New style for MOEO
git-svn-id: svn://scm.gforge.inria.fr/svnroot/paradiseo@788 331e1502-861f-0410-8da2-ba01fb791d7f
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canape
parent
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103 changed files with 2607 additions and 2521 deletions
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@ -1,4 +1,4 @@
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/*
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/*
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* <moeoAdditiveEpsilonBinaryMetric.h>
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* Copyright (C) DOLPHIN Project-Team, INRIA Futurs, 2006-2007
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* (C) OPAC Team, LIFL, 2002-2007
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@ -47,8 +47,8 @@
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*/
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template < class ObjectiveVector >
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class moeoAdditiveEpsilonBinaryMetric : public moeoNormalizedSolutionVsSolutionBinaryMetric < ObjectiveVector, double >
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{
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public:
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{
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public:
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/**
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* Returns the minimal distance by which the objective vector _o1 must be translated in all objectives
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@ -59,21 +59,21 @@ public:
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*/
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double operator()(const ObjectiveVector & _o1, const ObjectiveVector & _o2)
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{
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// computation of the epsilon value for the first objective
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double result = epsilon(_o1, _o2, 0);
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// computation of the epsilon value for the other objectives
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double tmp;
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for (unsigned int i=1; i<ObjectiveVector::Traits::nObjectives(); i++)
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// computation of the epsilon value for the first objective
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double result = epsilon(_o1, _o2, 0);
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// computation of the epsilon value for the other objectives
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double tmp;
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for (unsigned int i=1; i<ObjectiveVector::Traits::nObjectives(); i++)
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{
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tmp = epsilon(_o1, _o2, i);
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result = std::max(result, tmp);
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tmp = epsilon(_o1, _o2, i);
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result = std::max(result, tmp);
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}
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// returns the maximum epsilon value
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return result;
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// returns the maximum epsilon value
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return result;
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}
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private:
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private:
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/** the bounds for every objective */
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using moeoNormalizedSolutionVsSolutionBinaryMetric < ObjectiveVector, double > :: bounds;
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@ -88,22 +88,22 @@ private:
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*/
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double epsilon(const ObjectiveVector & _o1, const ObjectiveVector & _o2, const unsigned int _obj)
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{
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double result;
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// if the objective _obj have to be minimized
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if (ObjectiveVector::Traits::minimizing(_obj))
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double result;
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// if the objective _obj have to be minimized
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if (ObjectiveVector::Traits::minimizing(_obj))
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{
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// _o1[_obj] - _o2[_obj]
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result = ( (_o1[_obj] - bounds[_obj].minimum()) / bounds[_obj].range() ) - ( (_o2[_obj] - bounds[_obj].minimum()) / bounds[_obj].range() );
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// _o1[_obj] - _o2[_obj]
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result = ( (_o1[_obj] - bounds[_obj].minimum()) / bounds[_obj].range() ) - ( (_o2[_obj] - bounds[_obj].minimum()) / bounds[_obj].range() );
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}
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// if the objective _obj have to be maximized
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else
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// if the objective _obj have to be maximized
