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add diversity

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git-svn-id: svn://scm.gforge.inria.fr/svnroot/paradiseo@375 331e1502-861f-0410-8da2-ba01fb791d7f
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liefooga 2007-06-26 12:10:47 +00:00
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122
branches/paradiseo-moeo-1.0/src/diversity/moeoCrowdingDistanceDiversityAssignment.h Executable file
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// -*- mode: c++; c-indent-level: 4; c++-member-init-indent: 8; comment-column: 35; -*-
//-----------------------------------------------------------------------------
// moeoCrowdingDistanceDiversityAssignment.h
// (c) OPAC Team (LIFL), Dolphin Project (INRIA), 2007
/*
This library...
Contact: paradiseo-help@lists.gforge.inria.fr, http://paradiseo.gforge.inria.fr
*/
//-----------------------------------------------------------------------------
#ifndef MOEOCROWDINGDISTANCEDIVERSITYASSIGNMENT_H_
#define MOEOCROWDINGDISTANCEDIVERSITYASSIGNMENT_H_
#include <eoPop.h>
#include <comparator/moeoOneObjectiveComparator.h>
#include <diversity/moeoDiversityAssignment.h>
/**
* Diversity assignment sheme based on crowding distance proposed in:
* 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).
*/
template < class MOEOT >
class moeoCrowdingDistanceDiversityAssignment : public moeoDiversityAssignment < MOEOT >
{
public:
/** the objective vector type of the solutions */
typedef typename MOEOT::ObjectiveVector ObjectiveVector;
/**
* Returns a big value (regarded as infinite)
*/
double inf() const
{
return std::numeric_limits<double>::max();
}
/**
* Returns a very small value that can be used to avoid extreme cases (where the min bound == the max bound)
*/
double tiny() const
{
return 1e-6;
}
/**
* Computes diversity values for every solution contained in the population _pop
* @param _pop the population
*/
void operator()(eoPop < MOEOT > & _pop)
{
if (_pop.size() <= 2)
{
for (unsigned int i=0; i<_pop.size(); i++)
{
_pop[i].diversity(inf());
}
}
else
{
setDistances(_pop);
}
}
/**
* @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 moeoCrowdingDiversityAssignment" << std::endl;
}
protected:
/**
* Sets the distance values
* @param _pop the population
*/
virtual void setDistances (eoPop < MOEOT > & _pop)
{
double min, max, distance;
unsigned int nObjectives = MOEOT::ObjectiveVector::nObjectives();
// set diversity to 0
for (unsigned int i=0; i<_pop.size(); i++)
{
_pop[i].diversity(0);
}
// for each objective
for (unsigned int obj=0; obj<nObjectives; obj++)
{
// comparator
moeoOneObjectiveComparator < MOEOT > objComp(obj);
// sort
std::sort(_pop.begin(), _pop.end(), objComp);
// min & max
min = _pop[0].objectiveVector()[obj];
max = _pop[_pop.size()-1].objectiveVector()[obj];
// set the diversity value to infiny for min and max
_pop[0].diversity(inf());
_pop[_pop.size()-1].diversity(inf());
for (unsigned int i=1; i<_pop.size()-1; i++)
{
distance = (_pop[i+1].objectiveVector()[obj] - _pop[i-1].objectiveVector()[obj]) / (max-min);
_pop[i].diversity(_pop[i].diversity() + distance);
}
}
}
};
#endif /*MOEOCROWDINGDISTANCEDIVERSITYASSIGNMENT_H_*/

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branches/paradiseo-moeo-1.0/src/diversity/moeoDiversityAssignment.h Normal file
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// -*- mode: c++; c-indent-level: 4; c++-member-init-indent: 8; comment-column: 35; -*-
//-----------------------------------------------------------------------------
// moeoDiversityAssignment.h
// (c) OPAC Team (LIFL), Dolphin Project (INRIA), 2007
/*
This library...
Contact: paradiseo-help@lists.gforge.inria.fr, http://paradiseo.gforge.inria.fr
*/
//-----------------------------------------------------------------------------
#ifndef MOEODIVERSITYASSIGNMENT_H_
#define MOEODIVERSITYASSIGNMENT_H_
#include <eoFunctor.h>
#include <eoPop.h>
/**
* Functor that sets the diversity values of a whole population.
*/
template < class MOEOT >
class moeoDiversityAssignment : public eoUF < eoPop < MOEOT > &, void >
{
public:
/** The type for objective vector */
typedef typename MOEOT::ObjectiveVector ObjectiveVector;
/**
* 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
*/
virtual void updateByDeleting(eoPop < MOEOT > & _pop, ObjectiveVector & _objVec) = 0;
/**
* Updates the diversity values of the whole population _pop by taking the deletion of the individual _moeo into account.
* @param _pop the population
* @param _moeo the individual
*/
void updateByDeleting(eoPop < MOEOT > & _pop, MOEOT & _moeo)
{
updateByDeleting(_pop, _moeo.objectiveVector());
}
};
#endif /*MOEODIVERSITYASSIGNMENT_H_*/

