add diversity
git-svn-id: svn://scm.gforge.inria.fr/svnroot/paradiseo@375 331e1502-861f-0410-8da2-ba01fb791d7f
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6 changed files with 613 additions and 0 deletions
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// -*- mode: c++; c-indent-level: 4; c++-member-init-indent: 8; comment-column: 35; -*-
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//-----------------------------------------------------------------------------
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// moeoCrowdingDistanceDiversityAssignment.h
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// (c) OPAC Team (LIFL), Dolphin Project (INRIA), 2007
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/*
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This library...
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Contact: paradiseo-help@lists.gforge.inria.fr, http://paradiseo.gforge.inria.fr
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*/
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//-----------------------------------------------------------------------------
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#ifndef MOEOCROWDINGDISTANCEDIVERSITYASSIGNMENT_H_
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#define MOEOCROWDINGDISTANCEDIVERSITYASSIGNMENT_H_
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#include <eoPop.h>
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#include <comparator/moeoOneObjectiveComparator.h>
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#include <diversity/moeoDiversityAssignment.h>
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/**
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* Diversity assignment sheme based on crowding distance 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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*/
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template < class MOEOT >
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class moeoCrowdingDistanceDiversityAssignment : public moeoDiversityAssignment < 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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* Returns a big value (regarded as infinite)
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*/
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double inf() const
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{
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return std::numeric_limits<double>::max();
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}
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/**
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* Returns a very small value that can be used to avoid extreme cases (where the min bound == the max bound)
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*/
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double tiny() const
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{
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return 1e-6;
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}
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/**
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* Computes diversity 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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if (_pop.size() <= 2)
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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].diversity(inf());
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}
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}
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else
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{
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setDistances(_pop);
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}
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}
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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 moeoCrowdingDiversityAssignment" << std::endl;
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}
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protected:
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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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virtual void setDistances (eoPop < MOEOT > & _pop)
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{
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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
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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);
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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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// comparator
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moeoOneObjectiveComparator < MOEOT > objComp(obj);
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// sort
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std::sort(_pop.begin(), _pop.end(), objComp);
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// min & max
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min = _pop[0].objectiveVector()[obj];
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max = _pop[_pop.size()-1].objectiveVector()[obj];
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// set the diversity value to infiny for min and max
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_pop[0].diversity(inf());
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_pop[_pop.size()-1].diversity(inf());
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for (unsigned int i=1; i<_pop.size()-1; i++)
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{
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distance = (_pop[i+1].objectiveVector()[obj] - _pop[i-1].objectiveVector()[obj]) / (max-min);
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_pop[i].diversity(_pop[i].diversity() + distance);
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}
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}
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}
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};
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#endif /*MOEOCROWDINGDISTANCEDIVERSITYASSIGNMENT_H_*/
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// -*- mode: c++; c-indent-level: 4; c++-member-init-indent: 8; comment-column: 35; -*-
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//-----------------------------------------------------------------------------
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// moeoDiversityAssignment.h
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// (c) OPAC Team (LIFL), Dolphin Project (INRIA), 2007
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/*
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This library...
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Contact: paradiseo-help@lists.gforge.inria.fr, http://paradiseo.gforge.inria.fr
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*/
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//-----------------------------------------------------------------------------
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#ifndef MOEODIVERSITYASSIGNMENT_H_
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#define MOEODIVERSITYASSIGNMENT_H_
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#include <eoFunctor.h>
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#include <eoPop.h>
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/**
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* Functor that sets the diversity values of a whole population.
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*/
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template < class MOEOT >
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class moeoDiversityAssignment : public eoUF < eoPop < MOEOT > &, void >
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{
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public:
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/** The type for objective vector */
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typedef typename MOEOT::ObjectiveVector ObjectiveVector;
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/**
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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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*/
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virtual void updateByDeleting(eoPop < MOEOT > & _pop, ObjectiveVector & _objVec) = 0;
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/**
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* Updates the diversity values of the whole population _pop by taking the deletion of the individual _moeo into account.
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* @param _pop the population
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* @param _moeo the individual
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*/
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void updateByDeleting(eoPop < MOEOT > & _pop, MOEOT & _moeo)
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{
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updateByDeleting(_pop, _moeo.objectiveVector());
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}
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};
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#endif /*MOEODIVERSITYASSIGNMENT_H_*/
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// -*- mode: c++; c-indent-level: 4; c++-member-init-indent: 8; comment-column: 35; -*-
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//-----------------------------------------------------------------------------
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// moeoDummyDiversityAssignment.h
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// (c) OPAC Team (LIFL), Dolphin Project (INRIA), 2007
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/*
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This library...
