update and new stuffs
git-svn-id: svn://scm.gforge.inria.fr/svnroot/paradiseo@203 331e1502-861f-0410-8da2-ba01fb791d7f
This commit is contained in:
parent
ad029622a0
commit
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9 changed files with 158 additions and 239 deletions
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@ -115,7 +115,7 @@ public:
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{
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if ( invalidFitness() )
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{
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throw std::runtime_error("invalid fitness");
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// throw std::runtime_error("invalid fitness");
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}
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return fitnessValue;
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}
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@ -157,7 +157,7 @@ public:
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{
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if ( invalidDiversity() )
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{
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throw std::runtime_error("invalid diversity");
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// throw std::runtime_error("invalid diversity");
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}
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return diversityValue;
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}
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@ -29,11 +29,14 @@
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#include <moeoFastNonDominatedSortingFitnessAssignment.h>
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#include <moeoFitnessAssignment.h>
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#include <moeoGenerationalReplacement.h>
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#include <moeoIndicatorBasedFitnessAssignment.h>
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#include <moeoRandomSelect.h>
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#include <moeoReplacement.h>
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#include <moeoRouletteSelect.h>
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#include <moeoSelectOne.h>
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#include <moeoStochTournamentSelect.h>
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#include <metric/moeoNormalizedSolutionVsSolutionBinaryMetric.h>
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#include <metric/moeoVectorVsSolutionBinaryMetric.h>
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/**
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* ...
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@ -49,12 +52,21 @@ eoAlgo < MOEOT > & do_make_algo(eoParser & _parser, eoState & _state, eoEvalFunc
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/* the fitness assignment strategy */
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string & fitnessParam = _parser.createParam(string("FastNonDominatedSorting"), "fitness",
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"Fitness assignment strategy parameter: FastNonDominatedSorting, ...", 'F', "Evolution Engine").value();
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"Fitness assignment strategy parameter: FastNonDominatedSorting, IndicatorBased...", 'F', "Evolution Engine").value();
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moeoFitnessAssignment < MOEOT > * fitnessAssignment;
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if (fitnessParam == string("FastNonDominatedSorting"))
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{
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fitnessAssignment = new moeoFastNonDominatedSortingFitnessAssignment < MOEOT> ();
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}
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/****************************************************************************************************************************/
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else if (fitnessParam == string("IndicatorBased"))
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{
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typedef typename MOEOT::ObjectiveVector ObjectiveVector;
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moeoAdditiveEpsilonBinaryMetric < ObjectiveVector > * e = new moeoAdditiveEpsilonBinaryMetric < ObjectiveVector >;
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moeoVectorVsSolutionBinaryMetric < ObjectiveVector, double > * metric = new moeoExponentialVectorVsSolutionBinaryMetric < ObjectiveVector> (e,0.001);
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fitnessAssignment = new moeoIndicatorBasedFitnessAssignment < MOEOT> (metric);
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}
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/****************************************************************************************************************************/
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else
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{
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string stmp = string("Invalid fitness assignment strategy: ") + fitnessParam;
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@ -1,84 +0,0 @@
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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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// moeoAdditiveEpsilonBinaryMetric.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 MOEOADDITIVEEPSILONBINARYMETRIC_H_
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#define MOEOADDITIVEEPSILONBINARYMETRIC_H_
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#include <metric/moeoMetric.h>
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/**
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* Additive epsilon binary metric allowing to compare two objective vectors as proposed in
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* Zitzler E., Thiele L., Laumanns M., Fonseca C. M., Grunert da Fonseca V.:
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* Performance Assessment of Multiobjective Optimizers: An Analysis and Review. IEEE Transactions on Evolutionary Computation 7(2), pp.117–132 (2003).
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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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* Returns the maximum epsilon value by which the objective vector _o1 must be translated in all objectives
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* so that it weakly dominates the objective vector _o2
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* @warning don't forget to set the bounds for every objective before the call of this function
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* @param _o1 the first objective vector
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* @param _o2 the second objective vector
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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 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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}
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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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/** the bounds for every objective */
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using moeoNormalizedSolutionVsSolutionBinaryMetric < ObjectiveVector, double > :: bounds;
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/**
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* Returns the epsilon value by which the objective vector _o1 must be translated in the objective _obj
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* so that it dominates the objective vector _o2
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* @param _o1 the first objective vector
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* @param _o2 the second objective vector
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* @param _obj the index of the objective
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*/
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double epsilon(const ObjectiveVector & _o1, const ObjectiveVector & _o2, const unsigned _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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{
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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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{
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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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}
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};
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#endif /*MOEOADDITIVEEPSILONBINARYMETRIC_H_*/
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@ -1,139 +0,0 @@
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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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// moeoHypervolumeBinaryMetric.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 MOEOHYPERVOLUMEBINARYMETRIC_H_
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#define MOEOHYPERVOLUMEBINARYMETRIC_H_
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#include <stdexcept>
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#include <metric/moeoMetric.h>
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/**
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* Hypervolume binary metric allowing to compare two objective vectors as proposed in
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* Zitzler E., Künzli S.: Indicator-Based Selection in Multiobjective Search. In Parallel Problem Solving from Nature (PPSN VIII).
