but WITHOUT ANY WARRANTY; without even the implied warranty of // MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the // GNU Lesser General Public License for more details. -// +// // You should have received a copy of the GNU Lesser General Public License // along with this program. If not, see . @@ -29,16 +29,18 @@ * Constructor. * @param eta Value for epsilon-dominance. */ -EpsilonDominanceComparator::EpsilonDominanceComparator(double eta) : Comparator() { - eta_ = eta; - overallConstraintViolationComparator_ = new OverallConstraintViolationComparator(); +EpsilonDominanceComparator::EpsilonDominanceComparator(double eta) : Comparator() +{ + eta_ = eta; + overallConstraintViolationComparator_ = snew OverallConstraintViolationComparator(); } // EpsilonDominanceComparator /** * Destructor. */ -EpsilonDominanceComparator::~EpsilonDominanceComparator() { - delete overallConstraintViolationComparator_; +EpsilonDominanceComparator::~EpsilonDominanceComparator() +{ + delete overallConstraintViolationComparator_; } // ~EpsilonDominanceComparator /** @@ -48,61 +50,73 @@ EpsilonDominanceComparator::~EpsilonDominanceComparator() { * @return -1, or 0, or 1 if o1 dominates o2, both are * non-dominated, or o1 is dominated by o2, respectively. */ -int EpsilonDominanceComparator::compare(void *o1, void *o2) { - - if (o1==NULL) - return 1; - else if (o2 == NULL) - return -1; - - Solution * solution1 = (Solution *) o1; - Solution * solution2 = (Solution *) o2; - - int dominate1 ; // dominate1 indicates if some objective of solution1 - // dominates the same objective in solution2. dominate2 - int dominate2 ; // is the complementary of dominate1. - - dominate1 = 0 ; - dominate2 = 0 ; - - int flag; //stores the result of the comparison - - flag = overallConstraintViolationComparator_->compare(solution1,solution2); - - if (flag != 0) { - return flag; - } - - // Equal number of violated constraints. Applying a dominance Test then - double value1, value2; - for (int i = 0; i < solution1->getNumberOfObjectives(); i++) { - value1 = solution1->getObjective(i); - value2 = solution2->getObjective(i); - - //Objetive implements comparable!!! - if (value1/(1 + eta_) < value2) { - flag = -1; - } else if (value1/(1 + eta_) > value2) { - flag = 1; - } else { - flag = 0; +int EpsilonDominanceComparator::compare(void *o1, void *o2) +{ + + if (o1==nullptr) + return 1; + else if (o2 == nullptr) + return -1; + + Solution * solution1 = (Solution *) o1; + Solution * solution2 = (Solution *) o2; + + int dominate1 ; // dominate1 indicates if some objective of solution1 + // dominates the same objective in solution2. dominate2 + int dominate2 ; // is the complementary of dominate1. + + dominate1 = 0 ; + dominate2 = 0 ; + + int flag; //stores the result of the comparison + + flag = overallConstraintViolationComparator_->compare(solution1,solution2); + + if (flag != 0) + { + return flag; } - if (flag == -1) { - dominate1 = 1; + // Equal number of violated constraints. Applying a dominance Test then + double value1, value2; + for (int i = 0; i < solution1->getNumberOfObjectives(); i++) + { + value1 = solution1->getObjective(i); + value2 = solution2->getObjective(i); + + //Objetive implements comparable!!! + if (value1/(1 + eta_) < value2) + { + flag = -1; + } + else if (value1/(1 + eta_) > value2) + { + flag = 1; + } + else + { + flag = 0; + } + + if (flag == -1) + { + dominate1 = 1; + } + + if (flag == 1) + { + dominate2 = 1; + } } - if (flag == 1) { - dominate2 = 1; + if (dominate1 == dominate2) + { + return 0; //No one dominates the other + } + if (dominate1 == 1) + { + return -1; // solution1 dominates } - } - - if (dominate1 == dominate2) { - return 0; //No one dominates the other - } - if (dominate1 == 1) { - return -1; // solution1 dominates - } - return 1; // solution2 dominates + return 1; // solution2 dominates } // compare diff --git a/src/util/comparators/EpsilonDominanceComparator.h b/src/util/comparators/EpsilonDominanceComparator.h index c9dabe0..d0c466b 100644 --- a/src/util/comparators/EpsilonDominanceComparator.h +++ b/src/util/comparators/EpsilonDominanceComparator.h @@ -29,41 +29,42 @@ * This class implements a Comparator (a method for comparing * Solution objects) based on epsilon dominance. */ -class EpsilonDominanceComparator : public Comparator { +class EpsilonDominanceComparator : public Comparator +{ private: - /** - * Stores the value of eta, needed for epsilon-dominance. - */ - double eta_; + /** + * Stores the value of eta, needed for epsilon-dominance. + */ + double eta_; - /** - * Stores a comparator for check the OverallConstraintComparator - */ - Comparator *overallConstraintViolationComparator_; + /** + * Stores a comparator for check the OverallConstraintComparator + */ + Comparator *overallConstraintViolationComparator_; public: - /** - * Constructor. - * @param eta Value for epsilon-dominance. - */ - EpsilonDominanceComparator(double eta); + /** + * Constructor. + * @param eta Value for epsilon-dominance. + */ + EpsilonDominanceComparator(double eta); - /** - * Destructor. - */ - ~EpsilonDominanceComparator(); + /** + * Destructor. + */ + ~EpsilonDominanceComparator(); - /** - * Compares two solutions. - * @param o1 Object representing the first Solution. - * @param o1 Object representing the second Solution. - * @return -1, or 0, or 1 if o1 dominates o2, both are - * non-dominated, or o1 is dominated by o2, respectively. - */ - int compare(void *o1, void *o2); + /** + * Compares two solutions. + * @param o1 Object representing the first Solution. + * @param o1 Object representing the second Solution. + * @return -1, or 0, or 1 if o1 dominates o2, both are + * non-dominated, or o1 is dominated by o2, respectively. + */ + int compare(void *o1, void *o2); }; #endif diff --git a/src/util/comparators/EpsilonObjectiveComparator.cpp b/src/util/comparators/EpsilonObjectiveComparator.cpp index 5c675e2..807540c 100644 --- a/src/util/comparators/EpsilonObjectiveComparator.cpp +++ b/src/util/comparators/EpsilonObjectiveComparator.cpp @@ -31,9 +31,10 @@ * @param nObj Index of the objective to compare. * @param eta Value for epsilon-dominance. */ -EpsilonObjectiveComparator::EpsilonObjectiveComparator(int nObj, double eta) : Comparator() { - objective_ = nObj; - eta_ = eta; +EpsilonObjectiveComparator::EpsilonObjectiveComparator(int nObj, double eta) : Comparator() +{ + objective_ = nObj; + eta_ = eta; } // EpsilonObjectiveComparator @@ -44,23 +45,29 @@ EpsilonObjectiveComparator::EpsilonObjectiveComparator(int nObj, double eta) : C * @return -1, or 0, or 1 if o1 is less than, equal, or greater than o2, * respectively. */ -int EpsilonObjectiveComparator::compare(void *o1, void *o2) { +int EpsilonObjectiveComparator::compare(void *o1, void *o2) +{ - if (o1==NULL) - return 1; - else if (o2 == NULL) - return -1; + if (o1==nullptr) + return 1; + else if (o2 == nullptr) + return -1; - double objetive1 = ((Solution *) o1)->getObjective(objective_); - double objetive2 = ((Solution *) o2)->getObjective(objective_); + double objetive1 = ((Solution *) o1)->getObjective(objective_); + double objetive2 = ((Solution *) o2)->getObjective(objective_); - //Objetive implements comparable!!! - if (objetive1/(1 + eta_) < objetive2) { - return -1; - } else if (objetive1/(1 + eta_) > objetive2) { - return 1; - } else { - return 0; - } + //Objetive implements comparable!!! + if (objetive1/(1 + eta_) < objetive2) + { + return -1; + } + else if (objetive1/(1 + eta_) > objetive2) + { + return 1; + } + else + { + return 0; + } } // compare diff --git a/src/util/comparators/EpsilonObjectiveComparator.h b/src/util/comparators/EpsilonObjectiveComparator.h index c2c80c4..e41ea8a 100644 --- a/src/util/comparators/EpsilonObjectiveComparator.h +++ b/src/util/comparators/EpsilonObjectiveComparator.h @@ -29,37 +29,38 @@ * Solution objects) based on epsilon dominance over a given * objective function. */ -class EpsilonObjectiveComparator : public Comparator { +class EpsilonObjectiveComparator : public Comparator +{ private: - /** - * Stores the objective index to compare - */ - int objective_; + /** + * Stores the objective index to compare + */ + int objective_; - /** - * Stores the eta value for epsilon-dominance - */ - double eta_; + /** + * Stores the eta value for epsilon-dominance + */ + double eta_; public: - /** - * Constructor. - * @param nObj Index of the objective to compare. - * @param eta Value for epsilon-dominance. - */ - EpsilonObjectiveComparator(int nObj, double eta); + /** + * Constructor. + * @param nObj Index of the objective to compare. + * @param eta Value for epsilon-dominance. + */ + EpsilonObjectiveComparator(int nObj, double eta); - /** - * Compares two solutions. - * @param o1 Object representing the first Solution. - * @param o2 Object representing the second Solution. - * @return -1, or 0, or 1 if o1 is less than, equal, or greater than o2, - * respectively. - */ - int compare(void *one, void *two); + /** + * Compares two solutions. + * @param o1 Object representing the first Solution. + * @param o2 Object representing the second Solution. + * @return -1, or 0, or 1 if o1 is less than, equal, or greater than o2, + * respectively. + */ + int compare(void *one, void *two); }; #endif diff --git a/src/util/comparators/EqualSolutions.cpp b/src/util/comparators/EqualSolutions.cpp index be74eca..a9fdd40 100644 --- a/src/util/comparators/EqualSolutions.cpp +++ b/src/util/comparators/EqualSolutions.cpp @@ -38,59 +38,72 @@ * and solution2 are equals, or solution1 is greater than solution2, * respectively. */ -int EqualSolutions::compare(void * o1, void * o2) { - - if (o1==NULL) - return 1; - else if (o2 == NULL) - return -1; - - int dominate1 ; // dominate1 indicates if some objective of solution1 - // dominates the same objective in solution2. dominate2 - int dominate2 ; // is the complementary of dominate1. - - dominate1 = 0 ; - dominate2 = 0 ; - - Solution * solution1 = (Solution *) o1; - Solution * solution2 = (Solution *) o2; - - int flag; - double value1, value2; - for (int i = 0; i < solution1->getNumberOfObjectives(); i++) { - Comparator * c = new ObjectiveComparator(i); - flag = c->compare(solution1,solution2); - delete c; - value1 = solution1->getObjective(i); - value2 = solution2->getObjective(i); - - if (value1 < value2) { - flag = -1; - } else if (value1 > value2) { - flag = 1; - } else { - flag = 0; +int EqualSolutions::compare(void * o1, void * o2) +{ + + if (o1==nullptr) + return 1; + else if (o2 == nullptr) + return -1; + + int dominate1 ; // dominate1 indicates if some objective of solution1 + // dominates the same objective in solution2. dominate2 + int dominate2 ; // is the complementary of dominate1. + + dominate1 = 0 ; + dominate2 = 0 ; + + Solution * solution1 = (Solution *) o1; + Solution * solution2 = (Solution *) o2; + + int flag; + double value1, value2; + for (int i = 0; i < solution1->getNumberOfObjectives(); i++) + { + Comparator * c = snew ObjectiveComparator(i); + flag = c->compare(solution1,solution2); + delete c; + value1 = solution1->getObjective(i); + value2 = solution2->getObjective(i); + + if (value1 < value2) + { + flag = -1; + } + else if (value1 > value2) + { + flag = 1; + } + else + { + flag = 0; + } + + if (flag == -1) + { + dominate1 = 1; + } + + if (flag == 1) + { + dominate2 = 1; + } } - if (flag == -1) { - dominate1 = 1; + if (dominate1== 0 && dominate2 ==0) + { + return 0; //No one dominate the other } - if (flag == 1) { - dominate2 = 1; + if (dominate1 == 1) + { + return -1; // solution1 dominate + } + else if (dominate2 == 1) + { + return 1; // solution2 dominate } - } - - if (dominate1== 0 && dominate2 ==0) { - return 0; //No one dominate the other - } - - if (dominate1 == 1) { - return -1; // solution1 dominate - } else if (dominate2 == 1) { - return 1; // solution2 dominate - } - return 2; + return 2; } // compare diff --git a/src/util/comparators/EqualSolutions.h b/src/util/comparators/EqualSolutions.h index 32991b7..a3bcf75 100644 --- a/src/util/comparators/EqualSolutions.h +++ b/src/util/comparators/EqualSolutions.h @@ -31,10 +31,11 @@ * equal or not. A dominance test is applied to decide about what solution * is the best. */ -class EqualSolutions : public Comparator { +class EqualSolutions : public Comparator +{ public: - int compare(void *solution1, void *solution2); + int compare(void *solution1, void *solution2); }; #endif diff --git a/src/util/comparators/ObjectiveComparator.cpp b/src/util/comparators/ObjectiveComparator.cpp index f9cc5fc..49f89e2 100644 --- a/src/util/comparators/ObjectiveComparator.cpp +++ b/src/util/comparators/ObjectiveComparator.cpp @@ -26,9 +26,10 @@ * Constructor. * @param nObj The index of the objective to compare */ -ObjectiveComparator::ObjectiveComparator(int nObj) { - this->nObj = nObj; - ascendingOrder_ = true; +ObjectiveComparator::ObjectiveComparator(int nObj) +{ + this->nObj = nObj; + ascendingOrder_ = true; } // ObjectiveComparator /** @@ -36,9 +37,10 @@ ObjectiveComparator::ObjectiveComparator(int nObj) { * @param nObj The index of the objective to compare * @param descendingOrder TRUE if use a descending order, FALSE otherwise */ -ObjectiveComparator::ObjectiveComparator(int nObj, bool descendingOrder) { - this->nObj = nObj; - ascendingOrder_ = !descendingOrder; +ObjectiveComparator::ObjectiveComparator(int nObj, bool descendingOrder) +{ + this->nObj = nObj; + ascendingOrder_ = !descendingOrder; } // ObjectiveComparator /** @@ -48,30 +50,44 @@ ObjectiveComparator::ObjectiveComparator(int nObj, bool descendingOrder) { * @return -1, or 0, or 1 if o1 is less than, equal, or greater than o2, * respectively. **/ -int ObjectiveComparator::compare(void *o1, void *o2) { - if (o1==NULL) - return 1; - else if (o2 == NULL) - return -1; +int ObjectiveComparator::compare(void *o1, void *o2) +{ + if (o1==nullptr) + return 1; + else if (o2 == nullptr) + return -1; - double objetive1 = ((Solution *) o1)->getObjective(this->nObj); - double objetive2 = ((Solution *) o2)->getObjective(this->nObj); - if (ascendingOrder_) { - if (objetive1 < objetive2) { - return -1; - } else if (objetive1 > objetive2) { - return 1; - } else { - return 0; + double objetive1 = ((Solution *) o1)->getObjective(this->nObj); + double objetive2 = ((Solution *) o2)->getObjective(this->nObj); + if (ascendingOrder_) + { + if (objetive1 < objetive2) + { + return -1; + } + else if (objetive1 > objetive2) + { + return 1; + } + else + { + return 0; + } } - } else { - if (objetive1 < objetive2) { - return 1; - } else if (objetive1 > objetive2) { - return -1; - } else { - return 0; + else + { + if (objetive1 < objetive2) + { + return 1; + } + else if (objetive1 > objetive2) + { + return -1; + } + else + { + return 0; + } } - } } // compare diff --git a/src/util/comparators/ObjectiveComparator.h b/src/util/comparators/ObjectiveComparator.h index 601a4aa..111fd6d 100644 --- a/src/util/comparators/ObjectiveComparator.h +++ b/src/util/comparators/ObjectiveComparator.h @@ -28,16 +28,17 @@ * This class implements a Comparator (a method for comparing * Solution objects) based on a objective values. */ -class ObjectiveComparator : public Comparator { +class ObjectiveComparator : public Comparator +{ private: - int nObj; - bool ascendingOrder_; + int nObj; + bool ascendingOrder_; public: - ObjectiveComparator(int nObj); - ObjectiveComparator(int nObj, bool descendingOrder); - int compare(void * o1, void * o2); + ObjectiveComparator(int nObj); + ObjectiveComparator(int nObj, bool descendingOrder); + int compare(void * o1, void * o2); }; diff --git a/src/util/comparators/OverallConstraintViolationComparator.cpp b/src/util/comparators/OverallConstraintViolationComparator.cpp index 6fec3f0..f42c550 100644 --- a/src/util/comparators/OverallConstraintViolationComparator.cpp +++ b/src/util/comparators/OverallConstraintViolationComparator.cpp @@ -29,25 +29,38 @@ * @return -1, or 0, or 1 if o1 is less than, equal, or greater than o2, * respectively. */ -int OverallConstraintViolationComparator::compare(void *o1, void *o2) { - double overall1, overall2; - overall1 = ((Solution *) o1)->getOverallConstraintViolation(); - overall2 = ((Solution *) o2)->getOverallConstraintViolation(); +int OverallConstraintViolationComparator::compare(void *o1, void *o2) +{ + double overall1, overall2; + overall1 = ((Solution *) o1)->getOverallConstraintViolation(); + overall2 = ((Solution *) o2)->getOverallConstraintViolation(); - if ((overall1 < 0) && (overall2 < 0)) { - if (overall1 > overall2){ - return -1; - } else if (overall2 > overall1){ - return 1; - } else { - return 0; + if ((overall1 < 0) && (overall2 < 0)) + { + if (overall1 > overall2) + { + return -1; + } + else if (overall2 > overall1) + { + return 1; + } + else + { + return 0; + } + } + else if ((overall1 == 0) && (overall2 < 0)) + { + return -1; + } + else if ((overall1 < 0) && (overall2 == 0)) + { + return 1; + } + else + { + return 0; } - } else if ((overall1 == 0) && (overall2 < 0)) { - return -1; - } else if ((overall1 < 0) && (overall2 == 0)) { - return 1; - } else { - return 0; - } } // compare diff --git a/src/util/comparators/OverallConstraintViolationComparator.h b/src/util/comparators/OverallConstraintViolationComparator.h index 6680149..5a1359e 100644 --- a/src/util/comparators/OverallConstraintViolationComparator.h +++ b/src/util/comparators/OverallConstraintViolationComparator.h @@ -29,10 +29,11 @@ * Solution objects) based on the overall constraint violation of * the solucions, as in NSGA-II. */ -class OverallConstraintViolationComparator : public Comparator { +class OverallConstraintViolationComparator : public Comparator +{ public: - int compare(void * o1, void * o2); + int compare(void * o1, void * o2); }; diff --git a/src/util/comparators/RankComparator.cpp b/src/util/comparators/RankComparator.cpp index ec0168f..ea10c29 100644 --- a/src/util/comparators/RankComparator.cpp +++ b/src/util/comparators/RankComparator.cpp @@ -29,23 +29,24 @@ * @return -1, or 0, or 1 if o1 is less than, equal, or greater than o2, * respectively. */ -int RankComparator::compare(void *o1, void *o2) { +int RankComparator::compare(void *o1, void *o2) +{ - if (o1 == NULL) - return 1; - else if (o2 == NULL) - return -1; + if (o1 == nullptr) + return 1; + else if (o2 == nullptr) + return -1; - Solution * solution1 = (Solution *) o1; - Solution * solution2 = (Solution *) o2; + Solution * solution1 = (Solution *) o1; + Solution * solution2 = (Solution *) o2; - if (solution1->getRank() < solution2->getRank()) - return -1; + if (solution1->getRank() < solution2->getRank()) + return -1; - if (solution1->getRank() > solution2->getRank()) - return 1; + if (solution1->getRank() > solution2->getRank()) + return 1; - return 0; + return 0; } // compare diff --git a/src/util/comparators/RankComparator.h b/src/util/comparators/RankComparator.h index dcc8609..97d0250 100644 --- a/src/util/comparators/RankComparator.h +++ b/src/util/comparators/RankComparator.h @@ -28,10 +28,11 @@ * This class implements a Comparator (a method for comparing * Solution objects) based on the rank of the solutions. */ -class RankComparator : public Comparator { +class RankComparator : public Comparator +{ public: - int compare(void * o1, void * o2); + int compare(void * o1, void * o2); }; diff --git a/src/util/comparators/SolutionComparator.cpp b/src/util/comparators/SolutionComparator.cpp index 036ee92..1d7ae3b 100644 --- a/src/util/comparators/SolutionComparator.cpp +++ b/src/util/comparators/SolutionComparator.cpp @@ -35,23 +35,25 @@ double SolutionComparator::EPSILON = 1e-10; * @return 0, if both solutions are equals with a certain dissimilarity, -1 * otherwise. **/ -int SolutionComparator::compare(void *o1, void *o2) { +int SolutionComparator::compare(void *o1, void *o2) +{ - Solution * solution1 = (Solution *) o1; - Solution * solution2 = (Solution *) o2; + Solution * solution1 = (Solution *) o1; + Solution * solution2 = (Solution *) o2; - int res = -1; + int res = -1; - if (solution1->getNumberOfVariables() != solution2->getNumberOfVariables()) - return res; + if (solution1->getNumberOfVariables() != solution2->getNumberOfVariables()) + return res; - Distance * d = new Distance(); - if (d->distanceBetweenSolutions(solution1,solution2) < EPSILON) { - res = 0; - } - delete d; + Distance * d = new Distance(); + if (d->distanceBetweenSolutions(solution1,solution2) < EPSILON) + { + res = 0; + } + delete d; - return res; + return res; } // compare diff --git a/src/util/comparators/SolutionComparator.h b/src/util/comparators/SolutionComparator.h index d628456..2bd6442 100644 --- a/src/util/comparators/SolutionComparator.h +++ b/src/util/comparators/SolutionComparator.h @@ -29,13 +29,14 @@ * This class implements a Comparator (a method for comparing * Solution objects) based on the values of the variables. */ -class SolutionComparator : public Comparator { +class SolutionComparator : public Comparator +{ private: - static double EPSILON; + static double EPSILON; public: - int compare(void * o1, void * o2); + int compare(void * o1, void * o2); }; // SolutionComparator diff --git a/src/util/wrapper/CMakeLists.txt b/src/util/wrapper/CMakeLists.txt new file mode 100644 index 0000000..ca3372a --- /dev/null +++ b/src/util/wrapper/CMakeLists.txt @@ -0,0 +1,3 @@ +file(GLOB SOURCES "*.cpp" "*.h") +ListToString(SOURCES ";" ${SOURCES}) +LIST_APPEND("${SOURCES}") diff --git a/src/util/wrapper/XReal.cpp b/src/util/wrapper/XReal.cpp index 720072b..8e86a1f 100644 --- a/src/util/wrapper/XReal.cpp +++ b/src/util/wrapper/XReal.cpp @@ -27,7 +27,8 @@ /** * Constructor */ -XReal::XReal() { +XReal::XReal() +{ } // Constructor @@ -35,9 +36,10 @@ XReal::XReal() { * Constructor * @param solution */ -XReal::XReal(Solution * solution) { - type_ = solution->getType(); - solution_ = solution; +XReal::XReal(Solution * solution) +{ + type_ = solution->getType(); + solution_ = solution; } @@ -47,20 +49,25 @@ XReal::XReal(Solution * solution) { * @return The value of the variable * @throws JMException */ -double XReal::getValue(int index) { - if ((typeid(*type_) == typeid(RealSolutionType)) || - (typeid(*type_) == typeid(BinaryRealSolutionType))){ - return solution_->getDecisionVariables()[index]->getValue(); - } - else if (typeid(*type_) == typeid(ArrayRealSolutionType)) { - return ((ArrayReal*)(solution_->getDecisionVariables()[0]))->array_[index]; - } - else { - cout << "ERROR GRAVE: solution type " - << typeid(*type_).name() << " invalid" << endl; - exit(-1); - } - return 0.0; +double XReal::getValue(int index) +{ + if ((typeid(*type_) == typeid(RealSolutionType)) || + (typeid(*type_) == typeid(BinaryRealSolutionType))) + { + return solution_->getDecisionVariables()[index]->getValue(); + } + else if (typeid(*type_) == typeid(ArrayRealSolutionType)) + { + //return ((ArrayReal*)(solution_->getDecisionVariables()[0]))->array_[index]; + return ((ArrayReal*)(solution_->getDecisionVariables()[0]))->getValue(index); + } + else + { + std::cout << "ERROR GRAVE: solution type " + << typeid(*type_).name() << " invalid" << std::endl; + exit(-1); + } + return 0.0; } // getValue @@ -70,19 +77,24 @@ double XReal::getValue(int index) { * @param value Value to be assigned * @throws JMException */ -void XReal::setValue(int index, double value) { - if ((typeid(*type_) == typeid(RealSolutionType)) || - (typeid(*type_) == typeid(BinaryRealSolutionType))){ - solution_->getDecisionVariables()[index]->setValue(value); - } - else if (typeid(*type_) == typeid(ArrayRealSolutionType)) { - ((ArrayReal*)(solution_->getDecisionVariables()[0]))->array_[index]=value; - } - else { - cout << "ERROR GRAVE: solution type " - << typeid(*type_).name() << " invalid" << endl; - exit(-1); - } +void XReal::setValue(int index, double value) +{ + if ((typeid(*type_) == typeid(RealSolutionType)) || + (typeid(*type_) == typeid(BinaryRealSolutionType))) + { + solution_->getDecisionVariables()[index]->setValue(value); + } + else if (typeid(*type_) == typeid(ArrayRealSolutionType)) + { + //((ArrayReal*)(solution_->getDecisionVariables()[0]))->array_[index]=value; + ((ArrayReal*)(solution_->getDecisionVariables()[0]))->setValue(index, value); + } + else + { + std::cout << "ERROR GRAVE: solution type " + << typeid(*type_).name() << " invalid" << std::endl; + exit(-1); + } } // setValue @@ -92,18 +104,20 @@ void XReal::setValue(int index, double value) { * @return The lower bound of the variable * @throws JMException */ -double XReal::getLowerBound(int index) { - if ((typeid(*type_) == typeid(RealSolutionType)) || - (typeid(*type_) == typeid(BinaryRealSolutionType))) - return solution_->getDecisionVariables()[index]->getLowerBound(); - else if (typeid(*type_) == typeid(ArrayRealSolutionType)) - return ((ArrayReal*)(solution_->getDecisionVariables()[0]))->getLowerBound(index); - else { - cout << "ERROR GRAVE: solution type " - << typeid(*type_).name() << " invalid" << endl; - exit(-1); - } - return 0.0; +double XReal::getLowerBound(int index) +{ + if ((typeid(*type_) == typeid(RealSolutionType)) || + (typeid(*type_) == typeid(BinaryRealSolutionType))) + return solution_->getDecisionVariables()[index]->getLowerBound(); + else if (typeid(*type_) == typeid(ArrayRealSolutionType)) + return ((ArrayReal*)(solution_->getDecisionVariables()[0]))->getLowerBound(index); + else + { + std::cout << "ERROR GRAVE: solution type " + << typeid(*type_).name() << " invalid" << std::endl; + exit(-1); + } + return 0.0; } // getLowerBound @@ -113,18 +127,20 @@ double XReal::getLowerBound(int index) { * @return The upper bound of the variable * @throws JMException */ -double XReal::getUpperBound(int index) { - if ((typeid(*type_) == typeid(RealSolutionType)) || - (typeid(*type_) == typeid(BinaryRealSolutionType))) - return solution_->getDecisionVariables()[index]->getUpperBound(); - else if (typeid(*type_) == typeid(ArrayRealSolutionType)) - return ((ArrayReal*)(solution_->getDecisionVariables()[0]))->getUpperBound(index); - else { - cout << "ERROR GRAVE: solution type " - << typeid(*type_).name() << " invalid" << endl; - exit(-1); - } - return 0.0; +double XReal::getUpperBound(int index) +{ + if ((typeid(*type_) == typeid(RealSolutionType)) || + (typeid(*type_) == typeid(BinaryRealSolutionType))) + return solution_->getDecisionVariables()[index]->getUpperBound(); + else if (typeid(*type_) == typeid(ArrayRealSolutionType)) + return ((ArrayReal*)(solution_->getDecisionVariables()[0]))->getUpperBound(index); + else + { + std::cout << "ERROR GRAVE: solution type " + << typeid(*type_).name() << " invalid" << std::endl; + exit(-1); + } + return 0.0; } // getUpperBound @@ -132,19 +148,21 @@ double XReal::getUpperBound(int index) { * Returns the number of variables of the solution * @return */ -int XReal::getNumberOfDecisionVariables() { - if ((typeid(*type_) == typeid(RealSolutionType)) || - (typeid(*type_) == typeid(BinaryRealSolutionType))) - //return solution_->getDecisionVariables().length ; - return solution_->getNumberOfVariables(); - else if (typeid(*type_) == typeid(ArrayRealSolutionType)) - return ((ArrayReal*)(solution_->getDecisionVariables()[0]))->getLength() ; - else { - cout << "ERROR GRAVE: solution type " - << typeid(*type_).name() << " invalid" << endl; - exit(-1); - } - return 0 ; +int XReal::getNumberOfDecisionVariables() +{ + if ((typeid(*type_) == typeid(RealSolutionType)) || + (typeid(*type_) == typeid(BinaryRealSolutionType))) + //return solution_->getDecisionVariables().length ; + return solution_->getNumberOfVariables(); + else if (typeid(*type_) == typeid(ArrayRealSolutionType)) + return ((ArrayReal*)(solution_->getDecisionVariables()[0]))->getLength() ; + else + { + std::cout << "ERROR GRAVE: solution type " + << typeid(*type_).name() << " invalid" << std::endl; + exit(-1); + } + return 0 ; } // getNumberOfDecisionVariables @@ -152,21 +170,24 @@ int XReal::getNumberOfDecisionVariables() { * Returns the number of variables of the solution * @return */ -int XReal::size() { - if ((typeid(*type_) == typeid(RealSolutionType)) || - (typeid(*type_) == typeid(BinaryRealSolutionType))) - return solution_->getNumberOfVariables(); - else if (typeid(*type_) == typeid(ArrayRealSolutionType)) - return ((ArrayReal*)(solution_->getDecisionVariables()[0]))->getLength(); - else { - cout << "ERROR GRAVE: solution type " - << typeid(*type_).name() << " invalid" << endl; - exit(-1); - } - return 0 ; +int XReal::size() +{ + if ((typeid(*type_) == typeid(RealSolutionType)) || + (typeid(*type_) == typeid(BinaryRealSolutionType))) + return solution_->getNumberOfVariables(); + else if (typeid(*type_) == typeid(ArrayRealSolutionType)) + return ((ArrayReal*)(solution_->getDecisionVariables()[0]))->getLength(); + else + { + std::cout << "ERROR GRAVE: solution type " + << typeid(*type_).name() << " invalid" << std::endl; + exit(-1); + } + return 0 ; } // size -Solution * XReal::getSolution() { - return solution_; +Solution * XReal::getSolution() +{ + return solution_; } // getSolution diff --git a/src/util/wrapper/XReal.h b/src/util/wrapper/XReal.h index dd5526c..5c9899b 100644 --- a/src/util/wrapper/XReal.h +++ b/src/util/wrapper/XReal.h @@ -33,22 +33,23 @@ * This class allows to apply a SBX crossover operator using two parent * solutions. **/ -class XReal { +class XReal +{ public: - XReal(); - XReal(Solution * solution); - double getValue(int index); - void setValue(int index, double value); - double getLowerBound(int index); - double getUpperBound(int index); - int getNumberOfDecisionVariables(); - int size(); - Solution * getSolution(); + XReal(); + XReal(Solution * solution); + double getValue(int index); + void setValue(int index, double value); + double getLowerBound(int index); + double getUpperBound(int index); + int getNumberOfDecisionVariables(); + int size(); + Solution * getSolution(); private: - Solution * solution_; - SolutionType * type_; + Solution * solution_; + SolutionType * type_; };