175 lines
6.9 KiB
C++
175 lines
6.9 KiB
C++
/*
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* <moeoFrontByFrontCrowdingDiversityAssignment.h>
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* Copyright (C) DOLPHIN Project-Team, INRIA Futurs, 2006-2009
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* (C) OPAC Team, LIFL, 2002-2009
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*
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* Arnaud Liefooghe, Waldo Cancino
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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 MOEOFRONTBYFRONTCROWDINGDIVERSITYASSIGNMENT2_H_
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#define MOEOFRONTBYFRONTCROWDINGDIVERSITYASSIGNMENT2_H_
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#include <diversity/moeoCrowdingDiversityAssignment.h>
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#include <comparator/moeoFitnessThenDiversityComparator.h>
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#include <comparator/moeoPtrComparator.h>
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/**
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* Diversity assignment sheme based on crowding proposed 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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* Tis strategy assigns diversity values FRONT BY FRONT. It is, for instance, used in NSGA-II.
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*/
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template < class MOEOT >
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class moeoFrontByFrontCrowdingDiversityAssignment : public moeoCrowdingDiversityAssignment < 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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* @warning NOT IMPLEMENTED, DO NOTHING !
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* Updates the diversity 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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* @warning NOT IMPLEMENTED, DO NOTHING !
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*/
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void updateByDeleting(eoPop < MOEOT > & _pop, ObjectiveVector & _objVec)
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{
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std::cout << "WARNING : updateByDeleting not implemented in moeoFrontByFrontCrowdingDistanceDiversityAssignment" << std::endl;
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}
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private:
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using moeoCrowdingDiversityAssignment < MOEOT >::inf;
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using moeoCrowdingDiversityAssignment < MOEOT >::tiny;
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/**
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* Sets the distance values
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* @param _pop the population
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*/
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void setDistances (eoPop <MOEOT> & _pop)
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{
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unsigned int a,b;
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double min, max, distance;
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unsigned int nObjectives = MOEOT::ObjectiveVector::nObjectives();
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// set diversity to 0 for every individual
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for (unsigned int i=0; i<_pop.size(); i++)
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{
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_pop[i].diversity(0.0);
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}
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// sort the whole pop according to fitness values
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moeoFitnessThenDiversityComparator < MOEOT > fitnessComparator;
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std::vector<MOEOT *> sortedptrpop;
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sortedptrpop.resize(_pop.size());
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// due to intensive sort operations for this diversity assignment,
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// it is more efficient to perform sorts using only pointers to the
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// population members in order to avoid copy of individuals
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for(int i=0; i< _pop.size(); i++) sortedptrpop[i] = & (_pop[i]);
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//sort the pointers to population members
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moeoPtrComparator<MOEOT> cmp2( fitnessComparator);
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std::sort(sortedptrpop.begin(), sortedptrpop.end(), cmp2);
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// compute the crowding distance values for every individual "front" by "front" (front : from a to b)
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a = 0; // the front starts at a
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while (a < _pop.size())
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{
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b = lastIndex(sortedptrpop,a); // the front ends at b
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//b = lastIndex(_pop,a); // the front ends at b
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// if there is less than 2 individuals in the front...
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if ((b-a) < 2)
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{
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for (unsigned int i=a; i<=b; i++)
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{
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sortedptrpop[i]->diversity(inf());
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//_pop[i].diversity(inf());
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}
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}
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// else...
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else
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{
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// for each objective
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for (unsigned int obj=0; obj<nObjectives; obj++)
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{
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// sort in the descending order using the values of the objective 'obj'
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moeoOneObjectiveComparator < MOEOT > objComp(obj);
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moeoPtrComparator<MOEOT> cmp2( objComp );
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std::sort(sortedptrpop.begin(), sortedptrpop.end(), cmp2);
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// min & max
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min = (sortedptrpop[b])->objectiveVector()[obj];
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max = (sortedptrpop[a])->objectiveVector()[obj];
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// avoid extreme case
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if (min == max)
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{
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min -= tiny();
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max += tiny();
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}
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// set the diversity value to infiny for min and max
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sortedptrpop[a]->diversity(inf());
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sortedptrpop[b]->diversity(inf());
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// set the diversity values for the other individuals
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for (unsigned int i=a+1; i<b; i++)
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{
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distance = ( sortedptrpop[i-1]->objectiveVector()[obj] - sortedptrpop[i+1]->objectiveVector()[obj] ) / (max-min);
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sortedptrpop[i]->diversity(sortedptrpop[i]->diversity() + distance);
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}
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}
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}
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// go to the next front
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a = b+1;
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}
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}
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/**
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* Returns the index of the last individual having the same fitness value than _pop[_start]
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* @param _pop the vector of pointers to population individuals
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* @param _start the index to start from
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*/
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unsigned int lastIndex (std::vector<MOEOT *> & _pop, unsigned int _start)
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{
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unsigned int i=_start;
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while ( (i<_pop.size()-1) && (_pop[i]->fitness()==_pop[i+1]->fitness()) )
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{
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i++;
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}
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return i;
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}
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};
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#endif /*MOEOFRONTBYFRONTCROWDINGDIVERSITYASSIGNMENT_H_*/
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