from moeoFastNonDominantedSortingFitnessAssignment to moeoDominanceDepthFitnessAssignment
git-svn-id: svn://scm.gforge.inria.fr/svnroot/paradiseo@1269 331e1502-861f-0410-8da2-ba01fb791d7f
This commit is contained in:
liefooga
parent
bc932bb89d
commit
b32c1704e8
9 changed files with 34 additions and 42 deletions
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@ -1,7 +1,7 @@
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/*
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* <moeoNSGA.h>
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* Copyright (C) DOLPHIN Project-Team, INRIA Futurs, 2006-2007
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* (C) OPAC Team, LIFL, 2002-2007
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* Copyright (C) DOLPHIN Project-Team, INRIA Futurs, 2006-2008
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* (C) OPAC Team, LIFL, 2002-2008
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*
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* Arnaud Liefooghe
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*
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@ -48,7 +48,7 @@
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#include <eoSGAGenOp.h>
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#include <algo/moeoEA.h>
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#include <diversity/moeoFrontByFrontSharingDiversityAssignment.h>
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#include <fitness/moeoFastNonDominatedSortingFitnessAssignment.h>
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#include <fitness/moeoDominanceDepthFitnessAssignment.h>
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#include <replacement/moeoElitistReplacement.h>
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#include <selection/moeoDetTournamentSelect.h>
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@ -204,7 +204,7 @@ protected:
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/** breeder */
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eoBreed < MOEOT > & breed;
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/** fitness assignment used in NSGA-II */
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moeoFastNonDominatedSortingFitnessAssignment < MOEOT > fitnessAssignment;
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moeoDominanceDepthFitnessAssignment < MOEOT > fitnessAssignment;
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/** diversity assignment used in NSGA-II */
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moeoFrontByFrontSharingDiversityAssignment < MOEOT > diversityAssignment;
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/** elitist replacement */
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@ -1,7 +1,7 @@
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/*
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* <moeoNSGAII.h>
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* Copyright (C) DOLPHIN Project-Team, INRIA Futurs, 2006-2007
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* (C) OPAC Team, LIFL, 2002-2007
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* Copyright (C) DOLPHIN Project-Team, INRIA Futurs, 2006-2008
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* (C) OPAC Team, LIFL, 2002-2008
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*
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* Arnaud Liefooghe
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*
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@ -49,7 +49,7 @@
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#include <eoSGAGenOp.h>
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#include <algo/moeoEA.h>
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#include <diversity/moeoFrontByFrontCrowdingDiversityAssignment.h>
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#include <fitness/moeoFastNonDominatedSortingFitnessAssignment.h>
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#include <fitness/moeoDominanceDepthFitnessAssignment.h>
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#include <replacement/moeoElitistReplacement.h>
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#include <selection/moeoDetTournamentSelect.h>
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@ -198,8 +198,8 @@ protected:
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eoGeneralBreeder < MOEOT > genBreed;
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/** breeder */
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eoBreed < MOEOT > & breed;
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/** fitness assignment used in NSGA-II */
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moeoFastNonDominatedSortingFitnessAssignment < MOEOT > fitnessAssignment;
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/** fitness assignment used in NSGA */
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moeoDominanceDepthFitnessAssignment < MOEOT > fitnessAssignment;
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/** diversity assignment used in NSGA-II */
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moeoFrontByFrontCrowdingDiversityAssignment < MOEOT > diversityAssignment;
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/** elitist replacement */
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@ -59,7 +59,7 @@
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#include <diversity/moeoFrontByFrontSharingDiversityAssignment.h>
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#include <fitness/moeoDummyFitnessAssignment.h>
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#include <fitness/moeoExpBinaryIndicatorBasedFitnessAssignment.h>
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#include <fitness/moeoFastNonDominatedSortingFitnessAssignment.h>
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#include <fitness/moeoDominanceDepthFitnessAssignment.h>
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#include <fitness/moeoFitnessAssignment.h>
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#include <metric/moeoAdditiveEpsilonBinaryMetric.h>
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#include <metric/moeoHypervolumeBinaryMetric.h>
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@ -93,8 +93,8 @@ moeoEA < MOEOT > & do_make_ea_moeo(eoParser & _parser, eoState & _state, eoEvalF
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/* the fitness assignment strategy */
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std::string & fitnessParam = _parser.createParam(std::string("FastNonDominatedSorting"), "fitness",
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"Fitness assignment scheme: Dummy, FastNonDominatedSorting or IndicatorBased", 'F',
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std::string & fitnessParam = _parser.createParam(std::string("DomDepth"), "fitness",