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else
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{
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// _o2[_obj] - _o1[_obj]
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result = ( (_o2[_obj] - bounds[_obj].minimum()) / bounds[_obj].range() ) - ( (_o1[_obj] - bounds[_obj].minimum()) / bounds[_obj].range() );
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// _o2[_obj] - _o1[_obj]
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result = ( (_o2[_obj] - bounds[_obj].minimum()) / bounds[_obj].range() ) - ( (_o1[_obj] - bounds[_obj].minimum()) / bounds[_obj].range() );
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}
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return result;
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return result;
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}
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};
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};
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#endif /*MOEOADDITIVEEPSILONBINARYMETRIC_H_*/
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@ -1,4 +1,4 @@
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/*
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/*
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* <moeoContributionMetric.h>
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* Copyright (C) DOLPHIN Project-Team, INRIA Futurs, 2006-2007
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* (C) OPAC Team, LIFL, 2002-2007
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@ -47,44 +47,47 @@
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*/
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template < class ObjectiveVector >
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class moeoContributionMetric : public moeoVectorVsVectorBinaryMetric < ObjectiveVector, double >
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{
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public:
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{
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public:
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/**
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* Returns the contribution of the Pareto set '_set1' relatively to the Pareto set '_set2'
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* @param _set1 the first Pareto set
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* @param _set2 the second Pareto set
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*/
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double operator()(const std::vector < ObjectiveVector > & _set1, const std::vector < ObjectiveVector > & _set2) {
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unsigned int c = card_C(_set1, _set2);
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unsigned int w1 = card_W(_set1, _set2);
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unsigned int n1 = card_N(_set1, _set2);
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unsigned int w2 = card_W(_set2, _set1);
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unsigned int n2 = card_N(_set2, _set1);
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return (double) (c / 2.0 + w1 + n1) / (c + w1 + n1 + w2 + n2);
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double operator()(const std::vector < ObjectiveVector > & _set1, const std::vector < ObjectiveVector > & _set2)
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{
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unsigned int c = card_C(_set1, _set2);
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unsigned int w1 = card_W(_set1, _set2);
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unsigned int n1 = card_N(_set1, _set2);
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unsigned int w2 = card_W(_set2, _set1);
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unsigned int n2 = card_N(_set2, _set1);
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return (double) (c / 2.0 + w1 + n1) / (c + w1 + n1 + w2 + n2);
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}
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private:
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private:
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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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/**
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* Returns the number of solutions both in '_set1' and '_set2'
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* @param _set1 the first Pareto set
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* @param _set2 the second Pareto set
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*/
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unsigned int card_C (const std::vector < ObjectiveVector > & _set1, const std::vector < ObjectiveVector > & _set2) {
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unsigned int c=0;
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for (unsigned int i=0; i<_set1.size(); i++)
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for (unsigned int j=0; j<_set2.size(); j++)
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if (_set1[i] == _set2[j]) {
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c++;
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break;
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}
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return c;
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unsigned int card_C (const std::vector < ObjectiveVector > & _set1, const std::vector < ObjectiveVector > & _set2)
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{
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unsigned int c=0;
