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quemy 2012-08-30 11:30:11 +02:00
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moeo/src/CMakeLists.txt Normal file
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######################################################################################
### 0) Include directories
######################################################################################
include_directories(${EO_SRC_DIR})
include_directories(${MO_SRC_DIR}/src)
include_directories(${CMAKE_CURRENT_SOURCE_DIR})
######################################################################################
### 1) Set paths
######################################################################################
set(MOEO_LIB_OUTPUT_PATH ${MOEO_BIN_DIR}/lib)
set(LIBRARY_OUTPUT_PATH ${MOEO_LIB_OUTPUT_PATH})
######################################################################################
### 2) Build lib
######################################################################################
set (MOEO_CORE core/moeoObjectiveVectorTraits.cpp)
add_library(moeo STATIC ${MOEO_CORE})
set(MOEO_VERSION ${GLOBAL_VERSION})
set_target_properties(moeo PROPERTIES VERSION "${MOEO_VERSION}")
install(TARGETS moeo ARCHIVE DESTINATION local/${LIB} COMPONENT libraries)
######################################################################################
### 3) Look for headers
######################################################################################
file(GLOB HDRS moeo)
install(FILES ${HDRS} DESTINATION local/include${INSTALL_SUB_DIR}/moeo COMPONENT headers)
######################################################################################
### 4) Install directories
######################################################################################
install(DIRECTORY acceptCrit algo archive comparator core distance diversity do explorer fitness hybridization metric replacement scalarStuffs selection utils
DESTINATION local/include${INSTALL_SUB_DIR}/moeo
COMPONENT headers
FILES_MATCHING PATTERN "*.h"
)

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moeo/src/algo/moeoASEEA.h Normal file
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/*
* <moeoASEEA.h>
* Copyright (C) DOLPHIN Project-Team, INRIA Futurs, 2006-2007
* (C) OPAC Team, LIFL, 2002-2007
*
* Arnaud Liefooghe
* Jérémie Humeau
* François Legillon
* Thibaut demaret
*
* This software is governed by the CeCILL license under French law and
* abiding by the rules of distribution of free software. You can use,
* modify and/ or redistribute the software under the terms of the CeCILL
* license as circulated by CEA, CNRS and INRIA at the following URL
* "http://www.cecill.info".
*
* As a counterpart to the access to the source code and rights to copy,
* modify and redistribute granted by the license, users are provided only
* with a limited warranty and the software's author, the holder of the
* economic rights, and the successive licensors have only limited liability.
*
* In this respect, the user's attention is drawn to the risks associated
* with loading, using, modifying and/or developing or reproducing the
* software by the user in light of its specific status of free software,
* that may mean that it is complicated to manipulate, and that also
* therefore means that it is reserved for developers and experienced
* professionals having in-depth computer knowledge. Users are therefore
* encouraged to load and test the software's suitability as regards their
* requirements in conditions enabling the security of their systems and/or
* data to be ensured and, more generally, to use and operate it in the
* same conditions as regards security.
* The fact that you are presently reading this means that you have had
* knowledge of the CeCILL license and that you accept its terms.
*
* ParadisEO WebSite : http://paradiseo.gforge.inria.fr
* Contact: paradiseo-help@lists.gforge.inria.fr
*
*/
//-----------------------------------------------------------------------------
#ifndef MOEOASEEA_H_
#define MOEOASEEA_H_
#include <eoBreed.h>
#include <eoCloneOps.h>
#include <eoContinue.h>
#include <eoEvalFunc.h>
#include <eoGenContinue.h>
#include <eoGeneralBreeder.h>
#include <eoGenOp.h>
#include <eoPopEvalFunc.h>
#include <eoSGAGenOp.h>
#include <algo/moeoEA.h>
#include <archive/moeoArchive.h>
#include <selection/moeoRandomSelect.h>
#include <selection/moeoSelectFromPopAndArch.h>
#include <selection/moeoDetArchiveSelect.h>
/**
* ASEEA (Adaptive Simple Elitist Evolutionary Algorithm).
*/
template < class MOEOT >
class moeoASEEA : public moeoEA < MOEOT >
{
public:
/**
* Ctor with a crossover, a mutation and their corresponding rates.
* @param _maxGen number of generations before stopping
* @param _eval evaluation function
* @param _crossover crossover
* @param _pCross crossover probability
* @param _mutation mutation
* @param _pMut mutation probability
* @param _archive archive
* @param _max the max size for the pop
*/
moeoASEEA (unsigned int _maxGen, eoEvalFunc < MOEOT > & _eval, eoQuadOp < MOEOT > & _crossover, double _pCross, eoMonOp < MOEOT > & _mutation, double _pMut, moeoArchive < MOEOT > & _archive, unsigned int _max) :
defaultGenContinuator(_maxGen), continuator(defaultGenContinuator), eval(_eval), defaultPopEval(_eval), popEval(defaultPopEval), selectMany(_archive, _max), transform(_crossover, _pCross, _mutation, _pMut), selectTransform(selectMany, transform), breed (selectTransform), archive(_archive)
{}
/**
* Ctor with a eoContinue.
* @param _continuator stopping criteria
* @param _eval evaluation function
* @param _crossover crossover
* @param _pCross crossover probability
* @param _mutation mutation
* @param _pMut mutation probability
* @param _archive archive
* @param _max the max size for the pop
*/
moeoASEEA (eoContinue < MOEOT > & _continuator, eoEvalFunc < MOEOT > & _eval, eoQuadOp < MOEOT > & _crossover, double _pCross, eoMonOp < MOEOT > & _mutation, double _pMut, moeoArchive < MOEOT > & _archive, unsigned int _max) :
defaultGenContinuator(0), continuator(_continuator), eval(_eval), defaultPopEval(_eval), popEval(defaultPopEval), selectMany(_archive, _max), transform(_crossover, _pCross, _mutation, _pMut), selectTransform(selectMany, transform), breed(selectTransform), archive(_archive)
{}
/**
* Ctor with a eoContinue, a eoPopEval.
* @param _continuator stopping criteria
* @param _popEval population evaluation function
* @param _crossover crossover
* @param _pCross crossover probability
* @param _mutation mutation
* @param _pMut mutation probability
* @param _archive archive
* @param _max the max size for the pop
*/
moeoASEEA (eoContinue < MOEOT > & _continuator, eoPopEvalFunc < MOEOT > & _popEval, eoQuadOp < MOEOT > & _crossover, double _pCross, eoMonOp < MOEOT > & _mutation, double _pMut, moeoArchive < MOEOT > & _archive, unsigned int _max) :
defaultGenContinuator(0), continuator(_continuator), eval(defaultEval), defaultPopEval(eval), popEval(_popEval), selectMany(_archive, _max), transform(_crossover, _pCross, _mutation, _pMut), selectTransform(selectMany, transform), breed(selectTransform), archive(_archive)
{}
/**
* Ctor with a eoContinue and a eoTransform.
* @param _continuator stopping criteria
* @param _eval evaluation function
* @param _transform variation operator
* @param _archive archive
* @param _max the max size for the pop
*/
moeoASEEA (eoContinue < MOEOT > & _continuator, eoEvalFunc < MOEOT > & _eval, eoTransform < MOEOT > & _transform, moeoArchive < MOEOT > & _archive, unsigned int _max) :
defaultGenContinuator(0), continuator(_continuator), eval(_eval), defaultPopEval(_eval), popEval(defaultPopEval), selectMany(_archive, _max), transform(defaultQuadOp, 0.0, defaultMonOp, 0.0), selectTransform(selectMany, _transform), breed(selectTransform), archive(_archive)
{}
/**
* Ctor with a eoContinue, a eoPopEval and a eoTransform.
* @param _continuator stopping criteria
* @param _popEval population evaluation function
* @param _transform variation operator
* @param _archive archive
* @param _max the max size for the pop
*/
moeoASEEA (eoContinue < MOEOT > & _continuator, eoPopEvalFunc < MOEOT > & _popEval, eoTransform < MOEOT > & _transform, moeoArchive < MOEOT > & _archive, unsigned int _max) :
defaultGenContinuator(0), continuator(_continuator), eval(defaultEval), defaultPopEval(eval), popEval(_popEval), selectMany(_archive, _max), transform(defaultQuadOp, 0.0, defaultMonOp, 0.0), selectTransform(selectMany, _transform), breed(selectTransform), archive(_archive)
{}
/**
* Apply a few generation of evolution to the population _pop until the stopping criteria is verified.
* @param _pop the population
*/
virtual void operator () (eoPop < MOEOT > &_pop)
{
eoPop < MOEOT > empty_pop, offspring;
popEval (empty_pop, _pop); // a first eval of _pop
archive(_pop); // archive update
while (continuator (_pop))
{
// generate offspring
breed (_pop, offspring);
popEval (_pop, offspring); // eval of offspring
// archive (_pop); // archive update
archive (offspring); // archive update
_pop.resize(0);
offspring.resize(0);
}
}
protected:
/** default eval */
class DummyEval : public eoEvalFunc < MOEOT >{
public:
void operator()(MOEOT &) {}
}defaultEval;
/** default transform */
class DummyTransform : public eoTransform < MOEOT >{
public :
void operator()(eoPop<MOEOT>&) {}
}defaultTransform;
/** a continuator based on the number of generations (used as default) */
eoGenContinue < MOEOT > defaultGenContinuator;
/** stopping criteria */
eoContinue < MOEOT > & continuator;
/** evaluation function */
eoEvalFunc < MOEOT > & eval;
/** default popEval */
eoPopLoopEval < MOEOT > defaultPopEval;
/** evaluation function used to evaluate the whole population */
eoPopEvalFunc < MOEOT > & popEval;
/** default select many */
moeoDetArchiveSelect < MOEOT > selectMany; // A REMPLACER !!!!!!!!!!! => add/moeoDetArchiveSelect.h
/** eoTransform */
eoSGATransform < MOEOT > transform;
/** select transform */
eoSelectTransform < MOEOT > selectTransform;
/** a default crossover */
eoQuadCloneOp < MOEOT > defaultQuadOp;
/** a default mutation */
eoMonCloneOp < MOEOT > defaultMonOp;
/** an object for genetic operators (used as default) */
//eoSGAGenOp < MOEOT > defaultSGAGenOp;
/** an object for genetic operators (used as default) */
//eoSGAGenOp < MOEOT >& genOp;
/** breeder */
eoBreed < MOEOT > & breed;
/**archive */
moeoArchive < MOEOT > & archive;
};
#endif /*MOEOASEEA_H_*/

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/*
* <moeoAlgo.h>
* Copyright (C) DOLPHIN Project-Team, INRIA Futurs, 2006-2007
* (C) OPAC Team, LIFL, 2002-2007
*
* Arnaud Liefooghe
*
* This software is governed by the CeCILL license under French law and
* abiding by the rules of distribution of free software. You can use,
* modify and/ or redistribute the software under the terms of the CeCILL
* license as circulated by CEA, CNRS and INRIA at the following URL
* "http://www.cecill.info".
*
* As a counterpart to the access to the source code and rights to copy,
* modify and redistribute granted by the license, users are provided only
* with a limited warranty and the software's author, the holder of the
* economic rights, and the successive licensors have only limited liability.
*
* In this respect, the user's attention is drawn to the risks associated
* with loading, using, modifying and/or developing or reproducing the
* software by the user in light of its specific status of free software,
* that may mean that it is complicated to manipulate, and that also
* therefore means that it is reserved for developers and experienced
* professionals having in-depth computer knowledge. Users are therefore
* encouraged to load and test the software's suitability as regards their
* requirements in conditions enabling the security of their systems and/or
* data to be ensured and, more generally, to use and operate it in the
* same conditions as regards security.
* The fact that you are presently reading this means that you have had
* knowledge of the CeCILL license and that you accept its terms.
*
* ParadisEO WebSite : http://paradiseo.gforge.inria.fr
* Contact: paradiseo-help@lists.gforge.inria.fr
*
*/
//-----------------------------------------------------------------------------
#ifndef MOEOALGO_H_
#define MOEOALGO_H_
/**
* Abstract class for multi-objective algorithms.
*/
class moeoAlgo
{};
#endif /*MOEOALGO_H_*/

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moeo/src/algo/moeoEA.h Normal file
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/*
* <moeoEA.h>
* Copyright (C) DOLPHIN Project-Team, INRIA Futurs, 2006-2007
* (C) OPAC Team, LIFL, 2002-2007
*
* Arnaud Liefooghe
*
* This software is governed by the CeCILL license under French law and
* abiding by the rules of distribution of free software. You can use,
* modify and/ or redistribute the software under the terms of the CeCILL
* license as circulated by CEA, CNRS and INRIA at the following URL
* "http://www.cecill.info".
*
* As a counterpart to the access to the source code and rights to copy,
* modify and redistribute granted by the license, users are provided only
* with a limited warranty and the software's author, the holder of the
* economic rights, and the successive licensors have only limited liability.
*
* In this respect, the user's attention is drawn to the risks associated
* with loading, using, modifying and/or developing or reproducing the
* software by the user in light of its specific status of free software,
* that may mean that it is complicated to manipulate, and that also
* therefore means that it is reserved for developers and experienced
* professionals having in-depth computer knowledge. Users are therefore
* encouraged to load and test the software's suitability as regards their
* requirements in conditions enabling the security of their systems and/or
* data to be ensured and, more generally, to use and operate it in the
* same conditions as regards security.
* The fact that you are presently reading this means that you have had
* knowledge of the CeCILL license and that you accept its terms.
*
* ParadisEO WebSite : http://paradiseo.gforge.inria.fr
* Contact: paradiseo-help@lists.gforge.inria.fr
*
*/
//-----------------------------------------------------------------------------
#ifndef MOEOEA_H_
#define MOEOEA_H_
#include <algo/moeoPopAlgo.h>
/**
* Abstract class for multi-objective evolutionary algorithms.
*/
template < class MOEOT >
class moeoEA : public moeoPopAlgo < MOEOT >
{};
#endif /*MOEOEA_H_*/