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"Fitness assignment scheme: Dummy, DomDepth or IndicatorBased", 'F',
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"Evolution Engine").value();
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std::string & indicatorParam = _parser.createParam(std::string("Epsilon"), "indicator",
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"Binary indicator for IndicatorBased: Epsilon, Hypervolume", 'i',
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@ -108,9 +108,9 @@ moeoEA < MOEOT > & do_make_ea_moeo(eoParser & _parser, eoState & _state, eoEvalF
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{
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fitnessAssignment = new moeoDummyFitnessAssignment < MOEOT> ();
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}
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else if (fitnessParam == std::string("FastNonDominatedSorting"))
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else if (fitnessParam == std::string("DomDepth"))
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{
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fitnessAssignment = new moeoFastNonDominatedSortingFitnessAssignment < MOEOT> ();
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fitnessAssignment = new moeoDominanceDepthFitnessAssignment < MOEOT> ();
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}
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else if (fitnessParam == std::string("IndicatorBased"))
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{
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@ -0,0 +1,265 @@
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/*
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* <moeoDominanceDepthFitnessAssignment.h>
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* Copyright (C) DOLPHIN Project-Team, INRIA Futurs, 2006-2008
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* (C) OPAC Team, LIFL, 2002-2008
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*
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* Arnaud Liefooghe
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*
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* This software is governed by the CeCILL license under French law and
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* abiding by the rules of distribution of free software. You can use,
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* modify and/ or redistribute the software under the terms of the CeCILL
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* license as circulated by CEA, CNRS and INRIA at the following URL
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* "http://www.cecill.info".
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*
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* As a counterpart to the access to the source code and rights to copy,
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* modify and redistribute granted by the license, users are provided only
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* with a limited warranty and the software's author, the holder of the
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* economic rights, and the successive licensors have only limited liability.
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*
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* In this respect, the user's attention is drawn to the risks associated
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* with loading, using, modifying and/or developing or reproducing the
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* software by the user in light of its specific status of free software,
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* that may mean that it is complicated to manipulate, and that also
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* therefore means that it is reserved for developers and experienced
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* professionals having in-depth computer knowledge. Users are therefore
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* encouraged to load and test the software's suitability as regards their
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* requirements in conditions enabling the security of their systems and/or
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* data to be ensured and, more generally, to use and operate it in the
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* same conditions as regards security.
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* The fact that you are presently reading this means that you have had
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* knowledge of the CeCILL license and that you accept its terms.
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*
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* ParadisEO WebSite : http://paradiseo.gforge.inria.fr
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* Contact: paradiseo-help@lists.gforge.inria.fr
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*
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*/
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//-----------------------------------------------------------------------------
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#ifndef MOEODOMINANCEDEPTHFITNESSASSIGNMENT_H_
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#define MOEODOMINANCEDEPTHFITNESSASSIGNMENT_H_
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#include <vector>
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#include <eoPop.h>
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#include <comparator/moeoObjectiveObjectiveVectorComparator.h>
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#include <comparator/moeoObjectiveVectorComparator.h>
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#include <comparator/moeoParetoObjectiveVectorComparator.h>
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#include <fitness/moeoDominanceBasedFitnessAssignment.h>
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/**
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* Fitness assignment sheme based on Pareto-dominance count proposed in:
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* N. Srinivas, K. Deb, "Multiobjective Optimization Using Nondominated Sorting in Genetic Algorithms", Evolutionary Computation vol. 2, no. 3, pp. 221-248 (1994)
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* and in:
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* K. Deb, A. Pratap, S. Agarwal, T. Meyarivan, "A Fast and Elitist Multi-Objective Genetic Algorithm: NSGA-II", IEEE Transactions on Evolutionary Computation, vol. 6, no. 2 (2002).