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* Lecture Notes in Computer Science 3242, Springer, Birmingham, UK pp.832–842 (2004).
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* This indicator is based on the hypervolume concept introduced in
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* Zitzler, E., Thiele, L.: Multiobjective Optimization Using Evolutionary Algorithms - A Comparative Case Study.
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* Parallel Problem Solving from Nature (PPSN-V), pp.292-301 (1998).
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*/
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template < class ObjectiveVector >
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class moeoHypervolumeBinaryMetric : public moeoNormalizedSolutionVsSolutionBinaryMetric < ObjectiveVector, double >
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{
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public:
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/**
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* Ctor
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* @param _rho value used to compute the reference point from the worst values for each objective (default : 1.1)
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*/
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moeoHypervolumeBinaryMetric(double _rho = 1.1) : rho(_rho)
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{
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// not-a-maximization problem check
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for (unsigned i=0; i<ObjectiveVector::Traits::nObjectives(); i++)
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{
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if (ObjectiveVector::Traits::maximizing(i))
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{
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throw std::runtime_error("Hypervolume binary metric not yet implemented for a maximization problem in moeoHypervolumeBinaryMetric");
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}
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}
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// consistency check
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if (rho < 1)
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{
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cout << "Warning, value used to compute the reference point rho for the hypervolume calculation must not be smaller than 1" << endl;
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cout << "Adjusted to 1" << endl;
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rho = 1;
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}
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}
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/**
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* Returns the volume of the space that is dominated by _o2 but not by _o1 with respect to a reference point computed using rho.
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* @warning don't forget to set the bounds for every objective before the call of this function
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* @param _o1 the first objective vector
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* @param _o2 the second objective vector
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*/
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double operator()(const ObjectiveVector & _o1, const ObjectiveVector & _o2)
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{
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double result;
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// if _o1 dominates _o2
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if ( paretoComparator(_o1,_o2) )
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{
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result = - hypervolume(_o1, _o2, ObjectiveVector::Traits::nObjectives()-1);
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}
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else
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{
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result = hypervolume(_o2, _o1, ObjectiveVector::Traits::nObjectives()-1);
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}
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return result;
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}
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private:
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/** value used to compute the reference point from the worst values for each objective */
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double rho;
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/** the bounds for every objective */
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using moeoNormalizedSolutionVsSolutionBinaryMetric < ObjectiveVector, double > :: bounds;
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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 volume of the space that is dominated by _o2 but not by _o1 with respect to a reference point computed using rho for the objective _obj.
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* @param _o1 the first objective vector
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* @param _o2 the second objective vector
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* @param _obj the objective index
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* @param _flag used for iteration, if _flag=true _o2 is not talen into account (default : false)
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*/
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double hypervolume(const ObjectiveVector & _o1, const ObjectiveVector & _o2, const unsigned _obj, const bool _flag = false)
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{
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double result;
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double range = rho * bounds[_obj].range();
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double max = bounds[_obj].minimum() + range;
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// value of _1 for the objective _obj
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double v1 = _o1[_obj];
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// value of _2 for the objective _obj (if _flag=true, v2=max)
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double v2;
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if (_flag)
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{
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v2 = max;
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}
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else
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{
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v2 = _o2[_obj];
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}
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// computation of the volume
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if (_obj == 0)
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{
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if (v1 < v2)
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{
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result = (v2 - v1) / range;
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}
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else
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{
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result = 0;
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}
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}
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else
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{
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if (v1 < v2)
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{
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result = ( hypervolume(_o1, _o2, _obj-1, true) * (v2 - v1) / range ) + ( hypervolume(_o1, _o2, _obj-1) * (max - v2) / range );
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}
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else
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{
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result = hypervolume(_o1, _o2, _obj-1) * (max - v2) / range;
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}
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}