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moeo/src/algo/moeoEasyEA.h Executable file
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/*
* <moeoEasyEA.h>
* Copyright (C) DOLPHIN Project-Team, INRIA Futurs, 2006-2008
* (C) OPAC Team, LIFL, 2002-2008
*
* Arnaud Liefooghe
*
* This software is governed by the CeCILL license under French law and
* abiding by the rules of distribution of free software. You can use,
* modify and/ or redistribute the software under the terms of the CeCILL
* license as circulated by CEA, CNRS and INRIA at the following URL
* "http://www.cecill.info".
*
* As a counterpart to the access to the source code and rights to copy,
* modify and redistribute granted by the license, users are provided only
* with a limited warranty and the software's author, the holder of the
* economic rights, and the successive licensors have only limited liability.
*
* In this respect, the user's attention is drawn to the risks associated
* with loading, using, modifying and/or developing or reproducing the
* software by the user in light of its specific status of free software,
* that may mean that it is complicated to manipulate, and that also
* therefore means that it is reserved for developers and experienced
* professionals having in-depth computer knowledge. Users are therefore
* encouraged to load and test the software's suitability as regards their
* requirements in conditions enabling the security of their systems and/or
* data to be ensured and, more generally, to use and operate it in the
* same conditions as regards security.
* The fact that you are presently reading this means that you have had
* knowledge of the CeCILL license and that you accept its terms.
*
* ParadisEO WebSite : http://paradiseo.gforge.inria.fr
* Contact: paradiseo-help@lists.gforge.inria.fr
*
*/
//-----------------------------------------------------------------------------
#ifndef _MOEOEASYEA_H
#define _MOEOEASYEA_H
#include <apply.h>
#include <eoBreed.h>
#include <eoContinue.h>
#include <eoMergeReduce.h>
#include <eoPopEvalFunc.h>
#include <eoSelect.h>
#include <eoTransform.h>
#include <algo/moeoEA.h>
#include <diversity/moeoDiversityAssignment.h>
#include <diversity/moeoDummyDiversityAssignment.h>
#include <fitness/moeoFitnessAssignment.h>
#include <replacement/moeoReplacement.h>
/**
* An easy class to design multi-objective evolutionary algorithms.
*/
template < class MOEOT >
class moeoEasyEA: public moeoEA < MOEOT >
{
public:
/**
* Ctor taking a breed.
* @param _continuator the stopping criteria
* @param _eval the evaluation functions
* @param _breed the breeder
* @param _replace the replacement strategy
* @param _fitnessEval the fitness evaluation scheme
* @param _diversityEval the diversity evaluation scheme
* @param _evalFitAndDivBeforeSelection put this parameter to 'true' if you want to re-evalue the fitness and the diversity of the population before the selection process
*/
moeoEasyEA(eoContinue < MOEOT > & _continuator, eoEvalFunc < MOEOT > & _eval, eoBreed < MOEOT > & _breed, moeoReplacement < MOEOT > & _replace, moeoFitnessAssignment < MOEOT > & _fitnessEval, moeoDiversityAssignment < MOEOT > & _diversityEval, bool _evalFitAndDivBeforeSelection = false) :
continuator(_continuator), eval (_eval), loopEval(_eval), popEval(loopEval), selectTransform(dummySelect, dummyTransform), breed(_breed), replace(_replace), fitnessEval(_fitnessEval), diversityEval(_diversityEval), evalFitAndDivBeforeSelection(_evalFitAndDivBeforeSelection)
{}
/**
* Ctor taking a breed and a popEval.
* @param _continuator the stopping criteria
* @param _popEval the evaluation functions for the whole population
* @param _breed the breeder
* @param _replace the replacement strategy
* @param _fitnessEval the fitness evaluation scheme
* @param _diversityEval the diversity evaluation scheme
* @param _evalFitAndDivBeforeSelection put this parameter to 'true' if you want to re-evalue the fitness and the diversity of the population before the selection process
*/
moeoEasyEA(eoContinue < MOEOT > & _continuator, eoPopEvalFunc < MOEOT > & _popEval, eoBreed < MOEOT > & _breed, moeoReplacement < MOEOT > & _replace, moeoFitnessAssignment < MOEOT > & _fitnessEval, moeoDiversityAssignment < MOEOT > & _diversityEval, bool _evalFitAndDivBeforeSelection = false) :
continuator(_continuator), eval(dummyEval), loopEval(dummyEval), popEval(_popEval), selectTransform(dummySelect, dummyTransform), breed(_breed), replace(_replace), fitnessEval(_fitnessEval), diversityEval(_diversityEval), evalFitAndDivBeforeSelection(_evalFitAndDivBeforeSelection)
{}
/**
* Ctor taking a select and a transform.
* @param _continuator the stopping criteria
* @param _eval the evaluation functions
* @param _select the selection scheme
* @param _transform the tranformation scheme
* @param _replace the replacement strategy
* @param _fitnessEval the fitness evaluation scheme
* @param _diversityEval the diversity evaluation scheme
* @param _evalFitAndDivBeforeSelection put this parameter to 'true' if you want to re-evalue the fitness and the diversity of the population before the selection process
*/
moeoEasyEA(eoContinue < MOEOT > & _continuator, eoEvalFunc < MOEOT > & _eval, eoSelect < MOEOT > & _select, eoTransform < MOEOT > & _transform, moeoReplacement < MOEOT > & _replace, moeoFitnessAssignment < MOEOT > & _fitnessEval, moeoDiversityAssignment < MOEOT > & _diversityEval, bool _evalFitAndDivBeforeSelection = false) :
continuator(_continuator), eval(_eval), loopEval(_eval), popEval(loopEval), selectTransform(_select, _transform), breed(selectTransform), replace(_replace), fitnessEval(_fitnessEval), diversityEval(_diversityEval), evalFitAndDivBeforeSelection(_evalFitAndDivBeforeSelection)
{}
/**
* Ctor taking a select, a transform.and a popEval
* @param _continuator the stopping criteria
* @param _popEval the evaluation functions
* @param _select the selection scheme
* @param _transform the tranformation scheme
* @param _replace the replacement strategy
* @param _fitnessEval the fitness evaluation scheme
* @param _diversityEval the diversity evaluation scheme
* @param _evalFitAndDivBeforeSelection put this parameter to 'true' if you want to re-evalue the fitness and the diversity of the population before the selection process
*/
moeoEasyEA(eoContinue < MOEOT > & _continuator, eoPopEvalFunc < MOEOT > & _popEval, eoSelect < MOEOT > & _select, eoTransform < MOEOT > & _transform, moeoReplacement < MOEOT > & _replace, moeoFitnessAssignment < MOEOT > & _fitnessEval, moeoDiversityAssignment < MOEOT > & _diversityEval, bool _evalFitAndDivBeforeSelection = false) :
continuator(_continuator), eval(dummyEval), loopEval(dummyEval), popEval(_popEval), selectTransform(_select, _transform), breed(selectTransform), replace(_replace), fitnessEval(_fitnessEval), diversityEval(_diversityEval), evalFitAndDivBeforeSelection(_evalFitAndDivBeforeSelection)
{}
/**
* Applies a few generation of evolution to the population _pop.
* @param _pop the population
*/
virtual void operator()(eoPop < MOEOT > & _pop)
{
eoPop < MOEOT > offspring, empty_pop;
popEval(empty_pop, _pop); // A first eval of pop.
bool firstTime = true;
do
{
try
{
unsigned int pSize = _pop.size();
offspring.clear(); // new offspring
// fitness and diversity assignment (if you want to or if it is the first generation)
if (evalFitAndDivBeforeSelection || firstTime)
{
firstTime = false;
//std::cout << "fitness eval" << std::endl;
fitnessEval(_pop);
//std::cout << "diversity eval" << std::endl;
diversityEval(_pop);
}
breed(_pop, offspring);
popEval(_pop, offspring); // eval of parents + offspring if necessary
replace(_pop, offspring); // after replace, the new pop. is in _pop
if (pSize > _pop.size())
{
throw std::runtime_error("Population shrinking!");
}
else if (pSize < _pop.size())
{
throw std::runtime_error("Population growing!");
}
}
catch (std::exception& e)
{
std::string s = e.what();
s.append( " in moeoEasyEA");
throw std::runtime_error( s );
}
}
while (continuator(_pop));
}
protected:
/** the stopping criteria */
eoContinue < MOEOT > & continuator;
/** a dummy eval */
class eoDummyEval : public eoEvalFunc < MOEOT >
{
public:
void operator()(MOEOT &) {}
}
dummyEval;
/** the evaluation functions */
eoEvalFunc < MOEOT > & eval;
/** to evaluate the whole population */
eoPopLoopEval < MOEOT > loopEval;
/** to evaluate the whole population */
eoPopEvalFunc < MOEOT > & popEval;
/** dummy select */
class DummySelect : public eoSelect < MOEOT >
{
public :
void operator()(const eoPop<MOEOT>&, eoPop<MOEOT>&) {}
}
dummySelect;
/** breed: a select followed by a transform */
eoSelectTransform < MOEOT > selectTransform;
/** dummy transform */
class DummyTransform : public eoTransform < MOEOT >
{
public :
void operator()(eoPop<MOEOT>&) {}
}
dummyTransform;
/** the breeder */
eoBreed < MOEOT > & breed;
/** the replacment strategy */
moeoReplacement < MOEOT > & replace;
/** the fitness assignment strategy */
moeoFitnessAssignment < MOEOT > & fitnessEval;
/** the diversity assignment strategy */
moeoDiversityAssignment < MOEOT > & diversityEval;
/** if this parameter is set to 'true', the fitness and the diversity of the whole population will be re-evaluated before the selection process */
bool evalFitAndDivBeforeSelection;
};
#endif /*MOEOEASYEA_H_*/

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/*
* <moeoIBEA.h>
* Copyright (C) DOLPHIN Project-Team, INRIA Futurs, 2006-2007
* (C) OPAC Team, LIFL, 2002-2007
*
* Arnaud Liefooghe
*
* This software is governed by the CeCILL license under French law and
* abiding by the rules of distribution of free software. You can use,
* modify and/ or redistribute the software under the terms of the CeCILL
* license as circulated by CEA, CNRS and INRIA at the following URL
* "http://www.cecill.info".
*
* As a counterpart to the access to the source code and rights to copy,
* modify and redistribute granted by the license, users are provided only
* with a limited warranty and the software's author, the holder of the
* economic rights, and the successive licensors have only limited liability.
*
* In this respect, the user's attention is drawn to the risks associated
* with loading, using, modifying and/or developing or reproducing the
* software by the user in light of its specific status of free software,
* that may mean that it is complicated to manipulate, and that also
* therefore means that it is reserved for developers and experienced
* professionals having in-depth computer knowledge. Users are therefore
* encouraged to load and test the software's suitability as regards their
* requirements in conditions enabling the security of their systems and/or
* data to be ensured and, more generally, to use and operate it in the
* same conditions as regards security.
* The fact that you are presently reading this means that you have had
* knowledge of the CeCILL license and that you accept its terms.
*
* ParadisEO WebSite : http://paradiseo.gforge.inria.fr
* Contact: paradiseo-help@lists.gforge.inria.fr
*
*/
//-----------------------------------------------------------------------------
#ifndef MOEOIBEA_H_
#define MOEOIBEA_H_
#include <eoBreed.h>
#include <eoCloneOps.h>
#include <eoContinue.h>
#include <eoEvalFunc.h>
#include <eoGenContinue.h>
#include <eoGeneralBreeder.h>
#include <eoGenOp.h>
#include <eoPopEvalFunc.h>
#include <eoSGAGenOp.h>
#include <algo/moeoEA.h>
#include <diversity/moeoDummyDiversityAssignment.h>
#include <fitness/moeoExpBinaryIndicatorBasedFitnessAssignment.h>
#include <metric/moeoNormalizedSolutionVsSolutionBinaryMetric.h>
#include <replacement/moeoEnvironmentalReplacement.h>
#include <selection/moeoDetTournamentSelect.h>
/**
* IBEA (Indicator-Based Evolutionary Algorithm).
* E. Zitzler, S. Künzli, "Indicator-Based Selection in Multiobjective Search", Proc. 8th International Conference on Parallel Problem Solving from Nature (PPSN VIII), pp. 832-842, Birmingham, UK (2004).
* This class builds the IBEA algorithm only by using the fine-grained components of the ParadisEO-MOEO framework.
*/
template < class MOEOT >
class moeoIBEA : public moeoEA < MOEOT >
{
public:
/** The type of objective vector */
typedef typename MOEOT::ObjectiveVector ObjectiveVector;
/**
* Ctor with a crossover, a mutation and their corresponding rates.
* @param _maxGen maximum number of generations before stopping
* @param _eval evaluation function
* @param _crossover crossover
* @param _pCross crossover probability
* @param _mutation mutation
* @param _pMut mutation probability
* @param _metric metric
* @param _kappa scaling factor kappa
*/
moeoIBEA (unsigned int _maxGen, eoEvalFunc < MOEOT > & _eval, eoQuadOp < MOEOT > & _crossover, double _pCross, eoMonOp < MOEOT > & _mutation, double _pMut, moeoNormalizedSolutionVsSolutionBinaryMetric < ObjectiveVector, double > & _metric, const double _kappa=0.05) :
defaultGenContinuator(_maxGen), continuator(defaultGenContinuator), eval(_eval), defaultPopEval(_eval), popEval(defaultPopEval), select (2), selectMany(select,0.0), selectTransform(defaultSelect, defaultTransform), defaultSGAGenOp(_crossover, _pCross, _mutation, _pMut), genBreed (select, defaultSGAGenOp), breed (genBreed), fitnessAssignment(_metric, _kappa), replace (fitnessAssignment, diversityAssignment)
{}
/**
* Ctor with a eoContinue and a eoGenOp.
* @param _continuator stopping criteria
* @param _eval evaluation function
* @param _op variation operators
* @param _metric metric
* @param _kappa scaling factor kappa
*/
moeoIBEA (eoContinue < MOEOT > & _continuator, eoEvalFunc < MOEOT > & _eval, eoGenOp < MOEOT > & _op, moeoNormalizedSolutionVsSolutionBinaryMetric < ObjectiveVector, double > & _metric, const double _kappa=0.05) :
defaultGenContinuator(0), continuator(_continuator), eval(_eval), defaultPopEval(_eval), popEval(defaultPopEval), select(2),
selectMany(select,0.0), selectTransform(defaultSelect, defaultTransform), defaultSGAGenOp(defaultQuadOp, 1.0, defaultMonOp, 1.0), genBreed(select, _op), breed(genBreed), fitnessAssignment(_metric, _kappa), replace (fitnessAssignment, diversityAssignment)
{}
/**
* Ctor with a eoContinue, a eoPopEval and a eoGenOp.
* @param _continuator stopping criteria
* @param _popEval population evaluation function
* @param _op variation operators
* @param _metric metric
* @param _kappa scaling factor kappa
*/
moeoIBEA (eoContinue < MOEOT > & _continuator, eoPopEvalFunc < MOEOT > & _popEval, eoGenOp < MOEOT > & _op, moeoNormalizedSolutionVsSolutionBinaryMetric < ObjectiveVector, double > & _metric, const double _kappa=0.05) :
defaultGenContinuator(0), continuator(_continuator), eval(defaultEval), defaultPopEval(eval), popEval(_popEval), select(2),
selectMany(select,0.0), selectTransform(defaultSelect, defaultTransform), defaultSGAGenOp(defaultQuadOp, 1.0, defaultMonOp, 1.0), genBreed(select, _op), breed(genBreed), fitnessAssignment(_metric, _kappa), replace (fitnessAssignment, diversityAssignment)
{}
/**
* Ctor with a eoContinue and a eoTransform.
* @param _continuator stopping criteria
* @param _eval evaluation function
* @param _transform variation operator
* @param _metric metric
* @param _kappa scaling factor kappa
*/
moeoIBEA (eoContinue < MOEOT > & _continuator, eoEvalFunc < MOEOT > & _eval, eoTransform < MOEOT > & _transform, moeoNormalizedSolutionVsSolutionBinaryMetric < ObjectiveVector, double > & _metric, const double _kappa=0.05) :
defaultGenContinuator(0), continuator(_continuator), eval(_eval), defaultPopEval(_eval), popEval(defaultPopEval),
select(2), selectMany(select, 1.0), selectTransform(selectMany, _transform), defaultSGAGenOp(defaultQuadOp, 0.0, defaultMonOp, 0.0), genBreed(select, defaultSGAGenOp), breed(selectTransform), fitnessAssignment(_metric, _kappa), replace(fitnessAssignment, diversityAssignment)
{}
/**
* Ctor with a eoContinue, a eoPopEval and a eoTransform.
* @param _continuator stopping criteria
* @param _popEval population evaluation function
* @param _transform variation operator
* @param _metric metric
* @param _kappa scaling factor kappa
*/
moeoIBEA (eoContinue < MOEOT > & _continuator, eoPopEvalFunc < MOEOT > & _popEval, eoTransform < MOEOT > & _transform, moeoNormalizedSolutionVsSolutionBinaryMetric < ObjectiveVector, double > & _metric, const double _kappa=0.05) :
defaultGenContinuator(0), continuator(_continuator), eval(defaultEval), defaultPopEval(eval), popEval(_popEval),
select(2), selectMany(select, 1.0), selectTransform(selectMany, _transform), defaultSGAGenOp(defaultQuadOp, 0.0, defaultMonOp, 0.0), genBreed(select, defaultSGAGenOp), breed(selectTransform), fitnessAssignment(_metric, _kappa), replace(fitnessAssignment, diversityAssignment)
{}
/**
* Apply the algorithm to the population _pop until the stopping criteria is satified.
* @param _pop the population
*/
virtual void operator () (eoPop < MOEOT > &_pop)
{
eoPop < MOEOT > offspring, empty_pop;
popEval (empty_pop, _pop); // a first eval of _pop
// evaluate fitness and diversity
fitnessAssignment(_pop);
diversityAssignment(_pop);
do
{
// generate offspring, worths are recalculated if necessary
breed (_pop, offspring);
// eval of offspring
popEval (_pop, offspring);
// after replace, the new pop is in _pop. Worths are recalculated if necessary
replace (_pop, offspring);
}
while (continuator (_pop));
}
protected:
/** a continuator based on the number of generations (used as default) */
eoGenContinue < MOEOT > defaultGenContinuator;
/** stopping criteria */
eoContinue < MOEOT > & continuator;
/** default eval */
class DummyEval : public eoEvalFunc < MOEOT >
{
public:
void operator()(MOEOT &) {}
}
defaultEval;
/** evaluation function */
eoEvalFunc < MOEOT > & eval;
/** default popEval */
eoPopLoopEval < MOEOT > defaultPopEval;
/** evaluation function used to evaluate the whole population */
eoPopEvalFunc < MOEOT > & popEval;
/** default select */
class DummySelect : public eoSelect < MOEOT >
{
public :
void operator()(const eoPop<MOEOT>&, eoPop<MOEOT>&) {}
}
defaultSelect;
/** binary tournament selection */
moeoDetTournamentSelect < MOEOT > select;
/** default select many */
eoSelectMany < MOEOT > selectMany;
/** select transform */
eoSelectTransform < MOEOT > selectTransform;
/** a default crossover */
eoQuadCloneOp < MOEOT > defaultQuadOp;
/** a default mutation */
eoMonCloneOp < MOEOT > defaultMonOp;
/** an object for genetic operators (used as default) */
eoSGAGenOp < MOEOT > defaultSGAGenOp;
/** default transform */
class DummyTransform : public eoTransform < MOEOT >
{
public :
void operator()(eoPop<MOEOT>&) {}
}
defaultTransform;
/** general breeder */
eoGeneralBreeder < MOEOT > genBreed;
/** breeder */
eoBreed < MOEOT > & breed;
/** fitness assignment used in IBEA */
moeoExpBinaryIndicatorBasedFitnessAssignment < MOEOT > fitnessAssignment;
/** dummy diversity assignment */
moeoDummyDiversityAssignment < MOEOT > diversityAssignment;
/** environmental replacement */
moeoEnvironmentalReplacement < MOEOT > replace;
};
#endif /*MOEOIBEA_H_*/