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for (unsigned int i=0; i<_set1.size(); i++)
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for (unsigned int j=0; j<_set2.size(); j++)
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if (_set1[i] == _set2[j])
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{
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c++;
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break;
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}
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return c;
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}
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@ -93,16 +96,17 @@ private:
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* @param _set1 the first Pareto set
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* @param _set2 the second Pareto set
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*/
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unsigned int card_W (const std::vector < ObjectiveVector > & _set1, const std::vector < ObjectiveVector > & _set2) {
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unsigned int w=0;
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for (unsigned int i=0; i<_set1.size(); i++)
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for (unsigned int j=0; j<_set2.size(); j++)
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if (paretoComparator(_set2[j], _set1[i]))
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{
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w++;
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break;
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}
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return w;
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unsigned int card_W (const std::vector < ObjectiveVector > & _set1, const std::vector < ObjectiveVector > & _set2)
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{
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unsigned int w=0;
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for (unsigned int i=0; i<_set1.size(); i++)
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for (unsigned int j=0; j<_set2.size(); j++)
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if (paretoComparator(_set2[j], _set1[i]))
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{
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w++;
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break;
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}
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return w;
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}
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* @param _set1 the first Pareto set
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* @param _set2 the second Pareto set
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*/
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unsigned int card_N (const std::vector < ObjectiveVector > & _set1, const std::vector < ObjectiveVector > & _set2) {
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unsigned int n=0;
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for (unsigned int i=0; i<_set1.size(); i++) {
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bool domin_rel = false;
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for (unsigned int j=0; j<_set2.size(); j++)
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if ( (paretoComparator(_set2[j], _set1[i])) || (paretoComparator(_set1[i], _set2[j])) )
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{
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domin_rel = true;
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break;
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}
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if (! domin_rel)
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n++;
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unsigned int card_N (const std::vector < ObjectiveVector > & _set1, const std::vector < ObjectiveVector > & _set2)
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{
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unsigned int n=0;
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for (unsigned int i=0; i<_set1.size(); i++)
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{
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bool domin_rel = false;
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for (unsigned int j=0; j<_set2.size(); j++)
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if ( (paretoComparator(_set2[j], _set1[i])) || (paretoComparator(_set1[i], _set2[j])) )
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{
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domin_rel = true;
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break;
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}
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if (! domin_rel)
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n++;
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}
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return n;
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return n;
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}
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};
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};
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#endif /*MOEOCONTRIBUTIONMETRIC_H_*/
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/*
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/*
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* <moeoEntropyMetric.h>
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* Copyright (C) DOLPHIN Project-Team, INRIA Futurs, 2006-2007
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* (C) OPAC Team, LIFL, 2002-2007