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return result;
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}
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};
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#endif /*MOEOHYPERVOLUMEBINARYMETRIC_H_*/
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@ -0,0 +1,42 @@
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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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// moeoConvertPopToObjectiveVectors.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 MOEOPOPTOOBJECTIVEVECTORS_H_
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#define MOEOPOPTOOBJECTIVEVECTORS_H_
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#include <eoFunctor.h>
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/**
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* Functor allowing to get a vector of objective vectors from a population
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*/
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template < class MOEOT, class ObjectiveVector = typename MOEOT::ObjectiveVector >
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class moeoConvertPopToObjectiveVectors : public eoUF < const eoPop < MOEOT >, const std::vector < ObjectiveVector > >
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{
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public:
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/**
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* Returns a vector of the objective vectors from the population _pop
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* @param _pop the population
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*/
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const std::vector < ObjectiveVector > operator()(const eoPop < MOEOT > _pop)
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{
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std::vector < ObjectiveVector > result;
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result.resize(_pop.size());
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for (unsigned i=0; i<_pop.size(); i++)
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{
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result.push_back(_pop[i].objectiveVector());
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}
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return result;
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}
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};
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#endif /*MOEOPOPTOOBJECTIVEVECTORS_H_*/
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#ifndef MOEODETTOURNAMENTSELECT_H_
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#define MOEODETTOURNAMENTSELECT_H_
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#include <moeoComparator.h>
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#include <moeoDiversityAssignment.h>
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#include <moeoFitnessAssignment.h>
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#include <moeoSelectOne.h>
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#include <moeoSelectors.h>
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@ -20,7 +23,7 @@
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* Selection strategy that selects ONE individual by deterministic tournament.
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*/
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template < class MOEOT >
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class moeoDetTournamentSelect:public moeoSelectOne <MOEOT>
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class moeoDetTournamentSelect : public moeoSelectOne <MOEOT>
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{
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public:
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@ -31,7 +34,7 @@ public:
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* @param _comparator the comparator (used to compare 2 individuals)
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* @param _tSize the number of individuals in the tournament (default: 2)
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*/
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moeoDetTournamentSelect (moeoFitnessAssignment < MOEOT > & _evalFitness, moeoDiversityAssignment < MOEOT > & _evalDiversity, moeoComparator < MOEOT > & _comparator, unsigned _tSize = 2) :
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moeoDetTournamentSelect(moeoFitnessAssignment < MOEOT > & _evalFitness, moeoDiversityAssignment < MOEOT > & _evalDiversity, moeoComparator < MOEOT > & _comparator, unsigned _tSize = 2) :
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evalFitness (_evalFitness), evalDiversity (_evalDiversity), comparator (_comparator), tSize (_tSize)
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{
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// consistency check
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@ -41,7 +44,7 @@ public:
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tSize = 2;
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}
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}
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/**
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* Ctor without comparator. A moeoFitnessThenDiversityComparator is used as default.
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@ -49,7 +52,7 @@ public:
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* @param _evalDiversity the diversity assignment strategy
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* @param _tSize the number of individuals in the tournament (default: 2)
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*/
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moeoDetTournamentSelect (moeoFitnessAssignment < MOEOT > &_evalFitness, moeoDiversityAssignment < MOEOT > &_evalDiversity, unsigned _tSize = 2) :
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moeoDetTournamentSelect (moeoFitnessAssignment < MOEOT > & _evalFitness, moeoDiversityAssignment < MOEOT > & _evalDiversity, unsigned _tSize = 2) :
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evalFitness (_evalFitness),evalDiversity(_evalDiversity),tSize(_tSize)
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{
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// a moeoFitThenDivComparator is used as default
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* Evaluate the fitness and the diversity of each individual of the population _pop.
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* @param _pop the population
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*/
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void setup (eoPop<MOEOT>& _pop)
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//void setup (eoPop<MOEOT>& _pop)
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virtual void setup(const eoPop<MOEOT>& _pop)
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{
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// eval fitness
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evalFitness(_pop);
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//evalFitness(_pop);
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// eval diversity
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evalDiversity(_pop);
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//evalDiversity(_pop);
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}
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* Apply the tournament to the given population
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* @param _pop the population
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*/
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const MOEOT & operator () (const eoPop < MOEOT > &_pop)
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const MOEOT & operator () (const eoPop < MOEOT > &_pop)
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{
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// use the selector
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return mo_deterministic_tournament(_pop,tSize,comparator);
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@ -25,7 +25,7 @@ class moeoDiversityAssignment : public eoUF < eoPop < MOEOT > &, void >
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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.