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* This strategy is, for instance, used in NSGA and NSGA-II.
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*/
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template < class MOEOT >
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class moeoDominanceDepthFitnessAssignment : public moeoDominanceBasedFitnessAssignment < MOEOT >
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{
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public:
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/** the objective vector type of the solutions */
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typedef typename MOEOT::ObjectiveVector ObjectiveVector;
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/**
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* Default ctor
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*/
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moeoDominanceDepthFitnessAssignment() : comparator(paretoComparator)
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{}
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/**
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* Ctor where you can choose your own way to compare objective vectors
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* @param _comparator the functor used to compare objective vectors
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*/
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moeoDominanceDepthFitnessAssignment(moeoObjectiveVectorComparator < ObjectiveVector > & _comparator) : comparator(_comparator)
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{}
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/**
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* Sets the fitness values for every solution contained in the population _pop
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* @param _pop the population
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*/
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void operator()(eoPop < MOEOT > & _pop)
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{
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// number of objectives for the problem under consideration
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unsigned int nObjectives = MOEOT::ObjectiveVector::nObjectives();
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if (nObjectives == 1)
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{
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// one objective
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oneObjective(_pop);
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}
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else if (nObjectives == 2)
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{
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// two objectives (the two objectives function is still to implement)
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mObjectives(_pop);
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}
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else if (nObjectives > 2)
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{
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// more than two objectives
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mObjectives(_pop);
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}
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else
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{
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// problem with the number of objectives
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throw std::runtime_error("Problem with the number of objectives in moeoNonDominatedSortingFitnessAssignment");
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}
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// a higher fitness is better, so the values need to be inverted
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double max = _pop[0].fitness();
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for (unsigned int i=1 ; i<_pop.size() ; i++)
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{
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max = std::max(max, _pop[i].fitness());
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}
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for (unsigned int i=0 ; i<_pop.size() ; i++)
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{
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_pop[i].fitness(max - _pop[i].fitness());
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}
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}
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/**
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* Updates the fitness values of the whole population _pop by taking the deletion of the objective vector _objVec into account.
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* @param _pop the population
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* @param _objVec the objective vector
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*/
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void updateByDeleting(eoPop < MOEOT > & _pop, ObjectiveVector & _objVec)
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{
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for (unsigned int i=0; i<_pop.size(); i++)
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{
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// if _pop[i] is dominated by _objVec
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if ( comparator(_pop[i].objectiveVector(), _objVec) )
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{
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_pop[i].fitness(_pop[i].fitness()+1);
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}
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}
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}
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private:
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/** Functor to compare two objective vectors */
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moeoObjectiveVectorComparator < ObjectiveVector > & comparator;
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/** Functor to compare two objective vectors according to Pareto dominance relation */
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moeoParetoObjectiveVectorComparator < ObjectiveVector > paretoComparator;
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/** Functor allowing to compare two solutions according to their first objective value, then their second, and so on. */
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class ObjectiveComparator : public moeoComparator < MOEOT >
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{
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public:
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/**
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* Returns true if _moeo1 < _moeo2 on the first objective, then on the second, and so on
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* @param _moeo1 the first solution
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* @param _moeo2 the second solution
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*/
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const bool operator()(const MOEOT & _moeo1, const MOEOT & _moeo2)
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{
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return cmp(_moeo1.objectiveVector(), _moeo2.objectiveVector());
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}
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private:
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/** the corresponding comparator for objective vectors */
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moeoObjectiveObjectiveVectorComparator < ObjectiveVector > cmp;
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}
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objComparator;
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/**
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* Sets the fitness values for mono-objective problems
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* @param _pop the population
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*/
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void oneObjective (eoPop < MOEOT > & _pop)
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{
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// sorts the population in the ascending order
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std::sort(_pop.begin(), _pop.end(), objComparator);
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// assign fitness values
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unsigned int rank = 1;
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_pop[_pop.size()-1].fitness(rank);
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for (unsigned int i=_pop.size()-2; i>=0; i--)
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{
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if (_pop[i].objectiveVector() != _pop[i+1].objectiveVector())
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{
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rank++;
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}
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_pop[i].fitness(rank);
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}
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}
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/**
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* Sets the fitness values for bi-objective problems with a complexity of O(n log n), where n stands for the population size
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* @param _pop the population
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*/
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void twoObjectives (eoPop < MOEOT > & _pop)
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{
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//... TO DO !