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/*
* <moeoNSGA.h>
* Copyright (C) DOLPHIN Project-Team, INRIA Futurs, 2006-2008
* (C) OPAC Team, LIFL, 2002-2008
*
* Arnaud Liefooghe
* Jérémie Humeau
*
* This software is governed by the CeCILL license under French law and
* abiding by the rules of distribution of free software. You can use,
* modify and/ or redistribute the software under the terms of the CeCILL
* license as circulated by CEA, CNRS and INRIA at the following URL
* "http://www.cecill.info".
*
* As a counterpart to the access to the source code and rights to copy,
* modify and redistribute granted by the license, users are provided only
* with a limited warranty and the software's author, the holder of the
* economic rights, and the successive licensors have only limited liability.
*
* In this respect, the user's attention is drawn to the risks associated
* with loading, using, modifying and/or developing or reproducing the
* software by the user in light of its specific status of free software,
* that may mean that it is complicated to manipulate, and that also
* therefore means that it is reserved for developers and experienced
* professionals having in-depth computer knowledge. Users are therefore
* encouraged to load and test the software's suitability as regards their
* requirements in conditions enabling the security of their systems and/or
* data to be ensured and, more generally, to use and operate it in the
* same conditions as regards security.
* The fact that you are presently reading this means that you have had
* knowledge of the CeCILL license and that you accept its terms.
*
* ParadisEO WebSite : http://paradiseo.gforge.inria.fr
* Contact: paradiseo-help@lists.gforge.inria.fr
*
*/
//-----------------------------------------------------------------------------
#ifndef MOEOMOGA_H_
#define MOEOMOGA_H_
#include <eoBreed.h>
#include <eoContinue.h>
#include <eoEvalFunc.h>
#include <eoGenContinue.h>
#include <eoGeneralBreeder.h>
#include <eoGenOp.h>
#include <eoPopEvalFunc.h>
#include <eoSGAGenOp.h>
#include <algo/moeoEA.h>
#include <diversity/moeoFrontByFrontSharingDiversityAssignment.h>
#include <fitness/moeoDominanceRankFitnessAssignment.h>
#include <replacement/moeoElitistReplacement.h>
#include <selection/moeoDetTournamentSelect.h>
/**
* MOGA.
*/
template < class MOEOT >
class moeoMOGA: public moeoEA < MOEOT >
{
public:
/**
* Ctor with a crossover, a mutation and their corresponding rates.
* @param _maxGen maximum number of generations before stopping
* @param _eval evaluation function
* @param _crossover crossover
* @param _pCross crossover probability
* @param _mutation mutation
* @param _pMut mutation probability
* @param _nicheSize niche size
*/
moeoMOGA (unsigned int _maxGen, eoEvalFunc < MOEOT > & _eval, eoQuadOp < MOEOT > & _crossover, double _pCross, eoMonOp < MOEOT > & _mutation, double _pMut, double _nicheSize = 0.5) :
defaultGenContinuator(_maxGen), continuator(defaultGenContinuator), eval(_eval), defaultPopEval(_eval), popEval(defaultPopEval), select (2), selectMany(select,0.0), selectTransform(defaultSelect, defaultTransform), defaultSGAGenOp(_crossover, _pCross, _mutation, _pMut), genBreed (select, defaultSGAGenOp), breed (genBreed), diversityAssignment(_nicheSize), replace (fitnessAssignment, diversityAssignment)
{}
/**
* Ctor with a eoContinue and a eoGenOp.
* @param _continuator stopping criteria
* @param _eval evaluation function
* @param _op variation operators
* @param _nicheSize niche size
*/
moeoMOGA (eoContinue < MOEOT > & _continuator, eoEvalFunc < MOEOT > & _eval, eoGenOp < MOEOT > & _op, double _nicheSize = 0.5) :
defaultGenContinuator(0), continuator(_continuator), eval(_eval), defaultPopEval(_eval), popEval(defaultPopEval), select(2),
selectMany(select,0.0), selectTransform(defaultSelect, defaultTransform), defaultSGAGenOp(defaultQuadOp, 1.0, defaultMonOp, 1.0), genBreed(select, _op), breed(genBreed), diversityAssignment(_nicheSize), replace (fitnessAssignment, diversityAssignment)
{}
/**
* Ctor with a eoContinue, a eoPopEval and a eoGenOp.
* @param _continuator stopping criteria
* @param _popEval population evaluation function
* @param _op variation operators
* @param _nicheSize niche size
*/
moeoMOGA (eoContinue < MOEOT > & _continuator, eoPopEvalFunc < MOEOT > & _popEval, eoGenOp < MOEOT > & _op, double _nicheSize = 0.5) :
defaultGenContinuator(0), continuator(_continuator), eval(defaultEval), defaultPopEval(eval), popEval(_popEval), select(2),
selectMany(select,0.0), selectTransform(defaultSelect, defaultTransform), defaultSGAGenOp(defaultQuadOp, 1.0, defaultMonOp, 1.0), genBreed(select, _op), breed(genBreed), diversityAssignment(_nicheSize), replace (fitnessAssignment, diversityAssignment)
{}
/**
* Ctor with a eoContinue and a eoTransform.
* @param _continuator stopping criteria
* @param _eval evaluation function
* @param _transform variation operator
* @param _nicheSize niche size
*/
moeoMOGA (eoContinue < MOEOT > & _continuator, eoEvalFunc < MOEOT > & _eval, eoTransform < MOEOT > & _transform, double _nicheSize = 0.5) :
defaultGenContinuator(0), continuator(_continuator), eval(_eval), defaultPopEval(_eval), popEval(defaultPopEval),
select(2), selectMany(select, 1.0), selectTransform(selectMany, _transform), defaultSGAGenOp(defaultQuadOp, 0.0, defaultMonOp, 0.0), genBreed(select, defaultSGAGenOp), breed(selectTransform), diversityAssignment(_nicheSize), replace(fitnessAssignment, diversityAssignment)
{}
/**
* Ctor with a eoContinue, a eoPopEval and a eoTransform.
* @param _continuator stopping criteria
* @param _popEval population evaluation function
* @param _transform variation operator
* @param _nicheSize niche size
*/
moeoMOGA (eoContinue < MOEOT > & _continuator, eoPopEvalFunc < MOEOT > & _popEval, eoTransform < MOEOT > & _transform, double _nicheSize = 0.5) :
defaultGenContinuator(0), continuator(_continuator), eval(defaultEval), defaultPopEval(eval), popEval(_popEval),
select(2), selectMany(select, 1.0), selectTransform(selectMany, _transform), defaultSGAGenOp(defaultQuadOp, 0.0, defaultMonOp, 0.0), genBreed(select, defaultSGAGenOp), breed(selectTransform), diversityAssignment(_nicheSize), replace(fitnessAssignment, diversityAssignment)
{}
/**
* Apply the algorithm to the population _pop until the stopping criteria is satified.
* @param _pop the population
*/
virtual void operator () (eoPop < MOEOT > &_pop)
{
eoPop < MOEOT > offspring, empty_pop;
popEval (empty_pop, _pop); // a first eval of _pop
// evaluate fitness and diversity
fitnessAssignment(_pop);
diversityAssignment(_pop);
do
{
// generate offspring, worths are recalculated if necessary
breed (_pop, offspring);
// eval of offspring
popEval (_pop, offspring);
// after replace, the new pop is in _pop. Worths are recalculated if necessary
replace (_pop, offspring);
}
while (continuator (_pop));
}
protected:
/** a continuator based on the number of generations (used as default) */
eoGenContinue < MOEOT > defaultGenContinuator;
/** stopping criteria */
eoContinue < MOEOT > & continuator;
/** default eval */
class DummyEval : public eoEvalFunc < MOEOT >
{
public:
void operator()(MOEOT &) {}
}
defaultEval;
/** evaluation function */
eoEvalFunc < MOEOT > & eval;
/** default popEval */
eoPopLoopEval < MOEOT > defaultPopEval;
/** evaluation function used to evaluate the whole population */
eoPopEvalFunc < MOEOT > & popEval;
/** default select */
class DummySelect : public eoSelect < MOEOT >
{
public :
void operator()(const eoPop<MOEOT>&, eoPop<MOEOT>&) {}
}
defaultSelect;
/** binary tournament selection */
moeoDetTournamentSelect < MOEOT > select;
/** default select many */
eoSelectMany < MOEOT > selectMany;
/** select transform */
eoSelectTransform < MOEOT > selectTransform;
/** a default crossover */
eoQuadCloneOp < MOEOT > defaultQuadOp;
/** a default mutation */
eoMonCloneOp < MOEOT > defaultMonOp;
/** an object for genetic operators (used as default) */
eoSGAGenOp < MOEOT > defaultSGAGenOp;
/** default transform */
class DummyTransform : public eoTransform < MOEOT >
{
public :
void operator()(eoPop<MOEOT>&) {}
}
defaultTransform;
/** general breeder */
eoGeneralBreeder < MOEOT > genBreed;
/** breeder */
eoBreed < MOEOT > & breed;
/** fitness assignment used in NSGA-II */
moeoDominanceRankFitnessAssignment < MOEOT > fitnessAssignment;
/** diversity assignment used in NSGA-II */
moeoFrontByFrontSharingDiversityAssignment < MOEOT > diversityAssignment;
/** elitist replacement */
moeoElitistReplacement < MOEOT > replace;
};
#endif /*MOEOMOGA_H_*/

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/*
* <moeoNSGA.h>
* Copyright (C) DOLPHIN Project-Team, INRIA Futurs, 2006-2008
* (C) OPAC Team, LIFL, 2002-2008
*
* Arnaud Liefooghe
*
* This software is governed by the CeCILL license under French law and
* abiding by the rules of distribution of free software. You can use,
* modify and/ or redistribute the software under the terms of the CeCILL
* license as circulated by CEA, CNRS and INRIA at the following URL
* "http://www.cecill.info".
*
* As a counterpart to the access to the source code and rights to copy,
* modify and redistribute granted by the license, users are provided only
* with a limited warranty and the software's author, the holder of the
* economic rights, and the successive licensors have only limited liability.
*
* In this respect, the user's attention is drawn to the risks associated
* with loading, using, modifying and/or developing or reproducing the
* software by the user in light of its specific status of free software,
* that may mean that it is complicated to manipulate, and that also
* therefore means that it is reserved for developers and experienced
* professionals having in-depth computer knowledge. Users are therefore
* encouraged to load and test the software's suitability as regards their
* requirements in conditions enabling the security of their systems and/or
* data to be ensured and, more generally, to use and operate it in the
* same conditions as regards security.
* The fact that you are presently reading this means that you have had
* knowledge of the CeCILL license and that you accept its terms.
*
* ParadisEO WebSite : http://paradiseo.gforge.inria.fr
* Contact: paradiseo-help@lists.gforge.inria.fr
*
*/
//-----------------------------------------------------------------------------
#ifndef MOEONSGA_H_
#define MOEONSGA_H_
#include <eoBreed.h>
#include <eoContinue.h>
#include <eoEvalFunc.h>
#include <eoGenContinue.h>
#include <eoGeneralBreeder.h>
#include <eoGenOp.h>
#include <eoPopEvalFunc.h>
#include <eoSGAGenOp.h>
#include <algo/moeoEA.h>
#include <diversity/moeoFrontByFrontSharingDiversityAssignment.h>
#include <fitness/moeoDominanceDepthFitnessAssignment.h>
#include <replacement/moeoElitistReplacement.h>
#include <selection/moeoDetTournamentSelect.h>
/**
* NSGA (Non-dominated Sorting Genetic Algorithm).
* N. Srinivas, K. Deb, "Multiobjective Optimization Using Nondominated Sorting in Genetic Algorithms".
* Evolutionary Computation, Vol. 2(3), No 2, pp. 221-248 (1994).
* This class builds the NSGA algorithm only by using the fine-grained components of the ParadisEO-MOEO framework.
*/
template < class MOEOT >
class moeoNSGA: public moeoEA < MOEOT >
{
public:
/**
* Ctor with a crossover, a mutation and their corresponding rates.
* @param _maxGen maximum number of generations before stopping
* @param _eval evaluation function
* @param _crossover crossover
* @param _pCross crossover probability
* @param _mutation mutation
* @param _pMut mutation probability
* @param _nicheSize niche size
*/
moeoNSGA (unsigned int _maxGen, eoEvalFunc < MOEOT > & _eval, eoQuadOp < MOEOT > & _crossover, double _pCross, eoMonOp < MOEOT > & _mutation, double _pMut, double _nicheSize = 0.5) :
defaultGenContinuator(_maxGen), continuator(defaultGenContinuator), eval(_eval), defaultPopEval(_eval), popEval(defaultPopEval), select (2), selectMany(select,0.0), selectTransform(defaultSelect, defaultTransform), defaultSGAGenOp(_crossover, _pCross, _mutation, _pMut), genBreed (select, defaultSGAGenOp), breed (genBreed), diversityAssignment(_nicheSize), replace (fitnessAssignment, diversityAssignment)
{}
/**
* Ctor with a eoContinue and a eoGenOp.
* @param _continuator stopping criteria
* @param _eval evaluation function
* @param _op variation operators
* @param _nicheSize niche size
*/
moeoNSGA (eoContinue < MOEOT > & _continuator, eoEvalFunc < MOEOT > & _eval, eoGenOp < MOEOT > & _op, double _nicheSize = 0.5) :
defaultGenContinuator(0), continuator(_continuator), eval(_eval), defaultPopEval(_eval), popEval(defaultPopEval), select(2),
selectMany(select,0.0), selectTransform(defaultSelect, defaultTransform), defaultSGAGenOp(defaultQuadOp, 1.0, defaultMonOp, 1.0), genBreed(select, _op), breed(genBreed), diversityAssignment(_nicheSize), replace (fitnessAssignment, diversityAssignment)
{}
/**
* Ctor with a eoContinue, a eoPopEval and a eoGenOp.
* @param _continuator stopping criteria
* @param _popEval population evaluation function
* @param _op variation operators
* @param _nicheSize niche size
*/
moeoNSGA (eoContinue < MOEOT > & _continuator, eoPopEvalFunc < MOEOT > & _popEval, eoGenOp < MOEOT > & _op, double _nicheSize = 0.5) :
defaultGenContinuator(0), continuator(_continuator), eval(defaultEval), defaultPopEval(eval), popEval(_popEval), select(2),
selectMany(select,0.0), selectTransform(defaultSelect, defaultTransform), defaultSGAGenOp(defaultQuadOp, 1.0, defaultMonOp, 1.0), genBreed(select, _op), breed(genBreed), diversityAssignment(_nicheSize), replace (fitnessAssignment, diversityAssignment)
{}
/**
* Ctor with a eoContinue and a eoTransform.
* @param _continuator stopping criteria
* @param _eval evaluation function
* @param _transform variation operator
* @param _nicheSize niche size
*/
moeoNSGA (eoContinue < MOEOT > & _continuator, eoEvalFunc < MOEOT > & _eval, eoTransform < MOEOT > & _transform, double _nicheSize = 0.5) :
defaultGenContinuator(0), continuator(_continuator), eval(_eval), defaultPopEval(_eval), popEval(defaultPopEval),
select(2), selectMany(select, 1.0), selectTransform(selectMany, _transform), defaultSGAGenOp(defaultQuadOp, 0.0, defaultMonOp, 0.0), genBreed(select, defaultSGAGenOp), breed(selectTransform), diversityAssignment(_nicheSize), replace(fitnessAssignment, diversityAssignment)
{}
/**
* Ctor with a eoContinue, a eoPopEval and a eoTransform.
* @param _continuator stopping criteria
* @param _popEval population evaluation function
* @param _transform variation operator
* @param _nicheSize niche size
*/
moeoNSGA (eoContinue < MOEOT > & _continuator, eoPopEvalFunc < MOEOT > & _popEval, eoTransform < MOEOT > & _transform, double _nicheSize = 0.5) :
defaultGenContinuator(0), continuator(_continuator), eval(defaultEval), defaultPopEval(eval), popEval(_popEval),
select(2), selectMany(select, 1.0), selectTransform(selectMany, _transform), defaultSGAGenOp(defaultQuadOp, 0.0, defaultMonOp, 0.0), genBreed(select, defaultSGAGenOp), breed(selectTransform), diversityAssignment(_nicheSize), replace(fitnessAssignment, diversityAssignment)
{}
/**
* Apply the algorithm to the population _pop until the stopping criteria is satified.
* @param _pop the population
*/
virtual void operator () (eoPop < MOEOT > &_pop)
{
eoPop < MOEOT > offspring, empty_pop;
popEval (empty_pop, _pop); // a first eval of _pop
// evaluate fitness and diversity
fitnessAssignment(_pop);
diversityAssignment(_pop);
do
{
// generate offspring, worths are recalculated if necessary
breed (_pop, offspring);
// eval of offspring
popEval (_pop, offspring);
// after replace, the new pop is in _pop. Worths are recalculated if necessary
replace (_pop, offspring);
}
while (continuator (_pop));
}
protected:
/** a continuator based on the number of generations (used as default) */
eoGenContinue < MOEOT > defaultGenContinuator;
/** stopping criteria */
eoContinue < MOEOT > & continuator;
/** default eval */
class DummyEval : public eoEvalFunc < MOEOT >
{
public:
void operator()(MOEOT &) {}
}
defaultEval;
/** evaluation function */
eoEvalFunc < MOEOT > & eval;
/** default popEval */
eoPopLoopEval < MOEOT > defaultPopEval;
/** evaluation function used to evaluate the whole population */
eoPopEvalFunc < MOEOT > & popEval;
/** default select */
class DummySelect : public eoSelect < MOEOT >
{
public :
void operator()(const eoPop<MOEOT>&, eoPop<MOEOT>&) {}
}
defaultSelect;
/** binary tournament selection */
moeoDetTournamentSelect < MOEOT > select;
/** default select many */
eoSelectMany < MOEOT > selectMany;
/** select transform */
eoSelectTransform < MOEOT > selectTransform;
/** a default crossover */
eoQuadCloneOp < MOEOT > defaultQuadOp;
/** a default mutation */
eoMonCloneOp < MOEOT > defaultMonOp;
/** an object for genetic operators (used as default) */
eoSGAGenOp < MOEOT > defaultSGAGenOp;
/** default transform */
class DummyTransform : public eoTransform < MOEOT >
{
public :
void operator()(eoPop<MOEOT>&) {}
}
defaultTransform;
/** general breeder */
eoGeneralBreeder < MOEOT > genBreed;
/** breeder */
eoBreed < MOEOT > & breed;
/** fitness assignment used in NSGA-II */
moeoDominanceDepthFitnessAssignment < MOEOT > fitnessAssignment;
/** diversity assignment used in NSGA-II */
moeoFrontByFrontSharingDiversityAssignment < MOEOT > diversityAssignment;
/** elitist replacement */
moeoElitistReplacement < MOEOT > replace;
};
#endif /*MOEONSGA_H_*/