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@ -48,52 +48,55 @@
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*/
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template < class ObjectiveVector >
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class moeoEntropyMetric : public moeoVectorVsVectorBinaryMetric < ObjectiveVector, double >
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{
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public:
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{
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public:
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/**
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* Returns the entropy of the Pareto set '_set1' relatively to the Pareto set '_set2'
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* @param _set1 the first Pareto set
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* @param _set2 the second Pareto set
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*/
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double operator()(const std::vector < ObjectiveVector > & _set1, const std::vector < ObjectiveVector > & _set2) {
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// normalization
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std::vector< ObjectiveVector > set1 = _set1;
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std::vector< ObjectiveVector > set2= _set2;
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removeDominated (set1);
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removeDominated (set2);
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prenormalize (set1);
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normalize (set1);
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normalize (set2);
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double operator()(const std::vector < ObjectiveVector > & _set1, const std::vector < ObjectiveVector > & _set2)
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{
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// normalization
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std::vector< ObjectiveVector > set1 = _set1;
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std::vector< ObjectiveVector > set2= _set2;
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removeDominated (set1);
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removeDominated (set2);
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prenormalize (set1);
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normalize (set1);
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normalize (set2);
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// making of PO*
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std::vector< ObjectiveVector > star; // rotf :-)
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computeUnion (set1, set2, star);
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removeDominated (star);
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// making of PO*
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std::vector< ObjectiveVector > star; // rotf :-)
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computeUnion (set1, set2, star);
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removeDominated (star);
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// making of PO1 U PO*
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std::vector< ObjectiveVector > union_set1_star; // rotf again ...
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computeUnion (set1, star, union_set1_star);
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// making of PO1 U PO*
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std::vector< ObjectiveVector > union_set1_star; // rotf again ...
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computeUnion (set1, star, union_set1_star);
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unsigned int C = union_set1_star.size();
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float omega=0;
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float entropy=0;
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unsigned int C = union_set1_star.size();
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float omega=0;
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float entropy=0;
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for (unsigned int i=0 ; i<C ; i++) {
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unsigned int N_i = howManyInNicheOf (union_set1_star, union_set1_star[i], star.size());
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unsigned int n_i = howManyInNicheOf (set1, union_set1_star[i], star.size());
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if (n_i > 0) {
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omega += 1.0 / N_i;
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entropy += (float) n_i / (N_i * C) * log (((float) n_i / C) / log (2.0));
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for (unsigned int i=0 ; i<C ; i++)
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{
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unsigned int N_i = howManyInNicheOf (union_set1_star, union_set1_star[i], star.size());
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unsigned int n_i = howManyInNicheOf (set1, union_set1_star[i], star.size());
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if (n_i > 0)
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{
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omega += 1.0 / N_i;
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entropy += (float) n_i / (N_i * C) * log (((float) n_i / C) / log (2.0));
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}
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}