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}
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/**
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* Sets the fitness values for problems with more than two objectives with a complexity of O(n² log n), where n stands for the population size
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* @param _pop the population
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*/
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void mObjectives (eoPop < MOEOT > & _pop)
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{
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// S[i] = indexes of the individuals dominated by _pop[i]
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std::vector < std::vector<unsigned int> > S(_pop.size());
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// n[i] = number of individuals that dominate the individual _pop[i]
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std::vector < unsigned int > n(_pop.size(), 0);
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// fronts: F[i] = indexes of the individuals contained in the ith front
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std::vector < std::vector<unsigned int> > F(_pop.size()+2);
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// used to store the number of the first front
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F[1].reserve(_pop.size());
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for (unsigned int p=0; p<_pop.size(); p++)
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{
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for (unsigned int q=0; q<_pop.size(); q++)
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{
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// if q is dominated by p
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if ( comparator(_pop[q].objectiveVector(), _pop[p].objectiveVector()) )
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{
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// add q to the set of solutions dominated by p
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S[p].push_back(q);
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}
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// if p is dominated by q
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else if ( comparator(_pop[p].objectiveVector(), _pop[q].objectiveVector()) )
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{
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// increment the domination counter of p
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n[p]++;
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}
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}
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// if no individual dominates p
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if (n[p] == 0)
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{
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// p belongs to the first front
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_pop[p].fitness(1);
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F[1].push_back(p);
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}
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}
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// front counter
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unsigned int counter=1;
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unsigned int p,q;
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while (! F[counter].empty())
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{
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// used to store the number of the next front
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F[counter+1].reserve(_pop.size());
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for (unsigned int i=0; i<F[counter].size(); i++)
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{
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p = F[counter][i];
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for (unsigned int j=0; j<S[p].size(); j++)
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{
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q = S[p][j];
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n[q]--;
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// if no individual dominates q anymore