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/*
* <moeoNSGAII.h>
* Copyright (C) DOLPHIN Project-Team, INRIA Futurs, 2006-2008
* (C) OPAC Team, LIFL, 2002-2008
*
* Arnaud Liefooghe
*
* This software is governed by the CeCILL license under French law and
* abiding by the rules of distribution of free software. You can use,
* modify and/ or redistribute the software under the terms of the CeCILL
* license as circulated by CEA, CNRS and INRIA at the following URL
* "http://www.cecill.info".
*
* As a counterpart to the access to the source code and rights to copy,
* modify and redistribute granted by the license, users are provided only
* with a limited warranty and the software's author, the holder of the
* economic rights, and the successive licensors have only limited liability.
*
* In this respect, the user's attention is drawn to the risks associated
* with loading, using, modifying and/or developing or reproducing the
* software by the user in light of its specific status of free software,
* that may mean that it is complicated to manipulate, and that also
* therefore means that it is reserved for developers and experienced
* professionals having in-depth computer knowledge. Users are therefore
* encouraged to load and test the software's suitability as regards their
* requirements in conditions enabling the security of their systems and/or
* data to be ensured and, more generally, to use and operate it in the
* same conditions as regards security.
* The fact that you are presently reading this means that you have had
* knowledge of the CeCILL license and that you accept its terms.
*
* ParadisEO WebSite : http://paradiseo.gforge.inria.fr
* Contact: paradiseo-help@lists.gforge.inria.fr
*
*/
//-----------------------------------------------------------------------------
#ifndef MOEONSGAII_H_
#define MOEONSGAII_H_
#include <eoBreed.h>
#include <eoCloneOps.h>
#include <eoContinue.h>
#include <eoEvalFunc.h>
#include <eoGenContinue.h>
#include <eoGeneralBreeder.h>
#include <eoGenOp.h>
#include <eoPopEvalFunc.h>
#include <eoSGAGenOp.h>
#include <algo/moeoEA.h>
#include <diversity/moeoFrontByFrontCrowdingDiversityAssignment.h>
#include <fitness/moeoDominanceDepthFitnessAssignment.h>
#include <replacement/moeoElitistReplacement.h>
#include <selection/moeoDetTournamentSelect.h>
/**
* NSGA-II (Non-dominated Sorting Genetic Algorithm II).
* Deb, K., S. Agrawal, A. Pratap, and T. Meyarivan. A fast elitist non-dominated sorting genetic algorithm for multi-objective optimization: NSGA-II. IEEE Transactions on Evolutionary Computation, Vol. 6, No 2, pp 182-197 (2002).
* This class builds the NSGA-II algorithm only by using the fine-grained components of the ParadisEO-MOEO framework.
*/
template < class MOEOT >
class moeoNSGAII: public moeoEA < MOEOT >
{
public:
/**
* Ctor with a crossover, a mutation and their corresponding rates.
* @param _maxGen maximum number of generations before stopping
* @param _eval evaluation function
* @param _crossover crossover
* @param _pCross crossover probability
* @param _mutation mutation
* @param _pMut mutation probability
*/
moeoNSGAII (unsigned int _maxGen, eoEvalFunc < MOEOT > & _eval, eoQuadOp < MOEOT > & _crossover, double _pCross, eoMonOp < MOEOT > & _mutation, double _pMut) :
defaultGenContinuator(_maxGen), continuator(defaultGenContinuator), eval(_eval), defaultPopEval(_eval), popEval(defaultPopEval), select (2), selectMany(select,0.0), selectTransform(defaultSelect, defaultTransform), defaultSGAGenOp(_crossover, _pCross, _mutation, _pMut), genBreed (select, defaultSGAGenOp), breed (genBreed), replace (fitnessAssignment, diversityAssignment)
{}
/**
* Ctor with a eoContinue and a eoGenOp.
* @param _continuator stopping criteria
* @param _eval evaluation function
* @param _op variation operators
*/
moeoNSGAII (eoContinue < MOEOT > & _continuator, eoEvalFunc < MOEOT > & _eval, eoGenOp < MOEOT > & _op) :
defaultGenContinuator(0), continuator(_continuator), eval(_eval), defaultPopEval(_eval), popEval(defaultPopEval), select(2),
selectMany(select,0.0), selectTransform(defaultSelect, defaultTransform), defaultSGAGenOp(defaultQuadOp, 1.0, defaultMonOp, 1.0), genBreed(select, _op), breed(genBreed), replace (fitnessAssignment, diversityAssignment)
{}
/**
* Ctor with a eoContinue, a eoPopEval and a eoGenOp.
* @param _continuator stopping criteria
* @param _popEval population evaluation function
* @param _op variation operators
*/
moeoNSGAII (eoContinue < MOEOT > & _continuator, eoPopEvalFunc < MOEOT > & _popEval, eoGenOp < MOEOT > & _op) :
defaultGenContinuator(0), continuator(_continuator), eval(defaultEval), defaultPopEval(eval), popEval(_popEval), select(2),
selectMany(select,0.0), selectTransform(defaultSelect, defaultTransform), defaultSGAGenOp(defaultQuadOp, 1.0, defaultMonOp, 1.0), genBreed(select, _op), breed(genBreed), replace (fitnessAssignment, diversityAssignment)
{}
/**
* Ctor with a eoContinue and a eoTransform.
* @param _continuator stopping criteria
* @param _eval evaluation function
* @param _transform variation operator
*/
moeoNSGAII (eoContinue < MOEOT > & _continuator, eoEvalFunc < MOEOT > & _eval, eoTransform < MOEOT > & _transform) :
defaultGenContinuator(0), continuator(_continuator), eval(_eval), defaultPopEval(_eval), popEval(defaultPopEval),
select(2), selectMany(select, 1.0), selectTransform(selectMany, _transform), defaultSGAGenOp(defaultQuadOp, 0.0, defaultMonOp, 0.0), genBreed(select, defaultSGAGenOp), breed(selectTransform), replace(fitnessAssignment, diversityAssignment)
{}
/**
* Ctor with a eoContinue, a eoPopEval and a eoTransform.
* @param _continuator stopping criteria
* @param _popEval population evaluation function
* @param _transform variation operator
*/
moeoNSGAII (eoContinue < MOEOT > & _continuator, eoPopEvalFunc < MOEOT > & _popEval, eoTransform < MOEOT > & _transform) :
defaultGenContinuator(0), continuator(_continuator), eval(defaultEval), defaultPopEval(eval), popEval(_popEval),
select(2), selectMany(select, 1.0), selectTransform(selectMany, _transform), defaultSGAGenOp(defaultQuadOp, 0.0, defaultMonOp, 0.0), genBreed(select, defaultSGAGenOp), breed(selectTransform), replace(fitnessAssignment, diversityAssignment)
{}
/**
* Apply a the algorithm to the population _pop until the stopping criteria is satified.
* @param _pop the population
*/
virtual void operator () (eoPop < MOEOT > &_pop)
{
eoPop < MOEOT > offspring, empty_pop;
popEval (empty_pop, _pop); // a first eval of _pop
// evaluate fitness and diversity
fitnessAssignment(_pop);
diversityAssignment(_pop);
do
{
// generate offspring, worths are recalculated if necessary
breed (_pop, offspring);
// eval of offspring
popEval (_pop, offspring);
// after replace, the new pop is in _pop. Worths are recalculated if necessary
replace (_pop, offspring);
}
while (continuator (_pop));
}
protected:
/** a continuator based on the number of generations (used as default) */
eoGenContinue < MOEOT > defaultGenContinuator;
/** stopping criteria */
eoContinue < MOEOT > & continuator;
/** default eval */
class DummyEval : public eoEvalFunc < MOEOT >
{
public:
void operator()(MOEOT &) {}
}
defaultEval;
/** evaluation function */
eoEvalFunc < MOEOT > & eval;
/** default popEval */
eoPopLoopEval < MOEOT > defaultPopEval;
/** evaluation function used to evaluate the whole population */
eoPopEvalFunc < MOEOT > & popEval;
/** default select */
class DummySelect : public eoSelect < MOEOT >
{
public :
void operator()(const eoPop<MOEOT>&, eoPop<MOEOT>&) {}
}
defaultSelect;
/** binary tournament selection */
moeoDetTournamentSelect < MOEOT > select;
/** default select many */
eoSelectMany < MOEOT > selectMany;
/** select transform */
eoSelectTransform < MOEOT > selectTransform;
/** a default crossover */
eoQuadCloneOp < MOEOT > defaultQuadOp;
/** a default mutation */
eoMonCloneOp < MOEOT > defaultMonOp;
/** an object for genetic operators (used as default) */
eoSGAGenOp < MOEOT > defaultSGAGenOp;
/** default transform */
class DummyTransform : public eoTransform < MOEOT >
{
public :
void operator()(eoPop<MOEOT>&) {}
}
defaultTransform;
/** general breeder */
eoGeneralBreeder < MOEOT > genBreed;
/** breeder */
eoBreed < MOEOT > & breed;
/** fitness assignment used in NSGA */
moeoDominanceDepthFitnessAssignment < MOEOT > fitnessAssignment;
/** diversity assignment used in NSGA-II */
moeoFrontByFrontCrowdingDiversityAssignment < MOEOT > diversityAssignment;
/** elitist replacement */
moeoElitistReplacement < MOEOT > replace;
};
#endif /*MOEONSGAII_H_*/

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/*
* <moeoPLS1.h>
* Copyright (C) DOLPHIN Project-Team, INRIA Futurs, 2006-2008
* (C) OPAC Team, LIFL, 2002-2008
*
* Arnaud Liefooghe
* Jérémie Humeau
*
* This software is governed by the CeCILL license under French law and
* abiding by the rules of distribution of free software. You can use,
* modify and/ or redistribute the software under the terms of the CeCILL
* license as circulated by CEA, CNRS and INRIA at the following URL
* "http://www.cecill.info".
*
* As a counterpart to the access to the source code and rights to copy,
* modify and redistribute granted by the license, users are provided only
* with a limited warranty and the software's author, the holder of the
* economic rights, and the successive licensors have only limited liability.
*
* In this respect, the user's attention is drawn to the risks associated
* with loading, using, modifying and/or developing or reproducing the
* software by the user in light of its specific status of free software,
* that may mean that it is complicated to manipulate, and that also
* therefore means that it is reserved for developers and experienced
* professionals having in-depth computer knowledge. Users are therefore
* encouraged to load and test the software's suitability as regards their
* requirements in conditions enabling the security of their systems and/or
* data to be ensured and, more generally, to use and operate it in the
* same conditions as regards security.
* The fact that you are presently reading this means that you have had
* knowledge of the CeCILL license and that you accept its terms.
*
* ParadisEO WebSite : http://paradiseo.gforge.inria.fr
* Contact: paradiseo-help@lists.gforge.inria.fr
*
*/
//-----------------------------------------------------------------------------
#ifndef _MOEOPLS1_H
#define _MOEOPLS1_H
#include <algo/moeoUnifiedDominanceBasedLS.h>
#include <selection/moeoNumberUnvisitedSelect.h>
#include <explorer/moeoExhaustiveNeighborhoodExplorer.h>
/**
* PLS1 algorithm
*
* Paquete L, Chiarandini M, St ̈ tzle T (2004) Pareto local optimum sets in the biobjective
* traveling salesman problem: An experimental study. In: Metaheuristics for Multiobjective
* Optimisation, Lecture Notes in Economics and Mathematical Systems, vol 535, Springer-
* Verlag, Berlin, Germany, chap 7, pp 177–199
*/
template < class Neighbor >
class moeoPLS1 : public moeoUnifiedDominanceBasedLS < Neighbor >
{
public:
/** Alias for the type */
typedef typename Neighbor::EOT MOEOT;
typedef typename MOEOT::ObjectiveVector ObjectiveVector;
/**
* Ctor
* @param _continuator a stop creterion
* @param _eval a evaluation function
* @param _archive a archive to store no-dominated individuals
* @param _neighborhood a neighborhood
* @param _incrEval neighbor evaluation function
*/
moeoPLS1(
eoContinue < MOEOT > & _continuator,
eoEvalFunc < MOEOT > & _eval,
moeoArchive < MOEOT > & _archive,
moNeighborhood<Neighbor>& _neighborhood,
moEval < Neighbor > & _incrEval):
moeoUnifiedDominanceBasedLS<Neighbor>(
_continuator,
_eval,
_archive,
*(new moeoExhaustiveNeighborhoodExplorer<Neighbor>(_neighborhood, _incrEval)),
*(new moeoNumberUnvisitedSelect<MOEOT>(1))
){}
};
#endif /*MOEOPLS1_H_*/

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/*
* <moeoPLS2.h>
* Copyright (C) DOLPHIN Project-Team, INRIA Futurs, 2006-2008
* (C) OPAC Team, LIFL, 2002-2008
*
* Arnaud Liefooghe
* Jérémie Humeau
*
* This software is governed by the CeCILL license under French law and
* abiding by the rules of distribution of free software. You can use,
* modify and/ or redistribute the software under the terms of the CeCILL
* license as circulated by CEA, CNRS and INRIA at the following URL
* "http://www.cecill.info".
*
* As a counterpart to the access to the source code and rights to copy,
* modify and redistribute granted by the license, users are provided only
* with a limited warranty and the software's author, the holder of the
* economic rights, and the successive licensors have only limited liability.
*
* In this respect, the user's attention is drawn to the risks associated
* with loading, using, modifying and/or developing or reproducing the
* software by the user in light of its specific status of free software,
* that may mean that it is complicated to manipulate, and that also
* therefore means that it is reserved for developers and experienced
* professionals having in-depth computer knowledge. Users are therefore
* encouraged to load and test the software's suitability as regards their
* requirements in conditions enabling the security of their systems and/or
* data to be ensured and, more generally, to use and operate it in the
* same conditions as regards security.
* The fact that you are presently reading this means that you have had
* knowledge of the CeCILL license and that you accept its terms.
*
* ParadisEO WebSite : http://paradiseo.gforge.inria.fr
* Contact: paradiseo-help@lists.gforge.inria.fr
*
*/
//-----------------------------------------------------------------------------
#ifndef _MOEOPLS2_H
#define _MOEOPLS2_H
#include <algo/moeoUnifiedDominanceBasedLS.h>
#include <selection/moeoExhaustiveUnvisitedSelect.h>
#include <explorer/moeoExhaustiveNeighborhoodExplorer.h>
/**
* PLS2 algorithm
*
* Talbi EG, Rahoual M, Mabed MH, Dhaenens C (2001) A hybrid evolutionary approach for
* multicriteria optimization problems : Application to the fow shop. In: First International
* Conference on Evolutionary Multi-criterion Optimization (EMO 2001), Springer-Verlag,
* Zurich, Switzerland, Lecture Notes in Computer Science, vol 1993, pp 416–428
*
* Basseur M, Seynhaeve F, Talbi E (2003) Adaptive mechanisms for multiobjective evolution-
* ary algorithms. In: Congress on Engineering in System Application (CESA 2003), Lille,
* France, pp 72–86
*
* Angel E, Bampis E, Gourv ́ s L (2004) A dynasearch neighbohood for the bicriteria travel-
* ing salesman problem. In: Metaheuristics for Multiobjective Optimisation, Lecture Notes
* in Economics and Mathematical Systems, vol 535, Springer-Verlag, Berlin, Germany,
* chap 6, pp 153–176
*/
template < class Neighbor >
class moeoPLS2 : public moeoUnifiedDominanceBasedLS < Neighbor >
{
public:
/** Alias for the type */
typedef typename Neighbor::EOT MOEOT;
typedef typename MOEOT::ObjectiveVector ObjectiveVector;
/**
* Ctor
* @param _continuator a stop creterion
* @param _eval a evaluation function
* @param _archive a archive to store no-dominated individuals
* @param _neighborhood a neighborhood
* @param _incrEval neighbor evaluation function
*/
moeoPLS2(
eoContinue < MOEOT > & _continuator,
eoEvalFunc < MOEOT > & _eval,
moeoArchive < MOEOT > & _archive,
moNeighborhood<Neighbor>& _neighborhood,
moEval < Neighbor > & _incrEval):
moeoUnifiedDominanceBasedLS<Neighbor>(
_continuator,
_eval,
_archive,
*(new moeoExhaustiveNeighborhoodExplorer<Neighbor>(_neighborhood, _incrEval)),
*(new moeoExhaustiveUnvisitedSelect<MOEOT>())
){}
};
#endif /*MOEOPLS2_H_*/