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branches/paradiseo-moeo-1.0/src/diversity/moeoDummyDiversityAssignment.h Normal file
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// -*- mode: c++; c-indent-level: 4; c++-member-init-indent: 8; comment-column: 35; -*-
//-----------------------------------------------------------------------------
// moeoDummyDiversityAssignment.h
// (c) OPAC Team (LIFL), Dolphin Project (INRIA), 2007
/*
This library...
Contact: paradiseo-help@lists.gforge.inria.fr, http://paradiseo.gforge.inria.fr
*/
//-----------------------------------------------------------------------------
#ifndef MOEODUMMYDIVERSITYASSIGNMENT_H_
#define MOEODUMMYDIVERSITYASSIGNMENT_H_
#include<diversity/moeoDiversityAssignment.h>
/**
* moeoDummyDiversityAssignment is a moeoDiversityAssignment that gives the value '0' as the individual's diversity for a whole population if it is invalid.
*/
template < class MOEOT >
class moeoDummyDiversityAssignment : public moeoDiversityAssignment < MOEOT >
{
public:
/** The type for objective vector */
typedef typename MOEOT::ObjectiveVector ObjectiveVector;
/**
* Sets the diversity to '0' for every individuals of the population _pop if it is invalid
* @param _pop the population
*/
void operator () (eoPop < MOEOT > & _pop)
{
for (unsigned int idx = 0; idx<_pop.size (); idx++)
{
if (_pop[idx].invalidDiversity())
{
// set the diversity to 0
_pop[idx].diversity(0.0);
}
}
}
/**
* 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
*/
void updateByDeleting(eoPop < MOEOT > & _pop, ObjectiveVector & _objVec)
{
// nothing to do... ;-)
}
};
#endif /*MOEODUMMYDIVERSITYASSIGNMENT_H_*/

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branches/paradiseo-moeo-1.0/src/diversity/moeoFrontByFrontCrowdingDistanceDiversityAssignment.h Normal file
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// -*- mode: c++; c-indent-level: 4; c++-member-init-indent: 8; comment-column: 35; -*-
//-----------------------------------------------------------------------------
// moeoFrontByFrontCrowdingDistanceDiversityAssignment.h
// (c) OPAC Team (LIFL), Dolphin Project (INRIA), 2007
/*
This library...
Contact: paradiseo-help@lists.gforge.inria.fr, http://paradiseo.gforge.inria.fr
*/
//-----------------------------------------------------------------------------
#ifndef MOEOFRONTBYFRONTCROWDINGDISTANCEDIVERSITYASSIGNMENT_H_
#define MOEOFRONTBYFRONTCROWDINGDISTANCEDIVERSITYASSIGNMENT_H_
#include <diversity/moeoCrowdingDistanceDiversityAssignment.h>
#include <comparator/moeoFitnessThenDiversityComparator.h>
/**
* Diversity assignment sheme based on crowding distance proposed in:
* 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).
* Tis strategy assigns diversity values FRONT BY FRONT. It is, for instance, used in NSGA-II.
*/
template < class MOEOT >
class moeoFrontByFrontCrowdingDistanceDiversityAssignment : public moeoCrowdingDistanceDiversityAssignment < MOEOT >
{
public:
/** the objective vector type of the solutions */
typedef typename MOEOT::ObjectiveVector ObjectiveVector;
/**
* @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 moeoFrontByFrontCrowdingDistanceDiversityAssignment" << std::endl;
}
private:
using moeoCrowdingDistanceDiversityAssignment < MOEOT >::inf;
using moeoCrowdingDistanceDiversityAssignment < MOEOT >::tiny;
/**
* Sets the distance values
* @param _pop the population
*/
void setDistances (eoPop < MOEOT > & _pop)
{
unsigned int a,b;
double min, max, distance;
unsigned int nObjectives = MOEOT::ObjectiveVector::nObjectives();
// set diversity to 0 for every individual
for (unsigned int i=0; i<_pop.size(); i++)
{
_pop[i].diversity(0.0);
}
// sort the whole pop according to fitness values
moeoFitnessThenDiversityComparator < MOEOT > fitnessComparator;
std::sort(_pop.begin(), _pop.end(), fitnessComparator);
// compute the crowding distance values for every individual "front" by "front" (front : from a to b)
a = 0; // the front starts at a
while (a < _pop.size())
{
b = lastIndex(_pop,a); // the front ends at b
// if there is less than 2 individuals in the front...
if ((b-a) < 2)
{
for (unsigned int i=a; i<=b; i++)
{
_pop[i].diversity(inf());
}
}
// else...
else
{
// for each objective
for (unsigned int obj=0; obj<nObjectives; obj++)
{
// sort in the descending order using the values of the objective 'obj'
moeoOneObjectiveComparator < MOEOT > objComp(obj);
std::sort(_pop.begin()+a, _pop.begin()+b+1, objComp);
// min & max
min = _pop[b].objectiveVector()[obj];
max = _pop[a].objectiveVector()[obj];
// avoid extreme case
if (min == max)
{
min -= tiny();
max += tiny();
}
// set the diversity value to infiny for min and max
_pop[a].diversity(inf());
_pop[b].diversity(inf());
// set the diversity values for the other individuals
for (unsigned int i=a+1; i<b; i++)
{
distance = (_pop[i-1].objectiveVector()[obj] - _pop[i+1].objectiveVector()[obj]) / (max-min);
_pop[i].diversity(_pop[i].diversity() + distance);
}
}
}
// go to the next front
a = b+1;
}
}
/**
* Returns the index of the last individual having the same fitness value than _pop[_start]
* @param _pop the population
* @param _start the index to start from
*/
unsigned int lastIndex (eoPop < MOEOT > & _pop, unsigned int _start)
{
unsigned int i=_start;
while ( (i<_pop.size()-1) && (_pop[i].fitness()==_pop[i+1].fitness()) )
{
i++;
}
return i;
}
};
#endif /*MOEOFRONTBYFRONTCROWDINGDISTANCEDIVERSITYASSIGNMENT_H_*/