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if (n[q] == 0)
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{
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// q belongs to the next front
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_pop[q].fitness(counter+1);
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F[counter+1].push_back(q);
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}
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}
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}
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counter++;
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}
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}
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} ;
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#endif /*MOEODOMINANCEDEPTHFITNESSASSIGNMENT_H_*/
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@ -102,10 +102,10 @@
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#include <fitness/moeoDominanceBasedFitnessAssignment.h>
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#include <fitness/moeoDominanceCountFitnessAssignment.h>
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#include <fitness/moeoDominanceCountRankingFitnessAssignment.h>
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#include <fitness/moeoDominanceDepthFitnessAssignment.h>
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#include <fitness/moeoDominanceRankFitnessAssignment.h>
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#include <fitness/moeoDummyFitnessAssignment.h>
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#include <fitness/moeoExpBinaryIndicatorBasedFitnessAssignment.h>
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#include <fitness/moeoFastNonDominatedSortingFitnessAssignment.h>
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#include <fitness/moeoFitnessAssignment.h>
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#include <fitness/moeoIndicatorBasedFitnessAssignment.h>
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#include <fitness/moeoScalarFitnessAssignment.h>
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@ -44,7 +44,6 @@ SET (TEST_LIST
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t-moeoFitnessThenDiversityComparator
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t-moeoAchievementFitnessAssignment
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t-moeoExpBinaryIndicatorBasedFitnessAssignment
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t-moeoFastNonDominatedSortingFitnessAssignment
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t-moeoCrowdingDiversityAssignment
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t-moeoSharingDiversityAssignment
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t-moeoIBEA
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@ -56,6 +55,7 @@ SET (TEST_LIST
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t-moeoDominanceCountFitnessAssignment
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t-moeoDominanceRankFitnessAssignment
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t-moeoDominanceCountRankingFitnessAssignment
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t-moeoDominanceDepthFitnessAssignment
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t-moeoNearestNeighborDiversityAssignment
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t-moeoSPEA2Archive
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t-moeoSPEA2
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@ -0,0 +1,142 @@
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/*
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* <t-moeoDominanceDepthFitnessAssignment.cpp>
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* Copyright (C) DOLPHIN Project-Team, INRIA Futurs, 2006-2008
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||||
* (C) OPAC Team, LIFL, 2002-2008
|
||||
*
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||||
* Arnaud Liefooghe
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||||
*
|
||||
* 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
|
||||
*
|
||||
*/
|
||||
//-----------------------------------------------------------------------------
|
||||
// t-moeoDominanceDepthFitnessAssignment.cpp
|
||||
//-----------------------------------------------------------------------------
|
||||
|
||||
#include <eo>
|
||||
#include <moeo>
|
||||
|
||||