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/*
* <moeoPopAlgo.h>
* Copyright (C) DOLPHIN Project-Team, INRIA Futurs, 2006-2007
* (C) OPAC Team, LIFL, 2002-2007
*
* Arnaud Liefooghe
* Jérémie Humeau
*
* This software is governed by the CeCILL license under French law and
* abiding by the rules of distribution of free software. You can use,
* modify and/ or redistribute the software under the terms of the CeCILL
* license as circulated by CEA, CNRS and INRIA at the following URL
* "http://www.cecill.info".
*
* As a counterpart to the access to the source code and rights to copy,
* modify and redistribute granted by the license, users are provided only
* with a limited warranty and the software's author, the holder of the
* economic rights, and the successive licensors have only limited liability.
*
* In this respect, the user's attention is drawn to the risks associated
* with loading, using, modifying and/or developing or reproducing the
* software by the user in light of its specific status of free software,
* that may mean that it is complicated to manipulate, and that also
* therefore means that it is reserved for developers and experienced
* professionals having in-depth computer knowledge. Users are therefore
* encouraged to load and test the software's suitability as regards their
* requirements in conditions enabling the security of their systems and/or
* data to be ensured and, more generally, to use and operate it in the
* same conditions as regards security.
* The fact that you are presently reading this means that you have had
* knowledge of the CeCILL license and that you accept its terms.
*
* ParadisEO WebSite : http://paradiseo.gforge.inria.fr
* Contact: paradiseo-help@lists.gforge.inria.fr
*
*/
//-----------------------------------------------------------------------------
#ifndef MOEOPOPALGO_H_
#define MOEOPOPALGO_H_
#include <eoAlgo.h>
#include <algo/moeoAlgo.h>
/**
* Abstract class for population based multi-objective evolutionary algorithms.
*/
template < class MOEOT >
class moeoPopAlgo : public moeoAlgo, public eoAlgo < MOEOT >
{};
#endif /*MOEOPOPALGO_H_*/

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/*
* <moeoPopLS.h>
* Copyright (C) DOLPHIN Project-Team, INRIA Futurs, 2006-2007
* (C) OPAC Team, LIFL, 2002-2007
*
* Arnaud Liefooghe
* Jérémie Humeau
*
* This software is governed by the CeCILL license under French law and
* abiding by the rules of distribution of free software. You can use,
* modify and/ or redistribute the software under the terms of the CeCILL
* license as circulated by CEA, CNRS and INRIA at the following URL
* "http://www.cecill.info".
*
* As a counterpart to the access to the source code and rights to copy,
* modify and redistribute granted by the license, users are provided only
* with a limited warranty and the software's author, the holder of the
* economic rights, and the successive licensors have only limited liability.
*
* In this respect, the user's attention is drawn to the risks associated
* with loading, using, modifying and/or developing or reproducing the
* software by the user in light of its specific status of free software,
* that may mean that it is complicated to manipulate, and that also
* therefore means that it is reserved for developers and experienced
* professionals having in-depth computer knowledge. Users are therefore
* encouraged to load and test the software's suitability as regards their
* requirements in conditions enabling the security of their systems and/or
* data to be ensured and, more generally, to use and operate it in the
* same conditions as regards security.
* The fact that you are presently reading this means that you have had
* knowledge of the CeCILL license and that you accept its terms.
*
* ParadisEO WebSite : http://paradiseo.gforge.inria.fr
* Contact: paradiseo-help@lists.gforge.inria.fr
*
*/
//-----------------------------------------------------------------------------
#ifndef MOEOPOPLS_H_
#define MOEOPOPLS_H_
#include <algo/moeoPopAlgo.h>
/**
* Abstract class for Population based multi-objective local search.
*/
template < class Neighborhhod >
class moeoPopLS : public moeoPopAlgo < typename Neighborhhod::EOT > {};
#endif /*MOEOPOPLS_H_*/

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/*
* <moeoSEEA.h>
* Copyright (C) DOLPHIN Project-Team, INRIA Lille-Nord Europe, 2006-2008
* (C) OPAC Team, LIFL, 2002-2008
*
* Arnaud Liefooghe
*
* This software is governed by the CeCILL license under French law and
* abiding by the rules of distribution of free software. You can use,
* modify and/ or redistribute the software under the terms of the CeCILL
* license as circulated by CEA, CNRS and INRIA at the following URL
* "http://www.cecill.info".
*
* As a counterpart to the access to the source code and rights to copy,
* modify and redistribute granted by the license, users are provided only
* with a limited warranty and the software's author, the holder of the
* economic rights, and the successive licensors have only limited liability.
*
* In this respect, the user's attention is drawn to the risks associated
* with loading, using, modifying and/or developing or reproducing the
* software by the user in light of its specific status of free software,
* that may mean that it is complicated to manipulate, and that also
* therefore means that it is reserved for developers and experienced
* professionals having in-depth computer knowledge. Users are therefore
* encouraged to load and test the software's suitability as regards their
* requirements in conditions enabling the security of their systems and/or
* data to be ensured and, more generally, to use and operate it in the
* same conditions as regards security.
* The fact that you are presently reading this means that you have had
* knowledge of the CeCILL license and that you accept its terms.
*
* ParadisEO WebSite : http://paradiseo.gforge.inria.fr
* Contact: paradiseo-help@lists.gforge.inria.fr
*
*/
#ifndef MOEOSEEA_H_
#define MOEOSEEA_H_
#include <eoBreed.h>
#include <eoCloneOps.h>
#include <eoContinue.h>
#include <eoEvalFunc.h>
#include <eoGenContinue.h>
#include <eoGeneralBreeder.h>
#include <eoGenOp.h>
#include <eoPopEvalFunc.h>
#include <eoSGAGenOp.h>
#include <algo/moeoEA.h>
#include <archive/moeoArchive.h>
#include <replacement/moeoGenerationalReplacement.h>
#include <selection/moeoRandomSelect.h>
#include <selection/moeoSelectFromPopAndArch.h>
/**
* SEEA (Simple Elitist Evolutionary Algorithm).
* Liefooghe A. Jourdan L., Talbi E.-G.. Metaheuristics and Their Hybridization to Solve the Bi-objective Ring Star Problem: a Comparative Study. Technical Report RR-6515, INRIA, 2008
* This class builds SEEA by using the fine-grained components of the ParadisEO-MOEO framework.
*/
template < class MOEOT >
class moeoSEEA : public moeoEA < MOEOT >
{
public:
/**
* Ctor with a crossover, a mutation and their corresponding rates.
* @param _maxGen number of generations before stopping
* @param _eval evaluation function
* @param _crossover crossover
* @param _pCross crossover probability
* @param _mutation mutation
* @param _pMut mutation probability
* @param _archive archive
*/
moeoSEEA (unsigned int _maxGen, eoEvalFunc < MOEOT > & _eval, eoQuadOp < MOEOT > & _crossover, double _pCross, eoMonOp < MOEOT > & _mutation, double _pMut, moeoArchive < MOEOT > & _archive) :
defaultGenContinuator(_maxGen), continuator(defaultGenContinuator), eval(_eval), defaultPopEval(_eval), popEval(defaultPopEval), select(randomSelect, _archive, 0.0), selectMany(select,0.0), selectTransform(defaultSelect, defaultTransform), defaultSGAGenOp(_crossover, _pCross, _mutation, _pMut), genBreed (select, defaultSGAGenOp), breed (genBreed), archive(_archive)
{}
/**
* Ctor with a eoContinue and a eoGenOp.
* @param _continuator stopping criteria
* @param _eval evaluation function
* @param _op variation operators
* @param _archive archive
*/
moeoSEEA (eoContinue < MOEOT > & _continuator, eoEvalFunc < MOEOT > & _eval, eoGenOp < MOEOT > & _op, moeoArchive < MOEOT > & _archive) :
defaultGenContinuator(0), continuator(_continuator), eval(_eval), defaultPopEval(_eval), popEval(defaultPopEval), select(randomSelect, _archive, 0.0), selectMany(select,0.0), selectTransform(defaultSelect, defaultTransform), defaultSGAGenOp(defaultQuadOp, 1.0, defaultMonOp, 1.0), genBreed(select, _op), breed(genBreed), archive(_archive)
{}
/**
* Ctor with a eoContinue, a eoPopEval and a eoGenOp.
* @param _continuator stopping criteria
* @param _popEval population evaluation function
* @param _op variation operators
* @param _archive archive
*/
moeoSEEA (eoContinue < MOEOT > & _continuator, eoPopEvalFunc < MOEOT > & _popEval, eoGenOp < MOEOT > & _op, moeoArchive < MOEOT > & _archive) :
defaultGenContinuator(0), continuator(_continuator), eval(defaultEval), defaultPopEval(eval), popEval(_popEval), select(randomSelect, _archive, 0.0), selectMany(select,0.0), selectTransform(defaultSelect, defaultTransform), defaultSGAGenOp(defaultQuadOp, 1.0, defaultMonOp, 1.0), genBreed(select, _op), breed(genBreed), archive(_archive)
{}
/**
* Ctor with a eoContinue and a eoTransform.
* @param _continuator stopping criteria
* @param _eval evaluation function
* @param _transform variation operator
* @param _archive archive
*/
moeoSEEA (eoContinue < MOEOT > & _continuator, eoEvalFunc < MOEOT > & _eval, eoTransform < MOEOT > & _transform, moeoArchive < MOEOT > & _archive) :
defaultGenContinuator(0), continuator(_continuator), eval(_eval), defaultPopEval(_eval), popEval(defaultPopEval), select(randomSelect, _archive, 0.0), selectMany(select, 1.0), selectTransform(selectMany, _transform), defaultSGAGenOp(defaultQuadOp, 0.0, defaultMonOp, 0.0), genBreed(select, defaultSGAGenOp), breed(selectTransform), archive(_archive)
{}
/**
* Ctor with a eoContinue, a eoPopEval and a eoTransform.
* @param _continuator stopping criteria
* @param _popEval population evaluation function
* @param _transform variation operator
* @param _archive archive
*/
moeoSEEA (eoContinue < MOEOT > & _continuator, eoPopEvalFunc < MOEOT > & _popEval, eoTransform < MOEOT > & _transform, moeoArchive < MOEOT > & _archive) :
defaultGenContinuator(0), continuator(_continuator), eval(defaultEval), defaultPopEval(eval), popEval(_popEval), select(randomSelect, _archive, 0.0), selectMany(select, 1.0), selectTransform(selectMany, _transform), defaultSGAGenOp(defaultQuadOp, 0.0, defaultMonOp, 0.0), genBreed(select, defaultSGAGenOp), breed(selectTransform), archive(_archive)
{}
/**
* Apply a few generation of evolution to the population _pop until the stopping criteria is verified.
* @param _pop the population
*/
virtual void operator () (eoPop < MOEOT > &_pop)
{
eoPop < MOEOT > empty_pop, offspring;
popEval (empty_pop, _pop); // a first eval of _pop
archive(_pop); // archive update
while (continuator (_pop))
{
// generate offspring, worths are recalculated if necessary
genBreed (_pop, offspring);
popEval (_pop, offspring); // eval of offspring
// after replace, the new pop is in _pop
// replace (_pop, offspring);
// archive (_pop); // archive update
archive(offspring);
// _pop.resize(0);
// offspring.resize(0);
}
}
protected:
/** a continuator based on the number of generations (used as default) */
eoGenContinue < MOEOT > defaultGenContinuator;
/** stopping criteria */
eoContinue < MOEOT > & continuator;
/** default eval */
class DummyEval : public eoEvalFunc < MOEOT >
{
public:
void operator()(MOEOT &) {}
}
defaultEval;
/** evaluation function */
eoEvalFunc < MOEOT > & eval;
/** default popEval */
eoPopLoopEval < MOEOT > defaultPopEval;
/** evaluation function used to evaluate the whole population */
eoPopEvalFunc < MOEOT > & popEval;
/** default select */
class DummySelect : public eoSelect < MOEOT >
{
public :
void operator()(const eoPop<MOEOT>&, eoPop<MOEOT>&) {}
}
defaultSelect;
/** random select */
moeoRandomSelect < MOEOT > randomSelect;
/** elitist selection */
moeoSelectFromPopAndArch < MOEOT > select;
/** default select many */
eoSelectMany < MOEOT > selectMany;
/** select transform */
eoSelectTransform < MOEOT > selectTransform;
/** a default crossover */
eoQuadCloneOp < MOEOT > defaultQuadOp;
/** a default mutation */
eoMonCloneOp < MOEOT > defaultMonOp;
/** an object for genetic operators (used as default) */
eoSGAGenOp < MOEOT > defaultSGAGenOp;
/** default transform */
class DummyTransform : public eoTransform < MOEOT >
{
public :
void operator()(eoPop<MOEOT>&) {}
}
defaultTransform;
/** general breeder */
eoGeneralBreeder < MOEOT > genBreed;
/** breeder */
eoBreed < MOEOT > & breed;
/** generational replacement */
moeoGenerationalReplacement < MOEOT > replace;
/**archive*/
moeoArchive < MOEOT >& archive;
};
#endif /*MOEOSEEA_H_*/