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Contact: paradiseo-help@lists.gforge.inria.fr, http://paradiseo.gforge.inria.fr
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*/
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//-----------------------------------------------------------------------------
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#ifndef MOEODUMMYDIVERSITYASSIGNMENT_H_
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#define MOEODUMMYDIVERSITYASSIGNMENT_H_
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#include<diversity/moeoDiversityAssignment.h>
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/**
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* moeoDummyDiversityAssignment is a moeoDiversityAssignment that gives the value '0' as the individual's diversity for a whole population if it is invalid.
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*/
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template < class MOEOT >
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class moeoDummyDiversityAssignment : public moeoDiversityAssignment < MOEOT >
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{
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public:
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/** The type for objective vector */
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typedef typename MOEOT::ObjectiveVector ObjectiveVector;
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/**
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* Sets the diversity to '0' for every individuals of the population _pop if it is invalid
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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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for (unsigned int idx = 0; idx<_pop.size (); idx++)
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{
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if (_pop[idx].invalidDiversity())
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{
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// set the diversity to 0
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_pop[idx].diversity(0.0);
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}
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}
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}
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/**
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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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*/
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void updateByDeleting(eoPop < MOEOT > & _pop, ObjectiveVector & _objVec)
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{
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// nothing to do... ;-)
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}
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};
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#endif /*MOEODUMMYDIVERSITYASSIGNMENT_H_*/
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// -*- mode: c++; c-indent-level: 4; c++-member-init-indent: 8; comment-column: 35; -*-
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//-----------------------------------------------------------------------------
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// moeoFrontByFrontCrowdingDistanceDiversityAssignment.h
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// (c) OPAC Team (LIFL), Dolphin Project (INRIA), 2007
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/*
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This library...
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Contact: paradiseo-help@lists.gforge.inria.fr, http://paradiseo.gforge.inria.fr
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*/
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//-----------------------------------------------------------------------------
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#ifndef MOEOFRONTBYFRONTCROWDINGDISTANCEDIVERSITYASSIGNMENT_H_
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#define MOEOFRONTBYFRONTCROWDINGDISTANCEDIVERSITYASSIGNMENT_H_
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#include <diversity/moeoCrowdingDistanceDiversityAssignment.h>
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#include <comparator/moeoFitnessThenDiversityComparator.h>
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/**
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* Diversity assignment sheme based on crowding distance 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 moeoFrontByFrontCrowdingDistanceDiversityAssignment : public moeoCrowdingDistanceDiversityAssignment < 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 moeoCrowdingDistanceDiversityAssignment < MOEOT >::inf;
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using moeoCrowdingDistanceDiversityAssignment < 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::sort(_pop.begin(), _pop.end(), fitnessComparator);
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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(_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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_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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std::sort(_pop.begin()+a, _pop.begin()+b+1, objComp);
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// min & max
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min = _pop[b].objectiveVector()[obj];
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max = _pop[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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_pop[a].diversity(inf());
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_pop[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 = (_pop[i-1].objectiveVector()[obj] - _pop[i+1].objectiveVector()[obj]) / (max-min);
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_pop[i].diversity(_pop[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 population
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* @param _start the index to start from
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*/
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unsigned int lastIndex (eoPop < 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 /*MOEOFRONTBYFRONTCROWDINGDISTANCEDIVERSITYASSIGNMENT_H_*/
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// -*- mode: c++; c-indent-level: 4; c++-member-init-indent: 8; comment-column: 35; -*-
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//-----------------------------------------------------------------------------
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// moeoFrontByFrontSharingDiversityAssignment.h
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// (c) OPAC Team (LIFL), Dolphin Project (INRIA), 2007
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/*
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This library...
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Contact: paradiseo-help@lists.gforge.inria.fr, http://paradiseo.gforge.inria.fr
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*/
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//-----------------------------------------------------------------------------
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#ifndef MOEOFRONTBYFRONTSHARINGDIVERSITYASSIGNMENT_H_
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#define MOEOFRONTBYFRONTSHARINGDIVERSITYASSIGNMENT_H_
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#include <diversity/moeoSharingDiversityAssignment.h>
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/**
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* Sharing assignment scheme on the way it is used in NSGA.