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entropy /= - log (omega);
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entropy *= log (2.0);
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return entropy;
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entropy /= - log (omega);
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entropy *= log (2.0);
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return entropy;
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}
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private:
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private:
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/** vector of min values */
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std::vector<double> vect_min_val;
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* Removes the dominated individuals contained in _f
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* @param _f a Pareto set
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*/
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void removeDominated(std::vector < ObjectiveVector > & _f) {
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for (unsigned int i=0 ; i<_f.size(); i++) {
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bool dom = false;
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for (unsigned int j=0; j<_f.size(); j++)
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if (i != j && paretoComparator(_f[i],_f[j]))
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{
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dom = true;
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break;
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}
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if (dom) {
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_f[i] = _f.back();
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_f.pop_back();
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i--;
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void removeDominated(std::vector < ObjectiveVector > & _f)
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{
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for (unsigned int i=0 ; i<_f.size(); i++)
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{
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bool dom = false;
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for (unsigned int j=0; j<_f.size(); j++)
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if (i != j && paretoComparator(_f[i],_f[j]))
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{
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dom = true;
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break;
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}
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if (dom)
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{
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_f[i] = _f.back();
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_f.pop_back();
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i--;
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}
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}
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}
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* Prenormalization
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* @param _f a Pareto set
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*/
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void prenormalize (const std::vector< ObjectiveVector > & _f) {
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vect_min_val.clear();
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vect_max_val.clear();
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void prenormalize (const std::vector< ObjectiveVector > & _f)
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{
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vect_min_val.clear();
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vect_max_val.clear();
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for (unsigned int i=0 ; i<ObjectiveVector::nObjectives(); i++) {
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float min_val = _f.front()[i], max_val = min_val;
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for (unsigned int j=1 ; j<_f.size(); j++) {
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if (_f[j][i] < min_val)
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min_val = _f[j][i];
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if (_f[j][i]>max_val)
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max_val = _f[j][i];
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for (unsigned int i=0 ; i<ObjectiveVector::nObjectives(); i++)
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{
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float min_val = _f.front()[i], max_val = min_val;
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for (unsigned int j=1 ; j<_f.size(); j++)
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{
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if (_f[j][i] < min_val)
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min_val = _f[j][i];
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if (_f[j][i]>max_val)
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max_val = _f[j][i];
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}
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vect_min_val.push_back(min_val);
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vect_max_val.push_back (max_val);
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vect_min_val.push_back(min_val);
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vect_max_val.push_back (max_val);
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}