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/*
* <moeoSPEA2.h>
* Copyright (C) DOLPHIN Project-Team, INRIA Lille-Nord Europe, 2006-2008
* (C) OPAC Team, LIFL, 2002-2008
*
* Arnaud Liefooghe
* Jeremie Humeau
*
* This software is governed by the CeCILL license under French law and
* abiding by the rules of distribution of free software. You can use,
* modify and/ or redistribute the software under the terms of the CeCILL
* license as circulated by CEA, CNRS and INRIA at the following URL
* "http://www.cecill.info".
*
* As a counterpart to the access to the source code and rights to copy,
* modify and redistribute granted by the license, users are provided only
* with a limited warranty and the software's author, the holder of the
* economic rights, and the successive licensors have only limited liability.
*
* In this respect, the user's attention is drawn to the risks associated
* with loading, using, modifying and/or developing or reproducing the
* software by the user in light of its specific status of free software,
* that may mean that it is complicated to manipulate, and that also
* therefore means that it is reserved for developers and experienced
* professionals having in-depth computer knowledge. Users are therefore
* encouraged to load and test the software's suitability as regards their
* requirements in conditions enabling the security of their systems and/or
* data to be ensured and, more generally, to use and operate it in the
* same conditions as regards security.
* The fact that you are presently reading this means that you have had
* knowledge of the CeCILL license and that you accept its terms.
*
* ParadisEO WebSite : http://paradiseo.gforge.inria.fr
* Contact: paradiseo-help@lists.gforge.inria.fr
*
*/
//-----------------------------------------------------------------------------
// moeoSPEA2.h
//-----------------------------------------------------------------------------
#ifndef MOEOSPEA2_H_
#define MOEOSPEA2_H_
#include <eoBreed.h>
#include <eoCloneOps.h>
#include <eoContinue.h>
#include <eoEvalFunc.h>
#include <eoGenContinue.h>
#include <eoGeneralBreeder.h>
#include <eoGenOp.h>
#include <eoPopEvalFunc.h>
#include <eoSGAGenOp.h>
#include <algo/moeoEA.h>
#include <diversity/moeoNearestNeighborDiversityAssignment.h>
#include <fitness/moeoDominanceCountFitnessAssignment.h>
#include <fitness/moeoDominanceCountRankingFitnessAssignment.h>
#include <replacement/moeoGenerationalReplacement.h>
#include <selection/moeoDetTournamentSelect.h>
#include <archive/moeoFixedSizeArchive.h>
#include <distance/moeoEuclideanDistance.h>
#include <selection/moeoSelectFromPopAndArch.h>
/**
* SPEA2 algorithm.
* E. Zitzler, M. Laumanns, and L. Thiele. SPEA2: Improving the Strength Pareto Evolutionary Algorithm. Technical Report 103,
* Computer Engineering and Networks Laboratory (TIK), ETH Zurich, Zurich, Switzerland, 2001.
*/
template < class MOEOT >
class moeoSPEA2: public moeoEA < MOEOT >
{
public:
/**
* Ctor with a crossover, a mutation and their corresponding rates.
* @param _maxGen number of generations before stopping
* @param _eval evaluation function
* @param _crossover crossover
* @param _pCross crossover probability
* @param _mutation mutation
* @param _pMut mutation probability
* @param _archive archive
* @param _k the k-ieme distance used to fixe diversity
* @param _nocopy boolean allow to consider copies and doublons as bad elements whose were dominated by all other MOEOT in fitness assignment.
*/
moeoSPEA2 (unsigned int _maxGen, eoEvalFunc < MOEOT > & _eval, eoQuadOp < MOEOT > & _crossover, double _pCross, eoMonOp < MOEOT > & _mutation, double _pMut, moeoArchive < MOEOT >& _archive, unsigned int _k=1, bool _nocopy=false) :
defaultGenContinuator(_maxGen), continuator(defaultGenContinuator), eval(_eval), loopEval(_eval), popEval(loopEval), archive(_archive),defaultSelect(2),select(defaultSelect, defaultSelect, _archive, 0.0),
defaultSGAGenOp(_crossover, _pCross, _mutation, _pMut), fitnessAssignment(_archive, _nocopy),
genBreed(defaultSelect, defaultSGAGenOp),selectMany(defaultSelect,0.0), selectTransform(selectMany, dummyTransform), breed(genBreed), diversityAssignment(dist,_archive, _k)
{}
/**
* Ctor with a crossover, a mutation and their corresponding rates.
* @param _continuator stopping criteria
* @param _eval evaluation function
* @param _crossover crossover
* @param _pCross crossover probability
* @param _mutation mutation
* @param _pMut mutation probability
* @param _archive archive
* @param _k the k-ieme distance used to fixe diversity
* @param _nocopy boolean allow to consider copies and doublons as bad elements whose were dominated by all other MOEOT in fitness assignment.
*/
moeoSPEA2 (eoContinue < MOEOT >& _continuator, eoEvalFunc < MOEOT > & _eval, eoQuadOp < MOEOT > & _crossover, double _pCross, eoMonOp < MOEOT > & _mutation, double _pMut, moeoArchive < MOEOT >& _archive, unsigned int _k=1, bool _nocopy=false) :
defaultGenContinuator(0), continuator(_continuator), eval(_eval), loopEval(_eval), popEval(loopEval), archive(_archive),defaultSelect(2),select(defaultSelect, defaultSelect, _archive, 0.0),
defaultSGAGenOp(_crossover, _pCross, _mutation, _pMut), fitnessAssignment(_archive, _nocopy),
genBreed(defaultSelect, defaultSGAGenOp),selectMany(defaultSelect,0.0), selectTransform(selectMany, dummyTransform), breed(genBreed), diversityAssignment(dist,_archive, _k)
{}
/**
* Ctor with a crossover, a mutation and their corresponding rates.
* @param _continuator stopping criteria
* @param _eval pop evaluation function
* @param _crossover crossover
* @param _pCross crossover probability
* @param _mutation mutation
* @param _pMut mutation probability
* @param _archive archive
* @param _k the k-ieme distance used to fixe diversity
* @param _nocopy boolean allow to consider copies and doublons as bad elements whose were dominated by all other MOEOT in fitness assignment.
*/
moeoSPEA2 (eoContinue < MOEOT >& _continuator, eoPopEvalFunc < MOEOT > & _eval, eoQuadOp < MOEOT > & _crossover, double _pCross, eoMonOp < MOEOT > & _mutation, double _pMut, moeoArchive < MOEOT >& _archive, unsigned int _k=1, bool _nocopy=false) :
defaultGenContinuator(0), continuator(_continuator), eval(dummyEval), loopEval(dummyEval), popEval(_eval), archive(_archive),defaultSelect(2),select(defaultSelect, defaultSelect, _archive, 0.0),
defaultSGAGenOp(_crossover, _pCross, _mutation, _pMut), fitnessAssignment(_archive, _nocopy),
genBreed(defaultSelect, defaultSGAGenOp),selectMany(defaultSelect,0.0), selectTransform(selectMany, dummyTransform), breed(genBreed), diversityAssignment(dist,_archive, _k)
{}
/**
* Ctor with a crossover, a mutation and their corresponding rates.
* @param _continuator stopping criteria
* @param _eval evaluation function
* @param _op general operator
* @param _archive archive
* @param _k the k-ieme distance used to fixe diversity
* @param _nocopy boolean allow to consider copies and doublons as bad elements whose were dominated by all other MOEOT in fitness assignment.
*/
moeoSPEA2 (eoContinue < MOEOT >& _continuator, eoEvalFunc < MOEOT > & _eval, eoGenOp < MOEOT > & _op, moeoArchive < MOEOT >& _archive, unsigned int _k=1, bool _nocopy=false) :
defaultGenContinuator(0), continuator(_continuator), eval(_eval), loopEval(_eval), popEval(loopEval), archive(_archive),defaultSelect(2),select(defaultSelect, defaultSelect, _archive, 0.0),
defaultSGAGenOp(defaultQuadOp, 0.0, defaultMonOp, 0.0), fitnessAssignment(_archive, _nocopy),
genBreed(select, _op),selectMany(defaultSelect,0.0), selectTransform(selectMany, dummyTransform), breed(genBreed), diversityAssignment(dist,_archive, _k)
{}
/**
* Ctor with a crossover, a mutation and their corresponding rates.
* @param _continuator stopping criteria
* @param _eval evaluation function
* @param _op transformer
* @param _archive archive
* @param _k the k-ieme distance used to fixe diversity
* @param _nocopy boolean allow to consider copies and doublons as bad elements whose were dominated by all other MOEOT in fitness assignment.
*/
moeoSPEA2 (eoContinue < MOEOT >& _continuator, eoEvalFunc < MOEOT > & _eval, eoTransform < MOEOT > & _op, moeoArchive < MOEOT >& _archive, unsigned int _k=1, bool _nocopy=false) :
defaultGenContinuator(0), continuator(_continuator), eval(_eval), loopEval(_eval), popEval(loopEval), archive(_archive),defaultSelect(2),select(defaultSelect, defaultSelect, _archive, 0.0),
defaultSGAGenOp(defaultQuadOp, 0.0, defaultMonOp, 0.0), fitnessAssignment(_archive, _nocopy),
genBreed(defaultSelect, defaultSGAGenOp),selectMany(select,1.0), selectTransform(selectMany, _op), breed(selectTransform), diversityAssignment(dist,_archive, _k)
{}
/**
* Ctor with a crossover, a mutation and their corresponding rates.
* @param _continuator stopping criteria
* @param _eval pop evaluation function
* @param _op general operator
* @param _archive archive
* @param _k the k-ieme distance used to fixe diversity
* @param _nocopy boolean allow to consider copies and doublons as bad elements whose were dominated by all other MOEOT in fitness assignment.
*/
moeoSPEA2 (eoContinue < MOEOT >& _continuator, eoPopEvalFunc < MOEOT > & _eval, eoGenOp < MOEOT > & _op, moeoArchive < MOEOT >& _archive, unsigned int _k=1, bool _nocopy=false) :
defaultGenContinuator(0), continuator(_continuator),eval(dummyEval), loopEval(dummyEval), popEval(_eval), archive(_archive),defaultSelect(2),select(defaultSelect, defaultSelect, _archive, 0.0),
defaultSGAGenOp(defaultQuadOp, 0.0, defaultMonOp, 0.0), fitnessAssignment(_archive, _nocopy),
genBreed(select, _op),selectMany(defaultSelect,0.0), selectTransform(selectMany, dummyTransform), breed(genBreed), diversityAssignment(dist,_archive, _k)
{}
/**
* Ctor with a crossover, a mutation and their corresponding rates.
* @param _continuator stopping criteria
* @param _eval pop evaluation function
* @param _op transformer
* @param _archive archive
* @param _k the k-ieme distance used to fixe diversity
* @param _nocopy boolean allow to consider copies and doublons as bad elements whose were dominated by all other MOEOT in fitness assignment.
*/
moeoSPEA2 (eoContinue < MOEOT >& _continuator, eoPopEvalFunc < MOEOT > & _eval, eoTransform < MOEOT > & _op, moeoArchive < MOEOT >& _archive, unsigned int _k=100, bool _nocopy=false) :
defaultGenContinuator(0), continuator(_continuator),eval(dummyEval), loopEval(dummyEval), popEval(_eval), archive(_archive),defaultSelect(2),select(defaultSelect, defaultSelect, _archive, 0.0),
defaultSGAGenOp(defaultQuadOp, 0.0, defaultMonOp, 0.0), fitnessAssignment(_archive, _nocopy),
genBreed(defaultSelect, defaultSGAGenOp),selectMany(select,1.0), selectTransform(selectMany, _op), breed(selectTransform), diversityAssignment(dist,_archive, _k)
{}
/**
* Apply a few generation of evolution to the population _pop until the stopping criteria is verified.
* @param _pop the population
*/
virtual void operator () (eoPop < MOEOT > &_pop)
{
eoPop < MOEOT >empty_pop, offspring;
popEval (empty_pop, _pop);// a first eval of _pop
fitnessAssignment(_pop); //a first fitness assignment of _pop
diversityAssignment(_pop);//a first diversity assignment of _pop
archive(_pop);//a first filling of archive
while (continuator (_pop))
{
// generate offspring, worths are recalculated if necessary
breed (_pop, offspring);
popEval (_pop, offspring); // eval of offspring
// after replace, the new pop is in _pop. Worths are recalculated if necessary
replace (_pop, offspring);
fitnessAssignment(_pop); //fitness assignment of _pop
diversityAssignment(_pop); //diversity assignment of _pop
archive(_pop); //control of archive
}
}
protected:
/** dummy evaluation */
class eoDummyEval : public eoEvalFunc< MOEOT >
{
public:
void operator()(MOEOT &) {}
}
dummyEval;
/** dummy transform */
class eoDummyTransform : public eoTransform<MOEOT>
{
public :
void operator()(eoPop<MOEOT>&) {}
}
dummyTransform;
/** a continuator based on the number of generations (used as default) */
eoGenContinue < MOEOT > defaultGenContinuator;
/** stopping criteria */
eoContinue < MOEOT > & continuator;
/** evaluation function */
eoEvalFunc < MOEOT > & eval;
/** loop eval */
eoPopLoopEval < MOEOT > loopEval;
/** evaluation function used to evaluate the whole population */
eoPopEvalFunc < MOEOT > & popEval;
/**archive*/
moeoArchive < MOEOT >& archive;
/**SelectOne*/
moeoDetTournamentSelect < MOEOT > defaultSelect;
/** binary tournament selection */
moeoSelectFromPopAndArch < MOEOT > select;
/** a default mutation */
eoMonCloneOp < MOEOT > defaultMonOp;
/** a default crossover */
eoQuadCloneOp < MOEOT > defaultQuadOp;
/** an object for genetic operators (used as default) */
eoSGAGenOp < MOEOT > defaultSGAGenOp;
/** fitness assignment used in NSGA-II */
moeoDominanceCountRankingFitnessAssignment < MOEOT > fitnessAssignment;
/** general breeder */
eoGeneralBreeder < MOEOT > genBreed;
/** selectMany */
eoSelectMany <MOEOT> selectMany;
/** select Transform*/
eoSelectTransform <MOEOT> selectTransform;
/** breeder */
eoBreed < MOEOT > & breed;
/** diversity assignment used in NSGA-II */
moeoNearestNeighborDiversityAssignment < MOEOT > diversityAssignment;
/** elitist replacement */
moeoGenerationalReplacement < MOEOT > replace;
/**distance*/
moeoEuclideanDistance < MOEOT > dist;
};
#endif /*MOEOSPEA2_H_*/

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/*
* <moeoUnifiedDominanceBasedLS.h>
* Copyright (C) DOLPHIN Project-Team, INRIA Futurs, 2006-2008
* (C) OPAC Team, LIFL, 2002-2008
*
* Arnaud Liefooghe
* Jérémie Humeau
*
* This software is governed by the CeCILL license under French law and
* abiding by the rules of distribution of free software. You can use,
* modify and/ or redistribute the software under the terms of the CeCILL
* license as circulated by CEA, CNRS and INRIA at the following URL
* "http://www.cecill.info".
*
* As a counterpart to the access to the source code and rights to copy,
* modify and redistribute granted by the license, users are provided only
* with a limited warranty and the software's author, the holder of the
* economic rights, and the successive licensors have only limited liability.
*
* In this respect, the user's attention is drawn to the risks associated
* with loading, using, modifying and/or developing or reproducing the
* software by the user in light of its specific status of free software,
* that may mean that it is complicated to manipulate, and that also
* therefore means that it is reserved for developers and experienced
* professionals having in-depth computer knowledge. Users are therefore
* encouraged to load and test the software's suitability as regards their
* requirements in conditions enabling the security of their systems and/or
* data to be ensured and, more generally, to use and operate it in the
* same conditions as regards security.
* The fact that you are presently reading this means that you have had
* knowledge of the CeCILL license and that you accept its terms.
*
* ParadisEO WebSite : http://paradiseo.gforge.inria.fr
* Contact: paradiseo-help@lists.gforge.inria.fr
*
*/
//-----------------------------------------------------------------------------
#ifndef _MOEOUNIFIEDDOMINANCEBASEDLS_H
#define _MOEOUNIFIEDDOMINANCEBASEDLS_H
#include <eoPop.h>
#include <eoContinue.h>
#include <eoEvalFunc.h>
#include <eoPopEvalFunc.h>
#include <archive/moeoArchive.h>
#include <algo/moeoPopLS.h>
#include <explorer/moeoPopNeighborhoodExplorer.h>
#include <selection/moeoUnvisitedSelect.h>
/**
* A class to design dominance based local searches
*/
template < class Neighbor >
class moeoUnifiedDominanceBasedLS : public moeoPopLS < Neighbor >
{
public:
/** Alias for the type */
typedef typename Neighbor::EOT MOEOT;
/**
* Ctor
* @param _continuator a stop creterion
* @param _eval a evaluation function
* @param _archive a archive to store no-dominated individuals
* @param _explorer a neighborhood explorer
* @param _select a selector of unvisited individuals of a population
*/
moeoUnifiedDominanceBasedLS(
eoContinue < MOEOT > & _continuator,
eoEvalFunc < MOEOT > & _eval,
moeoArchive < MOEOT > & _archive,
moeoPopNeighborhoodExplorer < Neighbor > & _explorer,
moeoUnvisitedSelect < MOEOT > & _select) :
continuator(_continuator), loopEval(_eval), popEval(loopEval), archive(_archive), explorer(_explorer), select(_select) {}
/**
* Applies a few generation of evolution to the population _pop.
* @param _pop the population
*/
virtual void operator()(eoPop < MOEOT > & _pop)
{
std::vector < unsigned int> selectionVector;
eoPop < MOEOT > tmp_pop;
popEval(tmp_pop, _pop);
archive(_pop);
do{
tmp_pop.resize(0);
//selection
selectionVector = select(archive);
//exploration
explorer(archive, selectionVector, tmp_pop);
//archivage
archive(tmp_pop);
}
while (continuator(archive) && naturalContinuator(archive));
}
protected:
/** continuator */
eoContinue < MOEOT > & continuator;
/** loopEval */
eoPopLoopEval < MOEOT > loopEval;
/** popEval */
eoPopEvalFunc < MOEOT > & popEval;
/** archive */
moeoArchive < MOEOT > & archive;
/** explorer */
moeoPopNeighborhoodExplorer < Neighbor > & explorer;
/** selector */
moeoUnvisitedSelect < MOEOT > & select;
/**
* Natural Continuator (Stop when all individuals of the population are visited)
*/
class moeoContinue : public eoUF < eoPop < MOEOT > &, bool >
{
public:
/**
* Ctor
*/
moeoContinue(){}
/**
* functor which evaluate if the algorithm continue or not
* @param _pop the population
* @return true if the algorithm continue, else return false
*/
virtual bool operator()(eoPop < MOEOT > & _pop)
{
bool res = false;
unsigned int i=0;
while (!res && i < _pop.size()){
res = (_pop[i].flag() != 1);
i++;
}
//if (res==false)
//std::cout << "[Natural stop]" << std::endl;
return res;
}
} naturalContinuator;
};
#endif /*MOEOUNIFIEDDOMINANCEBASEDLS_H_*/