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*/
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template < class MOEOT >
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class moeoFrontByFrontSharingDiversityAssignment : public moeoSharingDiversityAssignment < 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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* Ctor
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* @param _distance the distance used to compute the neighborhood of solutions (can be related to the decision space or the objective space)
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* @param _nicheSize neighborhood size in terms of radius distance (closely related to the way the distances are computed)
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* @param _alpha parameter used to regulate the shape of the sharing function
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*/
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moeoFrontByFrontSharingDiversityAssignment(moeoDistance<MOEOT,double> & _distance, double _nicheSize = 0.5, double _alpha = 2.0) : moeoSharingDiversityAssignment < MOEOT >(_distance, _nicheSize, _alpha)
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{}
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/**
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* Ctor with an euclidean distance (with normalized objective values) in the objective space is used as default
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* @param _nicheSize neighborhood size in terms of radius distance (closely related to the way the distances are computed)
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* @param _alpha parameter used to regulate the shape of the sharing function
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*/
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moeoFrontByFrontSharingDiversityAssignment(double _nicheSize = 0.5, double _alpha = 2.0) : moeoSharingDiversityAssignment < MOEOT >(_nicheSize, _alpha)
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{}
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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 moeoSharingDiversityAssignment" << std::endl;
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}
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private:
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using moeoSharingDiversityAssignment < MOEOT >::distance;
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using moeoSharingDiversityAssignment < MOEOT >::nicheSize;
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using moeoSharingDiversityAssignment < MOEOT >::sh;
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using moeoSharingDiversityAssignment < MOEOT >::operator();
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/**
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* Sets similarities FRONT BY FRONT 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 setSimilarities(eoPop < MOEOT > & _pop)
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{
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// compute distances between every individuals
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moeoDistanceMatrix < MOEOT , double > dMatrix (_pop.size(), distance);
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dMatrix(_pop);
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// sets the distance to bigger than the niche size for every couple of solutions that do not belong to the same front
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for (unsigned int i=0; i<_pop.size(); i++)
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{
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for (unsigned int j=0; j<i; j++)
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{
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if (_pop[i].fitness() != _pop[j].fitness())
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{
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dMatrix[i][j] = nicheSize;
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dMatrix[j][i] = nicheSize;
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}
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}
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}
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// compute similarities
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double sum;
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for (unsigned int i=0; i<_pop.size(); i++)
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{
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sum = 0.0;
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for (unsigned int j=0; j<_pop.size(); j++)
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{
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sum += sh(dMatrix[i][j]);
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}
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_pop[i].diversity(sum);
|
||||
}
|
||||
}
|
||||
|
||||
};
|
||||
|
||||
#endif /*MOEOFRONTBYFRONTSHARINGDIVERSITYASSIGNMENT_H_*/
|
||||
|
|
@ -0,0 +1,142 @@
|
|||
// -*- mode: c++; c-indent-level: 4; c++-member-init-indent: 8; comment-column: 35; -*-
|
||||
|
||||
//-----------------------------------------------------------------------------
|
||||
// moeoSharingDiversityAssignment.h
|
||||
// (c) OPAC Team (LIFL), Dolphin Project (INRIA), 2007
|
||||
/*
|
||||
This library...
|
||||
|
||||
Contact: paradiseo-help@lists.gforge.inria.fr, http://paradiseo.gforge.inria.fr
|
||||
*/
|
||||
//-----------------------------------------------------------------------------
|
||||
|
||||
#ifndef MOEOSHARINGDIVERSITYASSIGNMENT_H_
|
||||
#define MOEOSHARINGDIVERSITYASSIGNMENT_H_
|
||||
|
||||
#include <eoPop.h>
|
||||
#include <comparator/moeoDiversityThenFitnessComparator.h>
|
||||
#include <distance/moeoDistance.h>
|
||||
#include <distance/moeoDistanceMatrix.h>
|
||||
#include <distance/moeoEuclideanDistance.h>
|
||||
#include <diversity/moeoDiversityAssignment.h>
|
||||
|
||||
/**
|
||||
* Sharing assignment scheme originally porposed by:
|
||||
* D. E. Goldberg, "Genetic Algorithms in Search, Optimization and Machine Learning", Addision-Wesley, MA, USA (1989).