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}
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* Normalization
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* @param _f a Pareto set
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*/
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void normalize (std::vector< ObjectiveVector > & _f) {
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for (unsigned int i=0 ; i<ObjectiveVector::nObjectives(); i++)
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for (unsigned int j=0; j<_f.size(); j++)
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_f[j][i] = (_f[j][i] - vect_min_val[i]) / (vect_max_val[i] - vect_min_val[i]);
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void normalize (std::vector< ObjectiveVector > & _f)
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{
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for (unsigned int i=0 ; i<ObjectiveVector::nObjectives(); i++)
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for (unsigned int j=0; j<_f.size(); j++)
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_f[j][i] = (_f[j][i] - vect_min_val[i]) / (vect_max_val[i] - vect_min_val[i]);
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}
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* @param _f2 the second Pareto set
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* @param _f the final Pareto set
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*/
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void computeUnion(const std::vector< ObjectiveVector > & _f1, const std::vector< ObjectiveVector > & _f2, std::vector< ObjectiveVector > & _f) {
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_f = _f1 ;
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for (unsigned int i=0; i<_f2.size(); i++) {
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bool b = false;
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for (unsigned int j=0; j<_f1.size(); j ++)
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if (_f1[j] == _f2[i]) {
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b = true;
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break;
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}
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if (! b)
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_f.push_back(_f2[i]);
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void computeUnion(const std::vector< ObjectiveVector > & _f1, const std::vector< ObjectiveVector > & _f2, std::vector< ObjectiveVector > & _f)
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{
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_f = _f1 ;
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for (unsigned int i=0; i<_f2.size(); i++)
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{
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bool b = false;
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for (unsigned int j=0; j<_f1.size(); j ++)
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if (_f1[j] == _f2[i])
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{
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b = true;
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break;
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}
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if (! b)
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_f.push_back(_f2[i]);
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}
|
||||
}
|
||||
|
||||
|
|
@ -182,26 +195,29 @@ private:
|
|||
/**
|
||||
* How many in niche
|
||||
*/
|
||||
unsigned int howManyInNicheOf (const std::vector< ObjectiveVector > & _f, const ObjectiveVector & _s, unsigned int _size) {
|
||||
unsigned int n=0;
|
||||
for (unsigned int i=0 ; i<_f.size(); i++) {
|
||||
if (euclidianDistance(_f[i], _s) < (_s.size() / (double) _size))
|
||||
n++;
|
||||
unsigned int howManyInNicheOf (const std::vector< ObjectiveVector > & _f, const ObjectiveVector & _s, unsigned int _size)
|
||||
{
|
||||
unsigned int n=0;
|
||||
for (unsigned int i=0 ; i<_f.size(); i++)
|
||||
{
|
||||
if (euclidianDistance(_f[i], _s) < (_s.size() / (double) _size))
|
||||
n++;
|
||||
}
|
||||
return n;
|
||||
return n;
|
||||
}
|
||||
|
||||
|
||||
/**
|
||||
* Euclidian distance
|
||||
*/
|
||||
double euclidianDistance (const ObjectiveVector & _set1, const ObjectiveVector & _to, unsigned int _deg = 2) {
|
||||
double dist=0;
|
||||
for (unsigned int i=0; i<_set1.size(); i++)
|
||||
dist += pow(fabs(_set1[i] - _to[i]), (int)_deg);
|
||||
return pow(dist, 1.0 / _deg);
|
||||
double euclidianDistance (const ObjectiveVector & _set1, const ObjectiveVector & _to, unsigned int _deg = 2)
|
||||
{
|
||||
double dist=0;
|
||||
for (unsigned int i=0; i<_set1.size(); i++)
|
||||
dist += pow(fabs(_set1[i] - _to[i]), (int)_deg);
|
||||
return pow(dist, 1.0 / _deg);
|
||||
}
|
||||
|
||||
};
|
||||
};
|
||||
|
||||
#endif /*MOEOENTROPYMETRIC_H_*/
|
||||
|
|
|
|||
|
|
@ -1,4 +1,4 @@
|
|||
/*
|
||||
/*
|
||||
* <moeoHypervolumeBinaryMetric.h>
|
||||
* Copyright (C) DOLPHIN Project-Team, INRIA Futurs, 2006-2007
|
||||
* (C) OPAC Team, LIFL, 2002-2007
|
||||
|
|
@ -52,8 +52,8 @@
|
|||
*/
|
||||
template < class ObjectiveVector >
|
||||
class moeoHypervolumeBinaryMetric : public moeoNormalizedSolutionVsSolutionBinaryMetric < ObjectiveVector, double >
|
||||
{
|
||||
public:
|
||||
{
|
||||
public:
|
||||
|
||||
/**
|
||||
* Ctor
|
||||
|
|
@ -61,20 +61,20 @@ public:
|
|||
*/
|
||||
moeoHypervolumeBinaryMetric(double _rho = 1.1) : rho(_rho)
|
||||
{
|
||||
// not-a-maximization problem check
|
||||
for (unsigned int i=0; i<ObjectiveVector::Traits::nObjectives(); i++)
|
||||
// not-a-maximization problem check
|
||||
for (unsigned int i=0; i<ObjectiveVector::Traits::nObjectives(); i++)