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// j'ai installé le svn :)
// re-test
/*
* <moeo2DMinHypervolumeArchive.h>
* Copyright (C) DOLPHIN Project-Team, INRIA Futurs, 2006-2007
* (C) OPAC Team, LIFL, 2002-2007
*
* Arnaud Liefooghe
* Jérémie Humeau
*
* This software is governed by the CeCILL license under French law and
* abiding by the rules of distribution of free software. You can use,
* modify and/ or redistribute the software under the terms of the CeCILL
* license as circulated by CEA, CNRS and INRIA at the following URL
* "http://www.cecill.info".
*
* As a counterpart to the access to the source code and rights to copy,
* modify and redistribute granted by the license, users are provided only
* with a limited warranty and the software's author, the holder of the
* economic rights, and the successive licensors have only limited liability.
*
* In this respect, the user's attention is drawn to the risks associated
* with loading, using, modifying and/or developing or reproducing the
* software by the user in light of its specific status of free software,
* that may mean that it is complicated to manipulate, and that also
* therefore means that it is reserved for developers and experienced
* professionals having in-depth computer knowledge. Users are therefore
* encouraged to load and test the software's suitability as regards their
* requirements in conditions enabling the security of their systems and/or
* data to be ensured and, more generally, to use and operate it in the
* same conditions as regards security.
* The fact that you are presently reading this means that you have had
* knowledge of the CeCILL license and that you accept its terms.
*
* ParadisEO WebSite : http://paradiseo.gforge.inria.fr
* Contact: paradiseo-help@lists.gforge.inria.fr
*
*/
//-----------------------------------------------------------------------------
#ifndef MOEO2DMINHYPERVOLUMEARCHIVE_H_
#define MOEO2DMINHYPERVOLUMEARCHIVE_H_
#include <set>
#include <climits>
template < class MOEOT >
struct comp
{
// returns a "before" b
// all objectives = min
bool operator() (const MOEOT & a, const MOEOT & b)
{
return ((a.objectiveVector()[1] < b.objectiveVector()[1]) || ((a.objectiveVector()[1] == b.objectiveVector()[1]) && (a.objectiveVector()[0] < b.objectiveVector()[0])));
}
};
/** 2D (minimization) bounded archive by hypervolume , base on a set */
template < class MOEOT >
class moeo2DMinHypervolumeArchive : public std::set<MOEOT , comp < MOEOT > >
{
public:
typedef typename MOEOT::Fitness Fitness;
typedef typename MOEOT::ObjectiveVector ObjectiveVector;
typedef typename std::set < MOEOT, comp<MOEOT> >::iterator Iterator;
using std::set < MOEOT, comp<MOEOT> > :: begin;
using std::set < MOEOT, comp<MOEOT> > :: end;
using std::set < MOEOT, comp<MOEOT> > :: insert;
using std::set < MOEOT, comp<MOEOT> > :: erase;
using std::set < MOEOT, comp<MOEOT> > :: size;
using std::set < MOEOT, comp<MOEOT> > :: upper_bound;
/**
* Ctr.
* @param _maxSize size of the archive (must be >= 2)
* @param _maxValue fitness assigned to the first and the last solution in the archive (default LONG_MAX)
*/
moeo2DMinHypervolumeArchive(unsigned int _maxSize=100, double _maxValue=LONG_MAX) : std::set < MOEOT, comp<MOEOT> > (), maxSize(_maxSize), maxValue(_maxValue)
{
maxSize = std::max((unsigned int) 2, maxSize);
}
/**
* Update the archive with a solution
* @param _moeo a solution
* @return true if _moeo has been added to the archive
*/
bool operator()(const MOEOT & _moeo)
{
//store result
bool result;
Iterator it;
//If archive is empty -> add the sol and affect its fitness value
if (size()==0)
{
result = true;
insert(_moeo);
it=begin();
fitness(it, maxValue);
}
else // test if sol can be added to the archive
{
result = insert(_moeo.objectiveVector());
if (result)
{
if(size() < maxSize)
{
// if yes, insert it and recompute fitness value of MOEOT and its neighbors
insert(hint, _moeo);
if(size() > 2)
{
//general case
hint--;
computeFitness(hint);
}
else
{
//archive size <= 2, fitness=maxValue for each sol
it=begin();
while(it!=end())
{
fitness(it, maxValue);
it++;
}
}
}
else
{
result = filter(_moeo);
}
}
}
return result;
}
/**
* update the archive with a population
* @param _pop a pop
* @return true if at least one solution of _pop has been added to the archive
*/
bool operator()(const eoPop < MOEOT > & _pop)
{
bool result = false;
bool tmp = false;
for (unsigned int i=0; i<_pop.size(); i++)
{
std::cout << "insert " << _pop[i].objectiveVector()[0] << ", " << _pop[i].objectiveVector()[1] << std::endl;
tmp = (*this)(_pop[i]);
result = tmp || result;
}
return result;
}
/**
* Test if insertion wrt Pareto-dominance is possible, and fix 'hint' if possible
* @param _objVec the objective vector of the sol to insert
* @return true if objVec can be added to the archive wrt Pareto-dominance
*/
bool insert(const ObjectiveVector & _objVec)
{
bool result = false;
Iterator it;
double min;
// set the objVec to the empty solution
empty.objectiveVector(_objVec);
// compute the position where it would possibly be added
it = upper_bound(empty);
// compute the weigth from the previous solution
min = begin()->objectiveVector()[0];
if (it != begin())
{
it--;
min = (*it).objectiveVector()[0];
it++;
}
// if it has a better weitgh, or if it's an extreme sol, let's add it
if (it == begin() || _objVec[0]<min)
{
// remove dominated solutions
remove(it,_objVec);
// set hint to the current iterator (probably modified by "remove")
hint=it;
// set result to true
result = true;
}
return result;
}
/**
* print objective vector and fitness value of the archive
*/
void print()
{
Iterator it = begin();
while(it!=end())
{
std::cout << (*it).objectiveVector()[0] << " " << (*it).objectiveVector()[1] << ", fit: " << (*it).fitness() << std::endl;
it++;
}
}
protected:
/** size max of the archive */
unsigned int maxSize;
/** fitness assigned to the first and the last solution in the archive */
double maxValue;
/** hint for the insertion */
Iterator hint;
/** an empty MOEOT used for checking insertion */
MOEOT empty;
/**
* set fitness
*/
void fitness(Iterator & _it, double _fitnessValue)
{
MOEOT* tmp;
tmp = (MOEOT*)&(*_it);
tmp->fitness(_fitnessValue);
}
/**
* remove solutions from the archive that are dominated by _objVec
* @param _it an iterator beginning on the first potentialy sol to remove
* @param _objVec the objective vector of the new solution
*/
void remove(Iterator & _it, const ObjectiveVector & _objVec)
{
Iterator itd;
while ((_it!=end()) && ((*_it).objectiveVector()[0] >= _objVec[0]))
{
itd = _it;
_it++;
erase(itd);
}
}
/**
* compute fitness value of a solution and its two neighbors
* @param _it refer to the solution
*/
void computeFitness(Iterator & _it)
{
Iterator tmp;
if(_it!=begin())
{
tmp=_it;
tmp--;
compute(tmp);
}
_it++;
if(_it!=end())
{
_it--;
tmp=_it;
tmp++;
compute(tmp);
}
else
{
_it--;
}
compute(_it);
}
/**
* compute fitness value of a solution
* @param _it refer to the solution
*/
void compute(Iterator & _it)
{
double x0, x1, y0, y1, fit;
if (_it==begin())
{
fitness(_it, maxValue);
}
else if ((++_it)==end())
{
_it--;
fitness(_it, maxValue);
}
else
{
_it--;
x0 = (*_it).objectiveVector()[0];
y0 = (*_it).objectiveVector()[1];
_it--;
x1 = (*_it).objectiveVector()[0];
_it++;
_it++;
y1 = (*_it).objectiveVector()[1];
_it--;
fit = (x1 - x0) * (y1 - y0);
fitness(_it, fit);
//tmp = (MOEOT*)&(*_it);
//tmp->fitness(fit);
}
}
double computeTmp(const ObjectiveVector & _objVec, int _where)
{
double res, tmp;
if(hint==begin() || hint==end())
res=maxValue;
else{
if(_where==0){
//on calcule la fit de celui à potentiellement inserer
res= (*hint).objectiveVector()[1] - _objVec[1];
hint--;
res*= ((*hint).objectiveVector()[0] - _objVec[0]);
hint++;
}
else if(_where <0){
// on calcule la fit de son predecesseur
res= _objVec[1] - (*hint).objectiveVector()[1];
tmp=(*hint).objectiveVector()[0];
hint--;
res*= ((*hint).objectiveVector()[0] - tmp);
hint++;
}
else{
// on calcule la fit de son successeur
res= _objVec[0] - (*hint).objectiveVector()[0];
tmp=(*hint).objectiveVector()[1];
hint++;
res*= ((*hint).objectiveVector()[1] - tmp);
hint--;
}
}
return res;
}
void filterbis()
{
Iterator it, itd;
//used to find sol with minimum fitness value
double minFit = maxValue;
// remove MOEOT with the lowest fitness value while archive size > maxSize
while (size() > maxSize)
{
//find sol with minimum fitness
for(it=begin(); it!=end(); it++)
{
if(it->fitness() < minFit)
{
minFit = it->fitness();
itd = it;
}
}
//remove it and recompute fitness of its neighbors
it = itd;
it--;
erase(itd);
compute(it);
it++;
compute(it);
}
}
/**
* iteratively removes the less-contributing solution from the acrhive
*/
bool filter(const MOEOT & _moeo)
{
bool res;
double x, y, pred, succ, tmp=0;
if(hint==begin() || hint==end())
{
insert(hint, _moeo);
hint--;
computeFitness(hint);
filterbis();
res=true;
}
else
{
//compute fitness tmp
tmp=computeTmp(_moeo.objectiveVector(), 0);
hint--;
pred=computeTmp(_moeo.objectiveVector(), -1);
hint++;
succ=computeTmp(_moeo.objectiveVector(), 1);
if(tmp>succ || tmp>pred)
{
insert(hint, _moeo);
hint--;
//ici faudrait utiliser les valeurs qu'on vient de calculer pour les affecter direct (faire attention à ou on se trouve)
computeFitness(hint);
filterbis();
res=true;
}
else
{
Iterator it;
double minFit = maxValue;
for(it=begin(); it!=end(); it++)
{
if(it->fitness() < minFit)
{
minFit = it->fitness();
}
}
if (tmp<=minFit)
{
res = false;
}
else
{
// REDONDANT arranger le code
insert(hint, _moeo);
hint--;
//ici faudrait utiliser les valeurs qu'on vient de calculer pour les affecter direct (faire attention à ou on se trouve)
computeFitness(hint);
filterbis();
res=true;
}
}
}
return res;
}
};
#endif /* MOEO2DMINHYPERVOLUMEARCHIVE_H_ */

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/*
* <moeoArchive.h>
* Copyright (C) DOLPHIN Project-Team, INRIA Futurs, 2006-2007
* (C) OPAC Team, LIFL, 2002-2007
*
* Arnaud Liefooghe
*
* This software is governed by the CeCILL license under French law and
* abiding by the rules of distribution of free software. You can use,
* modify and/ or redistribute the software under the terms of the CeCILL
* license as circulated by CEA, CNRS and INRIA at the following URL
* "http://www.cecill.info".
*
* As a counterpart to the access to the source code and rights to copy,
* modify and redistribute granted by the license, users are provided only
* with a limited warranty and the software's author, the holder of the
* economic rights, and the successive licensors have only limited liability.
*
* In this respect, the user's attention is drawn to the risks associated
* with loading, using, modifying and/or developing or reproducing the
* software by the user in light of its specific status of free software,
* that may mean that it is complicated to manipulate, and that also
* therefore means that it is reserved for developers and experienced
* professionals having in-depth computer knowledge. Users are therefore
* encouraged to load and test the software's suitability as regards their
* requirements in conditions enabling the security of their systems and/or
* data to be ensured and, more generally, to use and operate it in the
* same conditions as regards security.
* The fact that you are presently reading this means that you have had
* knowledge of the CeCILL license and that you accept its terms.
*
* ParadisEO WebSite : http://paradiseo.gforge.inria.fr
* Contact: paradiseo-help@lists.gforge.inria.fr
*
*/
//-----------------------------------------------------------------------------
#ifndef MOEOARCHIVE_H_
#define MOEOARCHIVE_H_
#include <eoPop.h>
#include <comparator/moeoObjectiveVectorComparator.h>
#include <comparator/moeoParetoObjectiveVectorComparator.h>
/**
* Abstract class for representing an archive ;
* an archive is a secondary population that stores non-dominated solutions.
*/
template < class MOEOT >
class moeoArchive : public eoPop < MOEOT >, public eoUF < const MOEOT &, bool>, public eoUF < const eoPop < MOEOT > &, bool>
{
public:
using eoPop < MOEOT > :: size;
using eoPop < MOEOT > :: operator[];
using eoPop < MOEOT > :: back;
using eoPop < MOEOT > :: pop_back;
/**
* The type of an objective vector for a solution
*/
typedef typename MOEOT::ObjectiveVector ObjectiveVector;
/**
* Default ctor.
* The moeoObjectiveVectorComparator used to compare solutions is based on Pareto dominance
* @param _replace boolean which determine if a solution with the same objectiveVector than another one, can replace it or not
*/
moeoArchive(bool _replace=true) : eoPop < MOEOT >(), comparator(paretoComparator), replace(_replace)
{}
/**
* Ctor
* @param _comparator the moeoObjectiveVectorComparator used to compare solutions
* @param _replace boolean which determine if a solution with the same objectiveVector than another one, can replace it or not
*/
moeoArchive(moeoObjectiveVectorComparator < ObjectiveVector > & _comparator, bool _replace=true) : eoPop < MOEOT >(), comparator(_comparator), replace(_replace)
{}
/**
* Returns true if the current archive dominates _objectiveVector according to the moeoObjectiveVectorComparator given in the constructor
* @param _objectiveVector the objective vector to compare with the current archive
*/
bool dominates (const ObjectiveVector & _objectiveVector) const
{
for (unsigned int i = 0; i<size(); i++)
{
// if _objectiveVector is dominated by the ith individual of the archive...
if ( comparator(_objectiveVector, operator[](i).objectiveVector()) )
{
return true;
}
}
return false;
}
/**
* Returns true if the current archive already contains a solution with the same objective values than _objectiveVector
* @param _objectiveVector the objective vector to compare with the current archive
*/
bool contains (const ObjectiveVector & _objectiveVector) const
{
for (unsigned int i = 0; i<size(); i++)
{
if (operator[](i).objectiveVector() == _objectiveVector)
{
return true;
}
}
return false;
}
/**
* Updates the archive with a given individual _moeo
* @param _moeo the given individual
* @return if the _moeo is added to the archive
*/
virtual bool operator()(const MOEOT & _moeo) = 0;
/**
* Updates the archive with a given population _pop
* @param _pop the given population
* @return if at least one _pop[i] is added to the archive
*/
virtual bool operator()(const eoPop < MOEOT > & _pop) = 0;
/**
* Returns true if the current archive contains the same objective vectors than the given archive _arch
* @param _arch the given archive
*/
bool equals (const moeoArchive < MOEOT > & _arch)
{
for (unsigned int i=0; i<size(); i++)
{
if (! _arch.contains(operator[](i).objectiveVector()))
{
return false;
}
}
for (unsigned int i=0; i<_arch.size() ; i++)
{
if (! contains(_arch[i].objectiveVector()))
{
return false;
}
}
return true;
}
protected:
/**
* Updates the archive with a given individual _moeo
* @param _moeo the given individual
*/
bool update(const MOEOT & _moeo)
{
// first step: removing the dominated solutions from the archive
for (unsigned int j=0; j<size();)
{
// if the jth solution contained in the archive is dominated by _moeo
if ( comparator(operator[](j).objectiveVector(), _moeo.objectiveVector()) )
{
operator[](j) = back();
pop_back();
}
else if (replace && (_moeo.objectiveVector() == operator[](j).objectiveVector()))
{
operator[](j) = back();
pop_back();
}
else
{
j++;
}
}
// second step: is _moeo dominated?
bool dom = false;
for (unsigned int j=0; j<size(); j++)
{
// if _moeo is dominated by the jth solution contained in the archive
if ( comparator(_moeo.objectiveVector(), operator[](j).objectiveVector()) )
{
dom = true;
break;
}
else if (!replace && (_moeo.objectiveVector() == operator[](j).objectiveVector()) )
{
dom = true;
break;
}
}
if (!dom)
{
this->push_back(_moeo);
}
return !dom;
}
/**
* Updates the archive with a given population _pop
* @param _pop the given population
*/
bool update(const eoPop < MOEOT > & _pop)
{
bool res = false;
bool tmp = false;
for (unsigned int i=0; i<_pop.size(); i++)
{
tmp = (*this).update(_pop[i]);
res = tmp || res;
}
return res;
}
/** The moeoObjectiveVectorComparator used to compare solutions */
moeoObjectiveVectorComparator < ObjectiveVector > & comparator;
/** A moeoObjectiveVectorComparator based on Pareto dominance (used as default) */
moeoParetoObjectiveVectorComparator < ObjectiveVector > paretoComparator;
/** boolean */
bool replace;
};
#endif /*MOEOARCHIVE_H_ */