|
||||
*/
|
||||
template < class MOEOT >
|
||||
class moeoSharingDiversityAssignment : public moeoDiversityAssignment < MOEOT >
|
||||
{
|
||||
public:
|
||||
|
||||
/** the objective vector type of the solutions */
|
||||
typedef typename MOEOT::ObjectiveVector ObjectiveVector;
|
||||
|
||||
|
||||
/**
|
||||
* Ctor
|
||||
* @param _distance the distance used to compute the neighborhood of solutions (can be related to the decision space or the objective space)
|
||||
* @param _nicheSize neighborhood size in terms of radius distance (closely related to the way the distances are computed)
|
||||
* @param _alpha parameter used to regulate the shape of the sharing function
|
||||
*/
|
||||
moeoSharingDiversityAssignment(moeoDistance<MOEOT,double> & _distance, double _nicheSize = 0.5, double _alpha = 1.0) : distance(_distance), nicheSize(_nicheSize), alpha(_alpha)
|
||||
{}
|
||||
|
||||
|
||||
/**
|
||||
* Ctor with an euclidean distance (with normalized objective values) in the objective space is used as default
|
||||
* @param _nicheSize neighborhood size in terms of radius distance (closely related to the way the distances are computed)
|
||||
* @param _alpha parameter used to regulate the shape of the sharing function
|
||||
*/
|
||||
moeoSharingDiversityAssignment(double _nicheSize = 0.5, double _alpha = 1.0) : distance(defaultDistance), nicheSize(_nicheSize), alpha(_alpha)
|
||||
{}
|
||||
|
||||
|
||||
/**
|
||||
* Sets diversity values for every solution contained in the population _pop
|
||||
* @param _pop the population
|
||||
*/
|
||||
void operator()(eoPop < MOEOT > & _pop)
|
||||
{
|
||||
// 1 - set simuilarities
|
||||
setSimilarities(_pop);
|
||||
// 2 - a higher diversity is better, so the values need to be inverted
|
||||
moeoDiversityThenFitnessComparator < MOEOT > divComparator;
|
||||
double max = std::max_element(_pop.begin(), _pop.end(), divComparator)->diversity();
|
||||
for (unsigned int i=0 ; i<_pop.size() ; i++)
|
||||
{
|
||||
_pop[i].diversity(max - _pop[i].diversity());
|
||||
}
|
||||
}
|
||||
|
||||
|
||||
/**
|
||||
* @warning NOT IMPLEMENTED, DO NOTHING !
|
||||
* Updates the diversity values of the whole population _pop by taking the deletion of the objective vector _objVec into account.
|
||||
* @param _pop the population
|
||||
* @param _objVec the objective vector
|
||||
* @warning NOT IMPLEMENTED, DO NOTHING !
|
||||
*/
|
||||
void updateByDeleting(eoPop < MOEOT > & _pop, ObjectiveVector & _objVec)
|
||||
{
|
||||
std::cout << "WARNING : updateByDeleting not implemented in moeoSharingDiversityAssignment" << std::endl;
|
||||
}
|
||||
|
||||
|
||||
protected:
|
||||
|
||||
/** the distance used to compute the neighborhood of solutions */
|
||||
moeoDistance < MOEOT , double > & distance;
|
||||
/** euclidean distancein the objective space (can be used as default) */
|
||||
moeoEuclideanDistance < MOEOT > defaultDistance;
|
||||
/** neighborhood size in terms of radius distance */
|
||||
double nicheSize;
|
||||
/** parameter used to regulate the shape of the sharing function */
|
||||
double alpha;
|
||||
|
||||
|
||||
/**
|
||||
* Sets similarities for every solution contained in the population _pop
|
||||
* @param _pop the population
|
||||
*/
|
||||
virtual void setSimilarities(eoPop < MOEOT > & _pop)
|
||||
{
|
||||
// compute distances between every individuals
|
||||
moeoDistanceMatrix < MOEOT , double > dMatrix (_pop.size(), distance);
|
||||
dMatrix(_pop);
|
||||
// compute similarities
|
||||
double sum;
|
||||
for (unsigned int i=0; i<_pop.size(); i++)
|
||||
{
|
||||
sum = 0.0;
|
||||
for (unsigned int j=0; j<_pop.size(); j++)
|
||||
{
|
||||
sum += sh(dMatrix[i][j]);
|
||||
}
|
||||
_pop[i].diversity(sum);
|
||||
}
|
||||
}
|
||||
|
||||
|
||||
/**
|
||||
* Sharing function
|
||||
* @param _dist the distance value
|
||||
*/
|
||||
double sh(double _dist)
|
||||
{
|
||||
double result;
|
||||
if (_dist < nicheSize)
|
||||
{
|
||||
result = 1.0 - pow(_dist / nicheSize, alpha);
|
||||
}
|
||||
else
|
||||
{
|
||||
result = 0.0;
|
||||
}
|
||||
return result;
|
||||
}
|
||||
|
||||
};
|
||||
|
||||
|
||||
#endif /*MOEOSHARINGDIVERSITYASSIGNMENT_H_*/
|
||||
Loading…
Add table
Add a link
Reference in a new issue