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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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@ -33,15 +33,18 @@ class moeoDummyDiversityAssignment : public moeoDiversityAssignment < MOEOT >
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public:
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/**
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* Sets the diversity to '0' for every individuals of the population _pop
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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 idx = 0; idx<_pop.size (); idx++)
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{
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// set the diversity to 0
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_pop[idx].diversity(0);
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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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@ -93,7 +93,12 @@ public:
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evalFitness (_parents);
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evalDiversity (_parents);
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// sorts the whole population according to the comparator
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std::sort (_parents.begin (), _parents.end (), comparator);
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/*************************************************************************/
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moeoFitnessThenDiversityComparator < MOEOT > comp;
|
||||
std::sort (_parents.begin (), _parents.end (), comp);
|
||||
/*************************************************************************/
|
||||
|
||||
// finally, resize this global population
|
||||
_parents.resize (sz);
|
||||
// and clear the offspring population
|
||||
|
|
|
|||
|
|
@ -0,0 +1,76 @@
|
|||
// -*- mode: c++; c-indent-level: 4; c++-member-init-indent: 8; comment-column: 35; -*-
|
||||
|
||||
//-----------------------------------------------------------------------------
|
||||
// moeoIndicatorBasedFitnessAssignment.h
|
||||
// (c) OPAC Team (LIFL), Dolphin Project (INRIA), 2007
|
||||
/*
|
||||
This library...
|
||||
|
||||
Contact: paradiseo-help@lists.gforge.inria.fr, http://paradiseo.gforge.inria.fr
|
||||
*/
|
||||
//-----------------------------------------------------------------------------
|
||||
|
||||
#ifndef MOEOINDICATORBASEDFITNESSASSIGNMENT_H_
|
||||
#define MOEOINDICATORBASEDFITNESSASSIGNMENT_H_
|
||||
|
||||
#include <eoPop.h>
|
||||
#include <moeoConvertPopToObjectiveVectors.h>
|
||||
#include <moeoFitnessAssignment.h>
|
||||
#include <metric/moeoNormalizedSolutionVsSolutionBinaryMetric.h>
|
||||
#include <metric/moeoVectorVsSolutionBinaryMetric.h>
|
||||
|
||||
/**
|
||||
*
|
||||
*/
|
||||
template < class MOEOT >
|
||||
class moeoIndicatorBasedFitnessAssignment : public moeoFitnessAssignment < MOEOT >
|
||||
{
|
||||
public:
|
||||
|
||||
/** The type of objective vector */
|
||||
typedef typename MOEOT::ObjectiveVector ObjectiveVector;
|
||||
|
||||
|
||||
/**
|
||||
* Default ctor
|
||||
* @param ...
|
||||
*/
|
||||
moeoIndicatorBasedFitnessAssignment(moeoVectorVsSolutionBinaryMetric < ObjectiveVector, double > * _metric) : metric(_metric)
|
||||
{}
|
||||
|
||||
|
||||
/**
|
||||
* Ctor
|
||||
* @param ...
|
||||
*/
|
||||
moeoIndicatorBasedFitnessAssignment(moeoNormalizedSolutionVsSolutionBinaryMetric < ObjectiveVector, double > * _solutionVsSolutionMetric, const double _kappa)// : metric(moeoExponentialVectorVsSolutionBinaryMetric < ObjectiveVector > (_solutionVsSolutionMetric, _kappa))
|
||||
{
|
||||
metric = new moeoExponentialVectorVsSolutionBinaryMetric < ObjectiveVector > (_solutionVsSolutionMetric, _kappa);
|
||||
}
|
||||
|
||||
|
||||
/**
|
||||
*
|
||||
*/
|
||||
void operator()(eoPop < MOEOT > & _pop)
|
||||
{
|
||||
eoPop < MOEOT > tmp_pop;
|
||||
moeoConvertPopToObjectiveVectors < MOEOT > convertor;
|
||||
for (unsigned i=0; i<_pop.size() ; i++)
|
||||
{
|
||||
tmp_pop.clear();
|
||||
tmp_pop = _pop;
|
||||
tmp_pop.erase(tmp_pop.begin() + i);
|
||||
_pop[i].fitness((*metric) (convertor(tmp_pop), _pop[i].objectiveVector()));
|
||||
}
|
||||
}
|
||||
|
||||
|
||||
|
||||
|
||||
private:
|
||||
moeoVectorVsSolutionBinaryMetric < ObjectiveVector, double > * metric;
|
||||
|
||||
};
|
||||
|
||||
#endif /*MOEOINDICATORBASEDFITNESSASSIGNMENT_H_*/
|
||||
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Add a link
Reference in a new issue