|
||||
{
|
||||
if (ObjectiveVector::Traits::maximizing(i))
|
||||
if (ObjectiveVector::Traits::maximizing(i))
|
||||
{
|
||||
throw std::runtime_error("Hypervolume binary metric not yet implemented for a maximization problem in moeoHypervolumeBinaryMetric");
|
||||
throw std::runtime_error("Hypervolume binary metric not yet implemented for a maximization problem in moeoHypervolumeBinaryMetric");
|
||||
}
|
||||
}
|
||||
// consistency check
|
||||
if (rho < 1)
|
||||
// consistency check
|
||||
if (rho < 1)
|
||||
{
|
||||
std::cout << "Warning, value used to compute the reference point rho for the hypervolume calculation must not be smaller than 1" << std::endl;
|
||||
std::cout << "Adjusted to 1" << std::endl;
|
||||
rho = 1;
|
||||
std::cout << "Warning, value used to compute the reference point rho for the hypervolume calculation must not be smaller than 1" << std::endl;
|
||||
std::cout << "Adjusted to 1" << std::endl;
|
||||
rho = 1;
|
||||
}
|
||||
}
|
||||
|
||||
|
|
@ -87,21 +87,21 @@ public:
|
|||
*/
|
||||
double operator()(const ObjectiveVector & _o1, const ObjectiveVector & _o2)
|
||||
{
|
||||
double result;
|
||||
// if _o2 is dominated by _o1
|
||||
if ( paretoComparator(_o2,_o1) )
|
||||
double result;
|
||||
// if _o2 is dominated by _o1
|
||||
if ( paretoComparator(_o2,_o1) )
|
||||
{
|
||||
result = - hypervolume(_o1, _o2, ObjectiveVector::Traits::nObjectives()-1);
|
||||
result = - hypervolume(_o1, _o2, ObjectiveVector::Traits::nObjectives()-1);
|
||||
}
|
||||
else
|
||||
else
|
||||
{
|
||||
result = hypervolume(_o2, _o1, ObjectiveVector::Traits::nObjectives()-1);
|
||||
result = hypervolume(_o2, _o1, ObjectiveVector::Traits::nObjectives()-1);
|
||||
}
|
||||
return result;
|
||||
return result;
|
||||
}
|
||||
|
||||
|
||||
private:
|
||||
private:
|
||||
|
||||
/** value used to compute the reference point from the worst values for each objective */
|
||||
double rho;
|
||||
|
|
@ -120,47 +120,47 @@ private:
|
|||
*/
|
||||
double hypervolume(const ObjectiveVector & _o1, const ObjectiveVector & _o2, const unsigned int _obj, const bool _flag = false)
|
||||
{
|
||||
double result;
|
||||
double range = rho * bounds[_obj].range();
|
||||
double max = bounds[_obj].minimum() + range;
|
||||
// value of _1 for the objective _obj
|
||||
double v1 = _o1[_obj];
|
||||
// value of _2 for the objective _obj (if _flag=true, v2=max)
|
||||
double v2;
|
||||
if (_flag)
|
||||
double result;
|
||||
double range = rho * bounds[_obj].range();
|
||||
double max = bounds[_obj].minimum() + range;
|
||||
// value of _1 for the objective _obj
|
||||
double v1 = _o1[_obj];
|
||||
// value of _2 for the objective _obj (if _flag=true, v2=max)
|
||||
double v2;
|
||||
if (_flag)
|
||||
{
|
||||
v2 = max;
|
||||
v2 = max;
|
||||
}
|
||||
else
|
||||
else
|
||||
{
|
||||
v2 = _o2[_obj];
|
||||
v2 = _o2[_obj];
|
||||
}
|
||||
// computation of the volume
|
||||
if (_obj == 0)
|
||||
// computation of the volume
|
||||
if (_obj == 0)
|
||||
{
|
||||
if (v1 < v2)
|
||||
if (v1 < v2)
|
||||
{
|
||||
result = (v2 - v1) / range;
|
||||
result = (v2 - v1) / range;
|
||||
}
|
||||
else
|
||||
else
|
||||
{
|
||||
result = 0;
|
||||
result = 0;
|
||||
}
|
||||
}
|
||||
else
|
||||
else
|
||||
{
|
||||
if (v1 < v2)
|
||||
if (v1 < v2)
|
||||
{
|
||||
result = ( hypervolume(_o1, _o2, _obj-1, true) * (v2 - v1) / range ) + ( hypervolume(_o1, _o2, _obj-1) * (max - v2) / range );
|
||||
result = ( hypervolume(_o1, _o2, _obj-1, true) * (v2 - v1) / range ) + ( hypervolume(_o1, _o2, _obj-1) * (max - v2) / range );
|
||||
}
|
||||
else
|
||||
else
|
||||
{
|
||||
result = hypervolume(_o1, _o2, _obj-1) * (max - v2) / range;
|
||||
result = hypervolume(_o1, _o2, _obj-1) * (max - v2) / range;
|
||||
}
|
||||
}
|
||||
return result;
|
||||
return result;
|
||||
}
|
||||
|
||||
};
|
||||
};
|
||||
|
||||
#endif /*MOEOHYPERVOLUMEBINARYMETRIC_H_*/
|
||||
|
|
|
|||
|
|
@ -1,4 +1,4 @@
|
|||
/*
|
||||
/*
|
||||
* <moeoMetric.h>
|
||||
* Copyright (C) DOLPHIN Project-Team, INRIA Futurs, 2006-2007
|
||||
* (C) OPAC Team, LIFL, 2002-2007
|
||||
|
|
@ -44,49 +44,56 @@
|
|||
/**
|
||||
* Base class for performance metrics (also known as quality indicators).
|
||||
*/
|
||||
class moeoMetric : public eoFunctorBase {};
|
||||
class moeoMetric : public eoFunctorBase
|
||||
{};
|
||||
|
||||
|
||||
/**
|
||||
* Base class for unary metrics.
|
||||
*/
|
||||
template < class A, class R >
|
||||
class moeoUnaryMetric : public eoUF < A, R >, public moeoMetric {};
|
||||
class moeoUnaryMetric : public eoUF < A, R >, public moeoMetric
|
||||
{};
|
||||
|
||||
|
||||
/**
|
||||
* Base class for binary metrics.
|
||||
*/
|
||||
template < class A1, class A2, class R >
|
||||
class moeoBinaryMetric : public eoBF < A1, A2, R >, public moeoMetric {};
|
||||
class moeoBinaryMetric : public eoBF < A1, A2, R >, public moeoMetric
|
||||
{};
|
||||
|
||||
|
||||
/**
|
||||
* Base class for unary metrics dedicated to the performance evaluation of a single solution's objective vector.
|
||||
*/
|
||||
template < class ObjectiveVector, class R >
|
||||
class moeoSolutionUnaryMetric : public moeoUnaryMetric < const ObjectiveVector &, R > {};
|
||||
class moeoSolutionUnaryMetric : public moeoUnaryMetric < const ObjectiveVector &, R >
|
||||
{};
|
||||
|
||||
|
||||
/**
|
||||
* Base class for unary metrics dedicated to the performance evaluation of a Pareto set (a vector of objective vectors)
|
||||
*/
|
||||
template < class ObjectiveVector, class R >
|
||||
class moeoVectorUnaryMetric : public moeoUnaryMetric < const std::vector < ObjectiveVector > &, R > {};
|
||||
class moeoVectorUnaryMetric : public moeoUnaryMetric < const std::vector < ObjectiveVector > &, R >
|
||||
{};
|
||||
|
||||
|
||||
/**
|
||||
* Base class for binary metrics dedicated to the performance comparison between two solutions's objective vectors.
