Migration from SVN

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quemy 2012-08-30 11:30:11 +02:00
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######################################################################################
### 0) Include subdirectories
######################################################################################
add_subdirectory(doc)
add_subdirectory(src)
if(ENABLE_CMAKE_TESTING)
add_subdirectory(test)
endif(ENABLE_CMAKE_TESTING)
if(ENABLE_CMAKE_EXAMPLE)
if(${CMAKE_VERBOSE_MAKEFILE})
message("MOEO Examples :")
endif(${CMAKE_VERBOSE_MAKEFILE})
add_subdirectory(tutorial)
endif(ENABLE_CMAKE_EXAMPLE)

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######################################################################################
### 0) Documentation
######################################################################################
if(DOXYGEN_FOUND)
# Directory where the generation will be launched
set(MOEO_DOC_DIR ${CMAKE_CURRENT_BINARY_DIR} CACHE PATH "Documentation directory")
# Name of the doxygene configuration file
set(MOEO_DOC_CONFIG_FILE "moeo.doxyfile" CACHE PATH "Documentation configuration file")
if(DOXYGEN_EXECUTABLE)
# Creating the custom target
if(UNIX AND NOT ${CMAKE_VERBOSE_MAKEFILE})
add_custom_target(doc-moeo
COMMAND ${DOXYGEN_EXECUTABLE} ${MOEO_DOC_CONFIG_FILE} 2> /dev/null > /dev/null
WORKING_DIRECTORY ${CMAKE_CURRENT_BINARY_DIR}
)
else(UNIX AND NOT ${CMAKE_VERBOSE_MAKEFILE})
add_custom_target(doc-moeo
COMMAND ${DOXYGEN_EXECUTABLE} ${MOEO_DOC_CONFIG_FILE}
WORKING_DIRECTORY ${CMAKE_CURRENT_BINARY_DIR}
)
endif(UNIX AND NOT ${CMAKE_VERBOSE_MAKEFILE})
endif(DOXYGEN_EXECUTABLE)
configure_file("${CMAKE_CURRENT_SOURCE_DIR}/${MOEO_DOC_CONFIG_FILE}.cmake"
"${MOEO_DOC_DIR}/${MOEO_DOC_CONFIG_FILE}")
install(
DIRECTORY ${CMAKE_CURRENT_BINARY_DIR}
DESTINATION local/share${INSTALL_SUB_DIR}/moeo COMPONENT doc
PATTERN "CMakeFiles" EXCLUDE
PATTERN "cmake_install.cmake" EXCLUDE
PATTERN "CTestTestfile.cmake" EXCLUDE
PATTERN "Makefile" EXCLUDE
PATTERN "moeo.cfg" EXCLUDE
PATTERN "moeo.doxytag" EXCLUDE
)
else(DOXYGEN_FOUND)
message(STATUS "Unable to generate the documentation, Doxygen package not found")
endif(DOXYGEN_FOUND)

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/** @mainpage Welcome to ParadisEO-MOEO
@section Introduction
ParadisEO-MOEO is a white-box object-oriented generic framework dedicated to the flexible design of evolutionary multi-objective algorithms.
This paradigm-free software embeds some features and techniques for Pareto-based resolution and
aims to provide a set of classes allowing to ease and speed up the development of computationally efficient programs.
It is based on a clear conceptual distinction between the solution methods and the multi-objective problems they are intended to solve.
This separation confers a maximum design and code reuse.
ParadisEO-MOEO provides a broad range of archive-related features (such as elitism or performance metrics)
and the most common Pareto-based fitness assignment strategies (MOGA, NSGA, SPEA, IBEA and more). Dominance-based Local Search are also available.
Furthermore, parallel and distributed models as well as hybridization mechanisms can be applied to an algorithm designed within ParadisEO-MOEO
using the whole version of ParadisEO.
@section tutorials Tutorials
Tutorials for ParadisEO-MOEO are available in the "Tutorials section" of the <a href="http://paradiseo.gforge.inria.fr">ParadisEO website</a>.
@section Installation
The installation procedure of the package is detailed in the README file in the top-directory of the source-tree.
@section Design
For an introduction to the design of ParadisEO-MOEO,
you can look at the <a href="http://paradiseo.gforge.inria.fr">ParadisEO website</a>.
@section LICENSE
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
*/
/** @page webpages Related webpages
- ParadisEO <a href="http://paradiseo.gforge.inria.fr">homepage</a>
- INRIA GForge <a href="http://gforge.inria.fr/projects/paradiseo/">project page</a>
- <a href="../../README">README</a>
*/

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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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/*
* <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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/*
* <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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/*
* <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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