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branches/paradiseo-moeo-1.0/src/diversity/moeoFrontByFrontSharingDiversityAssignment.h Normal file
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// -*- mode: c++; c-indent-level: 4; c++-member-init-indent: 8; comment-column: 35; -*-
//-----------------------------------------------------------------------------
// moeoFrontByFrontSharingDiversityAssignment.h
// (c) OPAC Team (LIFL), Dolphin Project (INRIA), 2007
/*
This library...
Contact: paradiseo-help@lists.gforge.inria.fr, http://paradiseo.gforge.inria.fr
*/
//-----------------------------------------------------------------------------
#ifndef MOEOFRONTBYFRONTSHARINGDIVERSITYASSIGNMENT_H_
#define MOEOFRONTBYFRONTSHARINGDIVERSITYASSIGNMENT_H_
#include <diversity/moeoSharingDiversityAssignment.h>
/**
* Sharing assignment scheme on the way it is used in NSGA.
*/
template < class MOEOT >
class moeoFrontByFrontSharingDiversityAssignment : public moeoSharingDiversityAssignment < 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
*/
moeoFrontByFrontSharingDiversityAssignment(moeoDistance<MOEOT,double> & _distance, double _nicheSize = 0.5, double _alpha = 2.0) : moeoSharingDiversityAssignment < MOEOT >(_distance, _nicheSize, _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
*/
moeoFrontByFrontSharingDiversityAssignment(double _nicheSize = 0.5, double _alpha = 2.0) : moeoSharingDiversityAssignment < MOEOT >(_nicheSize, _alpha)
{}
/**
* @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;
}
private:
using moeoSharingDiversityAssignment < MOEOT >::distance;
using moeoSharingDiversityAssignment < MOEOT >::nicheSize;
using moeoSharingDiversityAssignment < MOEOT >::sh;
using moeoSharingDiversityAssignment < MOEOT >::operator();
/**
* Sets similarities FRONT BY FRONT for every solution contained in the population _pop
* @param _pop the population
*/
void setSimilarities(eoPop < MOEOT > & _pop)
{
// compute distances between every individuals
moeoDistanceMatrix < MOEOT , double > dMatrix (_pop.size(), distance);
dMatrix(_pop);
// sets the distance to bigger than the niche size for every couple of solutions that do not belong to the same front
for (unsigned int i=0; i<_pop.size(); i++)
{
for (unsigned int j=0; j<i; j++)
{
if (_pop[i].fitness() != _pop[j].fitness())
{
dMatrix[i][j] = nicheSize;
dMatrix[j][i] = nicheSize;
}
}
}
// 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);
}
}
};
#endif /*MOEOFRONTBYFRONTSHARINGDIVERSITYASSIGNMENT_H_*/

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branches/paradiseo-moeo-1.0/src/diversity/moeoSharingDiversityAssignment.h Normal file
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// -*- 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_*/