|
||||
*/
|
||||
template < class ObjectiveVector, class R >
|
||||
class moeoSolutionVsSolutionBinaryMetric : public moeoBinaryMetric < const ObjectiveVector &, const ObjectiveVector &, R > {};
|
||||
class moeoSolutionVsSolutionBinaryMetric : public moeoBinaryMetric < const ObjectiveVector &, const ObjectiveVector &, R >
|
||||
{};
|
||||
|
||||
|
||||
/**
|
||||
* Base class for binary metrics dedicated to the performance comparison between two Pareto sets (two vectors of objective vectors)
|
||||
*/
|
||||
template < class ObjectiveVector, class R >
|
||||
class moeoVectorVsVectorBinaryMetric : public moeoBinaryMetric < const std::vector < ObjectiveVector > &, const std::vector < ObjectiveVector > &, R > {};
|
||||
class moeoVectorVsVectorBinaryMetric : public moeoBinaryMetric < const std::vector < ObjectiveVector > &, const std::vector < ObjectiveVector > &, R >
|
||||
{};
|
||||
|
||||
|
||||
#endif /*MOEOMETRIC_H_*/
|
||||
|
|
|
|||
|
|
@ -1,4 +1,4 @@
|
|||
/*
|
||||
/*
|
||||
* <moeoNormalizedSolutionVsSolutionBinaryMetric.h>
|
||||
* Copyright (C) DOLPHIN Project-Team, INRIA Futurs, 2006-2007
|
||||
* (C) OPAC Team, LIFL, 2002-2007
|
||||
|
|
@ -49,19 +49,19 @@
|
|||
*/
|
||||
template < class ObjectiveVector, class R >
|
||||
class moeoNormalizedSolutionVsSolutionBinaryMetric : public moeoSolutionVsSolutionBinaryMetric < ObjectiveVector, R >
|
||||
{
|
||||
public:
|
||||
{
|
||||
public:
|
||||
|
||||
/**
|
||||
* Default ctr for any moeoNormalizedSolutionVsSolutionBinaryMetric object
|
||||
*/
|
||||
moeoNormalizedSolutionVsSolutionBinaryMetric()
|
||||
{
|
||||
bounds.resize(ObjectiveVector::Traits::nObjectives());
|
||||
// initialize bounds in case someone does not want to use them
|
||||
for (unsigned int i=0; i<ObjectiveVector::Traits::nObjectives(); i++)
|
||||
bounds.resize(ObjectiveVector::Traits::nObjectives());
|
||||
// initialize bounds in case someone does not want to use them
|
||||
for (unsigned int i=0; i<ObjectiveVector::Traits::nObjectives(); i++)
|
||||
{
|
||||
bounds[i] = eoRealInterval(0,1);
|
||||
bounds[i] = eoRealInterval(0,1);
|
||||
}
|
||||
}
|
||||
|
||||
|
|
@ -74,12 +74,12 @@ public:
|
|||
*/
|
||||
void setup(double _min, double _max, unsigned int _obj)
|
||||
{
|
||||
if (_min == _max)
|
||||
if (_min == _max)
|
||||
{
|
||||
_min -= tiny();
|
||||
_max += tiny();
|
||||
_min -= tiny();
|
||||
_max += tiny();
|
||||
}
|
||||
bounds[_obj] = eoRealInterval(_min, _max);
|
||||
bounds[_obj] = eoRealInterval(_min, _max);
|
||||
}
|
||||
|
||||
|
||||
|
|
@ -90,7 +90,7 @@ public:
|
|||
*/
|
||||
virtual void setup(eoRealInterval _realInterval, unsigned int _obj)
|
||||
{
|
||||
bounds[_obj] = _realInterval;
|
||||
bounds[_obj] = _realInterval;
|
||||
}
|
||||
|
||||
|
||||
|
|
@ -99,15 +99,15 @@ public:
|
|||
*/
|
||||
static double tiny()
|
||||
{
|
||||
return 1e-6;
|
||||
return 1e-6;
|
||||
}
|
||||
|
||||
|
||||
protected:
|
||||
protected:
|
||||
|
||||
/** the bounds for every objective (bounds[i] = bounds for the objective i) */
|
||||
std::vector < eoRealInterval > bounds;
|
||||
|
||||
};
|
||||
};
|
||||
|
||||
#endif /*MOEONORMALIZEDSOLUTIONVSSOLUTIONBINARYMETRIC_H_*/
|
||||
|
|
|
|||
Loading…
Add table
Add a link
Reference in a new issue