special two-objective case of dominance depth ranking in O(n log n)
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@ -1,38 +1,38 @@
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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
|
||||
* license as circulated by CEA, CNRS and INRIA at the following URL
|
||||
* "http://www.cecill.info".
|
||||
*
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||||
* 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.
|
||||
*
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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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* <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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*
|
||||
* 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
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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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@ -44,7 +44,7 @@
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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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#include <comparator/moeoPtrComparator.h>
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/**
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* Fitness assignment sheme based on Pareto-dominance count proposed in:
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@ -55,69 +55,69 @@
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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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{
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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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moeoDominanceDepthFitnessAssignment(bool _rm_equiv_flag_in_2D = false) : comparator(paretoComparator), rm_equiv_flag_in_2D(_rm_equiv_flag_in_2D)
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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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moeoDominanceDepthFitnessAssignment(moeoObjectiveVectorComparator < ObjectiveVector > & _comparator, bool _rm_equiv_flag_in_2D = true) : comparator(_comparator), rm_equiv_flag_in_2D(_rm_equiv_flag_in_2D)
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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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// 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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// one objective
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oneObjective(_pop);
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}
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else if (nObjectives == 2)
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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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// two objectives
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twoObjectives(_pop);
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}
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else if (nObjectives > 2)
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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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// more than two objectives
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mObjectives(_pop);
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}
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else
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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 moeoDominanceDepthFitnessAssignment");
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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 moeoDominanceDepthFitnessAssignment");
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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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// 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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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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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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_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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@ -125,141 +125,209 @@ class moeoDominanceDepthFitnessAssignment : public moeoDominanceBasedFitnessAssi
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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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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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// 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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_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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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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/** flag to remove equivament solutions */
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bool rm_equiv_flag_in_2D;
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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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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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* 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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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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return cmp(_moeo2.objectiveVector(), _moeo1.objectiveVector());
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}
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private:
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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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}
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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 (int i=_pop.size()-2; i>=0; i--)
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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[0].fitness(rank);
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for (unsigned int i=1; i<_pop.size(); i++)
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{
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if (_pop[i].objectiveVector() != _pop[i+1].objectiveVector())
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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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rank++;
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}
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_pop[i].fitness(rank);
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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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double value_obj1;
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unsigned int front;
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unsigned int last_front = 0;
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bool equiv_flag;
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// sort pointers to pop's individuals with respect to the first objective (0) in the reverse order
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std::vector<MOEOT *> sortedptrpop;
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sortedptrpop.resize(_pop.size());
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for(unsigned int i=0; i<_pop.size(); i++)
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{
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sortedptrpop[i] = & (_pop[i]);
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}
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moeoPtrComparator<MOEOT> cmp(objComparator);
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std::sort(sortedptrpop.begin(), sortedptrpop.end(), cmp);
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// compute an upper bound on the second objective (1)
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double max_obj1 = std::numeric_limits<double>::min();
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for(unsigned int i=0; i<_pop.size(); i++)
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{
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max_obj1 = std::max(max_obj1, _pop[i].objectiveVector()[1]);
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}
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max_obj1 += 1.0;
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// initialize a vector with the max_obj1 value everywhere
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std::vector<double> d(_pop.size(), max_obj1);
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// initialize fronts
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std::vector<std::vector<unsigned int> > fronts(_pop.size());
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// compute rank for each individual
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for(unsigned int i=0; i<sortedptrpop.size(); i++)
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{
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equiv_flag = false;
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// check for equivalent solutions and assign them to the worst front
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if (i>0)
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{
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if ( (rm_equiv_flag_in_2D) && (sortedptrpop[i]->objectiveVector() == sortedptrpop[i-1]->objectiveVector()) )
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{
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equiv_flag = true;
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fronts.back().push_back(i);
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}
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}
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if (!equiv_flag)
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{
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// the value of the second objective for the current solutions
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value_obj1 = sortedptrpop[i]->objectiveVector()[1];
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// if we maximize, take the opposite value
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if (MOEOT::ObjectiveVector::maximizing(1))
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value_obj1 = max_obj1 - value_obj1;
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// perform binary search (log n)
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std::vector<double>::iterator it = std::upper_bound(d.begin(), d.begin() + last_front, value_obj1);
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// retrieve the corresponding front
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front = (unsigned int)(it - d.begin());
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if (front == last_front)
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last_front++;
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// update
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*it = value_obj1;
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// add the solution to the corresponding front
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fronts[front].push_back(i);
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}
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}
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// assign the fitness value (rank) to each individual
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for (unsigned int i=0; i<fronts.size(); i++)
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{
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for (unsigned int j=0; j<fronts[i].size(); j++)
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{
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sortedptrpop[fronts[i][j]]->fitness(i+1);
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}
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}
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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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// 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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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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// 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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// 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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// 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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// 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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// 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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// 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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// 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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// 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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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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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
|
||||
_pop[q].fitness(counter+1);
|
||||
F[counter+1].push_back(q);
|
||||
// q belongs to the next front
|
||||
_pop[q].fitness(counter+1);
|
||||
F[counter+1].push_back(q);
|
||||
}
|
||||
}
|
||||
}
|
||||
counter++;
|
||||
counter++;
|
||||
}
|
||||
}
|
||||
|
||||
} ;
|
||||
|
||||
} ;
|
||||
|
||||
#endif /*MOEODOMINANCEDEPTHFITNESSASSIGNMENT_H_*/
|
||||
|
|
|
|||
Loading…
Add table
Add a link
Reference in a new issue