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/*
* <moeoBoundedArchive.h>
* Copyright (C) DOLPHIN Project-Team, INRIA Lille-Nord Europe, 2006-2008
* (C) OPAC Team, LIFL, 2002-2008
*
* Arnaud Liefooghe
* Jeremie Humeau
*
* This software is governed by the CeCILL license under French law and
* abiding by the rules of distribution of free software. You can use,
* modify and/ or redistribute the software under the terms of the CeCILL
* license as circulated by CEA, CNRS and INRIA at the following URL
* "http://www.cecill.info".
*
* As a counterpart to the access to the source code and rights to copy,
* modify and redistribute granted by the license, users are provided only
* with a limited warranty and the software's author, the holder of the
* economic rights, and the successive licensors have only limited liability.
*
* In this respect, the user's attention is drawn to the risks associated
* with loading, using, modifying and/or developing or reproducing the
* software by the user in light of its specific status of free software,
* that may mean that it is complicated to manipulate, and that also
* therefore means that it is reserved for developers and experienced
* professionals having in-depth computer knowledge. Users are therefore
* encouraged to load and test the software's suitability as regards their
* requirements in conditions enabling the security of their systems and/or
* data to be ensured and, more generally, to use and operate it in the
* same conditions as regards security.
* The fact that you are presently reading this means that you have had
* knowledge of the CeCILL license and that you accept its terms.
*
* ParadisEO WebSite : http://paradiseo.gforge.inria.fr
* Contact: paradiseo-help@lists.gforge.inria.fr
*
*/
//-----------------------------------------------------------------------------
// moeoBoundedArchive.h
//-----------------------------------------------------------------------------
#ifndef MOEOBOUNDEDARCHIVE_H_
#define MOEOBOUNDEDARCHIVE_H_
#include <archive/moeoArchive.h>
/**
* This class represents a bounded archive which different parameters to specify.
*/
template < class MOEOT >
class moeoBoundedArchive : public moeoArchive < MOEOT >
{
public:
/**
* The type of an objective vector for a solution
*/
typedef typename MOEOT::ObjectiveVector ObjectiveVector;
/**
* Ctor where you can choose your own moeoObjectiveVectorComparator and archive size.
* @param _comparator the functor used to compare objective vectors
* @param _maxSize the size of archive (must be smaller or egal to the population size)
* @param _replace boolean which determine if a solution with the same objectiveVector than another one, can replace it or not
*/
moeoBoundedArchive(moeoObjectiveVectorComparator < ObjectiveVector > & _comparator, unsigned int _maxSize=100, bool _replace=true) : moeoArchive < MOEOT >(_comparator, _replace), maxSize(_maxSize){}
/**
* Ctor with moeoParetoObjectiveVectorComparator where you can choose your own archive size.
* @param _maxSize the size of archive (must be smaller or egal to the population size)
* @param _replace boolean which determine if a solution with the same objectiveVector than another one, can replace it or not
*/
moeoBoundedArchive(unsigned int _maxSize=100, bool _replace=true) : moeoArchive < MOEOT >(_replace), maxSize(_maxSize){}
protected:
/** archive max size */
unsigned int maxSize;
};
#endif /*MOEOBOUNDEDARCHIVE_H_*/

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/*
* <moeoEpsilonHyperboxArchive.h>
* Copyright (C) DOLPHIN Project-Team, INRIA Lille-Nord Europe, 2006-2008
* (C) OPAC Team, LIFL, 2002-2008
*
* Arnaud Liefooghe
* Jeremie Humeau
*
* This software is governed by the CeCILL license under French law and
* abiding by the rules of distribution of free software. You can use,
* modify and/ or redistribute the software under the terms of the CeCILL
* license as circulated by CEA, CNRS and INRIA at the following URL
* "http://www.cecill.info".
*
* As a counterpart to the access to the source code and rights to copy,
* modify and redistribute granted by the license, users are provided only
* with a limited warranty and the software's author, the holder of the
* economic rights, and the successive licensors have only limited liability.
*
* In this respect, the user's attention is drawn to the risks associated
* with loading, using, modifying and/or developing or reproducing the
* software by the user in light of its specific status of free software,
* that may mean that it is complicated to manipulate, and that also
* therefore means that it is reserved for developers and experienced
* professionals having in-depth computer knowledge. Users are therefore
* encouraged to load and test the software's suitability as regards their
* requirements in conditions enabling the security of their systems and/or
* data to be ensured and, more generally, to use and operate it in the
* same conditions as regards security.
* The fact that you are presently reading this means that you have had
* knowledge of the CeCILL license and that you accept its terms.
*
* ParadisEO WebSite : http://paradiseo.gforge.inria.fr
* Contact: paradiseo-help@lists.gforge.inria.fr
*
*/
//-----------------------------------------------------------------------------
// moeoEpsilonHyperboxArchive.h
//-----------------------------------------------------------------------------
#ifndef MOEOEPSILONBOXARCHIVE_H_
#define MOEOEPSILONBOXARCHIVE_H_
#include <eoPop.h>
#include <comparator/moeoComparator.h>
#include <comparator/moeoObjectiveVectorComparator.h>
#include <distance/moeoEuclideanDistance.h>
#include <utils/moeoObjectiveVectorNormalizer.h>
#include <utils/eoRealBounds.h>
/**
* This class represents an epsilon hyperbox archive.
*/
template < class MOEOT >
class moeoEpsilonHyperboxArchive : public moeoArchive < MOEOT >
{
public:
using moeoArchive < MOEOT > :: size;
using moeoArchive < MOEOT > :: resize;
using moeoArchive < MOEOT > :: operator[];
using moeoArchive < MOEOT > :: back;
using moeoArchive < MOEOT > :: pop_back;
using moeoArchive < MOEOT > :: push_back;
using moeoArchive < MOEOT > :: begin;
using moeoArchive < MOEOT > :: end;
using moeoArchive < MOEOT > :: replace;
/**
* The type of an objective vector for a solution
*/
typedef typename MOEOT::ObjectiveVector ObjectiveVector;
/**
* Ctor where you can choose your own moeoObjectiveVectorComparator
* @param _comparator the functor used to compare objective vectors
* @param _epsilon the vector contains epsilon values for each objective
* @param _replace boolean which determine if a solution with the same objectiveVector than another one, can replace it or not
*/
moeoEpsilonHyperboxArchive(moeoObjectiveVectorComparator < ObjectiveVector > & _comparator, std::vector<double> _epsilon, bool _replace=true) : moeoArchive < MOEOT >(_comparator, _replace), epsilon(_epsilon), bounds(0.0, 1.0), normalizer(bounds, 1.0)
{}
/**
* Default Ctor
* @param _epsilon the vector contains epsilon values for each objective
* @param _replace boolean which determine if a solution with the same objectiveVector than another one, can replace it or not
*/
moeoEpsilonHyperboxArchive(std::vector<double> _epsilon, bool _replace=true) : moeoArchive < MOEOT >(paretoComparator, _replace), epsilon(_epsilon), bounds(0.0, 1.0), normalizer(bounds, 1.0)
{}
/**
* Updates the archive with a given individual _moeo
* @param _moeo the given individual
* @return true if _moeo is non-dominated (and not if it is added to the archive)
*/
bool operator()(const MOEOT & _moeo)
{
bool res=false;
unsigned int i=0;
bool nonstop = true;
bool same = true;
int change = 0;
MOEOT removed;
//if the archive is empty, we accept automaticaly _moeo
if(size()==0){
push_back(_moeo);
ideal = _moeo.objectiveVector();
nadir = _moeo.objectiveVector();
res = true;
}
else{
//change bounds if necessary
change = changeBounds(_moeo);
//if change < 0, we have detected that _moeo is bad
//else there are 4 cases:
if(change >= 0){
//calculate the hyperbox corner of _moeo
ObjectiveVector corner, tmp;
corner=hyperbox(_moeo);
//test if _moeo hyperbox corner dominates a hyperbox corner of an element of the archive
while(nonstop && (i<size())){
same = true;
//calculate the hyperbox corner of the ieme element of the archive
tmp=hyperbox(operator[](i));
//CASE 1: _moeo epsilon-domine the ieme element of the archive
if(this->comparator(tmp, corner)){
std::cout << "ENTER CASE 1" << std::endl;
//test if bounds changed
//removed=operator[](i);
//delete the ieme element of the archive
if(i==size()-1)
pop_back();
else{
operator[](i)=back();
pop_back();
i--;
}
//changeBoundsByDeleting(removed);
res = true;
}//END CASE 1
//CASE 2: the ieme element of the archive epsilon-domine _moeo
else if(this->comparator(corner, tmp)){
std::cout << "ENTER CASE 2" << std::endl;
if(change == 1)
changeBoundsByDeleting(_moeo);
//we can stop
nonstop = false;
}//END CASE 2
// _moeo is no-epsilon-dominated by archive[i] and arhcive[i] is no-epsilon-dominated by _moeo
else{
//test if the hyperbox corner are the same
for(unsigned int j=0; j<corner.size(); j++)
same = same && (corner[j] == tmp[j]);
//CASE 3: _moeo is in the same hyperbox of archive[i]
if(same){
std::cout << "ENTER CASE 3" << std::endl;
// _moeo dominates archive[i]
if(this->comparator(operator[](i).objectiveVector(), _moeo.objectiveVector())){
if(i==size()-1)
pop_back();
else{
operator[](i)=back();
pop_back();
i--;
}
// removed=operator[](i);
// operator[](i) = _moeo;
// changeBoundsByDeleting(removed);
res=true;
}
// _moeo is dominated by archive[i]
else if(this->comparator(_moeo.objectiveVector(), operator[](i).objectiveVector())){
changeBoundsByDeleting(_moeo);
nonstop=false;
}
else{
//keep the one who have the shortest euclidian distance between the corner
moeoEuclideanDistance < MOEOT > dist;
double d1 = dist(_moeo.objectiveVector(), corner);
double d2 = dist(operator[](i).objectiveVector(), corner);
if(d1 <= d2){
if(i==size()-1)
pop_back();
else{
operator[](i)=back();
pop_back();
i--;
}
// removed=operator[](i);
// operator[](i) = _moeo;
// changeBoundsByDeleting(removed);
res=true;
}
else{
nonstop=false;
// changeBoundsByDeleting(_moeo);
res=true;
}
}
}//END CASE 3
}
i++;
}
//CASE 4: _moeo have is place in a empty hyperbox
if(nonstop){
std::cout << "ENTER CASE 4" << std::endl;
push_back(_moeo);
res=true;
recalculateBounds();
}//END CASE 4
}
else{
std::cout << "ENTER CASE 5" << std::endl;
}
}
return res;
}
/**
* Updates the archive with a given population _pop
* @param _pop the given population
* @return if an archive's element is non-dominated (and not if it is added to the archive)
*/
bool operator()(const eoPop < MOEOT > & _pop)
{
bool res, tmp = false;
for(unsigned int i=0; i<_pop.size(); i++){
tmp = (*this)(_pop[i]);
res = res || tmp;
}
return res;
}
/**
* get the nadir point
* @return ObjectiveVector corresponding to the nadir point
*/
ObjectiveVector getNadir(){
return nadir;
}
/**
* get the idealpoint
* @return ObjectiveVector corresponding to the ideal point
*/
ObjectiveVector getIdeal(){
return ideal;
}
void filtre(){
eoPop<MOEOT> pop;
for(int i=0; i<size(); i++)
pop.push_back(operator[](i));
for(int i=0; i<pop.size(); i++)
(*this)(pop[i]);
}
private:
/**
* calculate the hyperbox corner of _moeo
* @param _moeo the given individual
* @return the ObjectiveVector contains the hyperbox corner values
*/
ObjectiveVector hyperbox(const MOEOT & _moeo){
//normalize _moeo's objectiveVector
ObjectiveVector res;
res = normalizer(_moeo.objectiveVector());
// std::cout << "ObjectiveVector non normalise:"<< _moeo.objectiveVector() << std::endl;
// std::cout << "ObjectiveVector normalise:"<< res << std::endl;
//calculate the hyperbox corner
for(unsigned int i=0; i<ObjectiveVector::nObjectives(); i++){
if(ObjectiveVector::minimizing(i))
res[i] = floor(res[i]*1.0/epsilon[i]);
else
res[i] = ceil(res[i]*1.0/epsilon[i]);
}
// std::cout << "ObjectiveVector epsilone:" << res << std::endl;
return res;
}
/**
* changes ideal and nadir point if _moeo is out of bounds and is not bad
* @param _moeo the given individual
* @return if bounds changed or not (1 -> changed, 0 -> not changed, -1 -> _moeo is bad)
*/
int changeBounds(const MOEOT & _moeo){
// std::cout << "changebounds objVec: "<< _moeo.objectiveVector() << std::endl;
int res = 0;
//check if an objective is better than the corresponding of the current ideal point
for(unsigned int i=0; i<ObjectiveVector::nObjectives(); i++){
if(ObjectiveVector::minimizing(i)){
if(_moeo.objectiveVector()[i] < ideal[i]){
ideal[i]=_moeo.objectiveVector()[i];
res = 1;
}
}
else{
if(_moeo.objectiveVector()[i] > ideal[i]){
ideal[i]=_moeo.objectiveVector()[i];
res = 1;
}
}
}
//check if an objective is worst than the corresponding of the current nadir point
for(unsigned int i=0; i<ObjectiveVector::nObjectives(); i++){
if(ObjectiveVector::minimizing(i)){
if(_moeo.objectiveVector()[i] > nadir[i]){
if(res == 1)
nadir[i]=_moeo.objectiveVector()[i];
else
res = -1; // no objective is better than the ideal and some are worst than nadir -> _moeo is bad
}
}
else{
if(_moeo.objectiveVector()[i] < nadir[i]){
if(res == 1)
nadir[i]=_moeo.objectiveVector()[i];
else
res = -1; // no objective is better than the ideal and some are worst than nadir -> _moeo is bad
}
}
}
//If bounds are changed, change the scale of normalizer
if(res == 1){
ObjectiveVector mini;
ObjectiveVector maxi;
for(unsigned int i=0; i<ObjectiveVector::nObjectives(); i++){
mini[i]=std::min(ideal[i], nadir[i]);
maxi[i]=std::max(ideal[i], nadir[i]);
}
normalizer.update_by_min_max(mini, maxi);
}
// std::cout << "change nadir: " << nadir << std::endl;
// std::cout << "change ideal: " << ideal << std::endl;
// std::cout << "res: " << res << std::endl;
return res;
}
/**
* when a element is deleting, change the bounds if neccesary.
* @param _moeo the deleted individual
*/
void changeBoundsByDeleting(const MOEOT & _moeo){
for(unsigned int i=0; i< ObjectiveVector::nObjectives(); i++){
if((_moeo.objectiveVector()[i]==nadir[i]) || (_moeo.objectiveVector()[i]==ideal[i]) )
return recalculateBounds();
}
}
/**
* recalculate ideal and nadir point and change scale of normalizer
*/
void recalculateBounds(){
ObjectiveVector tmp;
ideal=operator[](0).objectiveVector();
nadir=operator[](0).objectiveVector();
if (size() > 1){
for(unsigned int i=0; i< ObjectiveVector::nObjectives(); i++){
for(unsigned int j=1; j<size(); j++){
tmp=operator[](j).objectiveVector();
if(ObjectiveVector::minimizing(i)){
if(tmp[i] < ideal[i])
ideal[i] = tmp[i];
else if(tmp[i] > nadir[i])
nadir[i] = tmp[i];
}
else{
if(tmp[i] > ideal[i]){
ideal[i] = tmp[i];
}
else if(tmp[i] < nadir[i]){
nadir[i] = tmp[i];
}
}
}
}
}
ObjectiveVector mini;
ObjectiveVector maxi;
for(unsigned int i=0; i<ObjectiveVector::nObjectives(); i++){
mini[i]=std::min(ideal[i], nadir[i]);
maxi[i]=std::max(ideal[i], nadir[i]);
}
normalizer.update_by_min_max(mini, maxi);
}
/** A moeoObjectiveVectorComparator based on Pareto dominance (used as default) */
moeoParetoObjectiveVectorComparator < ObjectiveVector > paretoComparator;
/** epsilon values */
std::vector <double> epsilon;
/** ideal point of the archive */
ObjectiveVector ideal;
/** nadir point of the archive */
ObjectiveVector nadir;
/** bounds use by default to initialize the normalizer */
eoRealInterval bounds;
/** the objective vector normalizer */
moeoObjectiveVectorNormalizer <MOEOT> normalizer;
};
#endif /*MOEOEPSILONBOXARCHIVE_H_*/

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