//-----------------------------------------------------------------------------
|
||||
|
||||
class ObjectiveVectorTraits : public moeoObjectiveVectorTraits
|
||||
{
|
||||
public:
|
||||
static bool minimizing (int i)
|
||||
{
|
||||
return true;
|
||||
}
|
||||
static bool maximizing (int i)
|
||||
{
|
||||
return false;
|
||||
}
|
||||
static unsigned int nObjectives ()
|
||||
{
|
||||
return 2;
|
||||
}
|
||||
};
|
||||
|
||||
typedef moeoRealObjectiveVector < ObjectiveVectorTraits > ObjectiveVector;
|
||||
|
||||
typedef MOEO < ObjectiveVector, double, double > Solution;
|
||||
|
||||
//-----------------------------------------------------------------------------
|
||||
|
||||
int main()
|
||||
{
|
||||
std::cout << "[moeoDominanceDepthFitnessAssignment]\t=>\t";
|
||||
|
||||
// objective vectors
|
||||
ObjectiveVector obj0, obj1, obj2, obj3, obj4, obj5;
|
||||
obj0[0] = 2;
|
||||
obj0[1] = 5;
|
||||
obj1[0] = 3;
|
||||
obj1[1] = 3;
|
||||
obj2[0] = 4;
|
||||
obj2[1] = 1;
|
||||
obj3[0] = 5;
|
||||
obj3[1] = 5;
|
||||
obj4[0] = 5;
|
||||
obj4[1] = 1;
|
||||
obj5[0] = 3;
|
||||
obj5[1] = 3;
|
||||
|
||||
// population
|
||||
eoPop < Solution > pop;
|
||||
pop.resize(6);
|
||||
pop[0].objectiveVector(obj0); // class 1
|
||||
pop[1].objectiveVector(obj1); // class 1
|
||||
pop[2].objectiveVector(obj2); // class 1
|
||||
pop[3].objectiveVector(obj3); // class 3
|
||||
pop[4].objectiveVector(obj4); // class 2
|
||||
pop[5].objectiveVector(obj5); // class 1
|
||||
|
||||
// fitness assignment
|
||||
moeoDominanceDepthFitnessAssignment< Solution > fitnessAssignment;
|
||||
fitnessAssignment(pop);
|
||||
|
||||
// pop[0]
|
||||
if (pop[0].fitness() != 2.0)
|
||||
{
|
||||
std::cout << "ERROR (bad fitness for pop[0])" << std::endl;
|
||||
return EXIT_FAILURE;
|
||||
}
|
||||
// pop[1]
|
||||
if (pop[1].fitness() != 2.0)
|
||||
{
|
||||
std::cout << "ERROR (bad fitness for pop[1])" << std::endl;
|
||||
return EXIT_FAILURE;
|
||||
}
|
||||
// pop[2]
|
||||
if (pop[2].fitness() != 2.0)
|
||||
{
|
||||
std::cout << "ERROR (bad fitness for pop[2])" << std::endl;
|
||||
return EXIT_FAILURE;
|
||||
}
|
||||
// pop[3]
|
||||
if (pop[3].fitness() != 0.0)
|
||||
{
|
||||
std::cout << "ERROR (bad fitness for pop[3]) " << std::endl;
|
||||
return EXIT_FAILURE;
|
||||
}
|
||||
// pop[4]
|
||||
if (pop[4].fitness() != 1.0)
|
||||
{
|
||||
std::cout << "ERROR (bad fitness for pop[4])" << std::endl;
|
||||
return EXIT_FAILURE;
|
||||
}
|
||||
// pop[5]
|
||||
if (pop[5].fitness() != 2.0)
|
||||
{
|
||||
std::cout << "ERROR (bad fitness for pop[5])" << std::endl;
|
||||
return EXIT_FAILURE;
|
||||
}
|
||||
|
||||
std::cout << "OK" << std::endl;
|
||||
return EXIT_SUCCESS;
|
||||
}
|
||||
|
||||
//-----------------------------------------------------------------------------
|
||||
|
|
@ -100,7 +100,7 @@ int main()
|
|||
eoRealInitBounded < Solution > init(bounds);
|
||||
eoPop < Solution > pop(20, init);
|
||||
eoGenContinue < Solution > term(20);
|
||||
moeoFastNonDominatedSortingFitnessAssignment < Solution > fitnessAssignment;
|
||||
moeoDominanceDepthFitnessAssignment < Solution > fitnessAssignment;
|
||||
moeoFrontByFrontCrowdingDiversityAssignment < Solution > diversityAssignment;
|
||||
moeoFitnessThenDiversityComparator < Solution > comparator;
|
||||
moeoDetTournamentSelect < Solution > selectOne(comparator, 2);
|
||||
|
|
|
|||
|
|
@ -46,14 +46,6 @@
|
|||
#include <make_op_FlowShop.h>
|
||||
// how to initialize the population
|
||||
#include <do/make_pop.h>
|
||||
// the stopping criterion
|
||||
#include <do/make_continue_moeo.h>
|
||||
// outputs (stats, population dumps, ...)
|
||||
#include <do/make_checkpoint_moeo.h>
|
||||
// evolution engine (selection and replacement)
|
||||
#include <do/make_ea_moeo.h>
|
||||
// simple call to the algo
|
||||
#include <do/make_run.h>
|
||||
// checks for help demand, and writes the status file and make_help; in libutils
|
||||
void make_help(eoParser & _parser);
|
||||
// definition of the representation
|
||||
|
|
@ -96,7 +88,7 @@ int main(int argc, char* argv[])
|
|||
moeoArchiveUpdater < FlowShop > updater(arch, pop);
|
||||
checkpoint.add(updater);
|
||||
// fitness assignment
|
||||
moeoFastNonDominatedSortingFitnessAssignment <FlowShop> fitnessAssignment;
|
||||
moeoDominanceDepthFitnessAssignment <FlowShop> fitnessAssignment;
|
||||
// diversity preservation
|
||||
moeoFrontByFrontCrowdingDiversityAssignment <FlowShop> diversityAssignment;
|
||||
// comparator
|
||||
|
|
|
|||
Loading…
Reference in a new issue