e3a610506b
git-svn-id: svn://scm.gforge.inria.fr/svnroot/paradiseo@2710 331e1502-861f-0410-8da2-ba01fb791d7f
171 lines
6.4 KiB
C++
171 lines
6.4 KiB
C++
/*
|
|
* <moeoConstraintFitnessAssignment.h>
|
|
* Copyright (C) DOLPHIN Project-Team, INRIA Lille-Nord Europe, 2006-2008
|
|
* (C) OPAC Team, LIFL, 2002-2008
|
|
*
|
|
* François Legillon
|
|
*
|
|
* This software is governed by the CeCILL license under French law and
|
|
* abiding by the rules of distribution of free software. You can use,
|
|
* modify and/ or redistribute the software under the terms of the CeCILL
|
|
* license as circulated by CEA, CNRS and INRIA at the following URL
|
|
* "http://www.cecill.info".
|
|
*
|
|
* As a counterpart to the access to the source code and rights to copy,
|
|
* modify and redistribute granted by the license, users are provided only
|
|
* with a limited warranty and the software's author, the holder of the
|
|
* economic rights, and the successive licensors have only limited liability.
|
|
*
|
|
* In this respect, the user's attention is drawn to the risks associated
|
|
* with loading, using, modifying and/or developing or reproducing the
|
|
* software by the user in light of its specific status of free software,
|
|
* that may mean that it is complicated to manipulate, and that also
|
|
* therefore means that it is reserved for developers and experienced
|
|
* professionals having in-depth computer knowledge. Users are therefore
|
|
* encouraged to load and test the software's suitability as regards their
|
|
* requirements in conditions enabling the security of their systems and/or
|
|
* data to be ensured and, more generally, to use and operate it in the
|
|
* same conditions as regards security.
|
|
* The fact that you are presently reading this means that you have had
|
|
* knowledge of the CeCILL license and that you accept its terms.
|
|
*
|
|
* ParadisEO WebSite : http://paradiseo.gforge.inria.fr
|
|
* Contact: paradiseo-help@lists.gforge.inria.fr
|
|
*
|
|
*/
|
|
//-----------------------------------------------------------------------------
|
|
// moeoConstraintFitnessAssignment.h
|
|
//-----------------------------------------------------------------------------
|
|
#ifndef MOEOCONSTRAINTFITNESSASSIGNMENT_H_
|
|
#define MOEOCONSTRAINTFITNESSASSIGNMENT_H_
|
|
|
|
#include <eoPop.h>
|
|
#include <fitness/moeoSingleObjectivization.h>
|
|
#include <utils/moeoObjectiveVectorNormalizer.h>
|
|
|
|
/*
|
|
* Fitness assignment scheme which give a penalty if MOEOT does not respect constraints
|
|
*/
|
|
template < class MOEOT >
|
|
class moeoConstraintFitnessAssignment : public moeoSingleObjectivization < MOEOT >
|
|
{
|
|
public:
|
|
|
|
/** the objective vector type of the solutions */
|
|
typedef typename MOEOT::ObjectiveVector ObjectiveVector;
|
|
/** the fitness type of the solutions */
|
|
typedef typename MOEOT::Fitness Fitness;
|
|
/** the type of the solutions */
|
|
typedef typename ObjectiveVector::Type Type;
|
|
|
|
/**
|
|
* Default ctor
|
|
* @param _weight vectors contains all weights to apply for not respecting the contraint in each dimension.
|
|
* @param _constraint vector containing the constraints, normalizer is applied to it
|
|
* @param _to_optimize dimension in which we ignore the constraint
|
|
* @param _normalizer normalizer to apply to each objective
|
|
*/
|
|
moeoConstraintFitnessAssignment(std::vector<double> & _weight, ObjectiveVector &_constraint, int _to_optimize, moeoObjectiveVectorNormalizer<MOEOT> &_normalizer, eoEvalFunc<MOEOT> &_eval) : weight(_weight),constraint(_constraint),to_optimize(_to_optimize),normalizer(_normalizer),eval(_eval),to_eval(true){}
|
|
|
|
/**
|
|
* Ctor with a dummy eval
|
|
* @param _weight vectors contains all weights to apply for not respecting the contraint in each dimension.
|
|
* @param _constraint vector containing the constraints, normalizer is applied to it
|
|
* @param _to_optimize dimension in which we ignore the constraint
|
|
* @param _normalizer normalizer to apply to each objective
|
|
*/
|
|
moeoConstraintFitnessAssignment(std::vector<double> & _weight, ObjectiveVector &_constraint, int _to_optimize, moeoObjectiveVectorNormalizer<MOEOT> &_normalizer) : weight(_weight), constraint(_constraint), to_optimize(_to_optimize), normalizer(_normalizer), eval(defaultEval), to_eval(false){}
|
|
|
|
/**
|
|
* Sets the fitness values for every solution contained in the population _pop (and in the archive)
|
|
* @param _mo the MOEOT
|
|
*/
|
|
void operator()(MOEOT & _mo){
|
|
if (to_eval && _mo.invalidObjectiveVector())
|
|
eval(_mo);
|
|
_mo.fitness(operator()(_mo.objectiveVector()));
|
|
}
|
|
|
|
/**
|
|
* Calculate a fitness from a valid objectiveVector
|
|
* @param _mo a valid objectiveVector
|
|
* @return the fitness of _mo
|
|
*/
|
|
Fitness operator()(const typename MOEOT::ObjectiveVector & _mo){
|
|
unsigned int dim=_mo.nObjectives();
|
|
Fitness res=0;
|
|
if (dim>weight.size()){
|
|
std::cout<<"moeoAggregationFitnessAssignmentFitness: ouch, given weight dimension is smaller than MOEOTs"<<std::endl;
|
|
}
|
|
else{
|
|
for(unsigned int l=0; l<dim; l++){
|
|
if ((int)l==to_optimize)
|
|
if (_mo.minimizing(l))
|
|
res-=(normalizer(_mo)[l]) * weight[l];
|
|
else
|
|
res+=(normalizer(_mo)[l]) * weight[l];
|
|
else{
|
|
if(_mo.minimizing(l)){
|
|
if (normalizer(_mo)[l]>normalizer(constraint)[l])
|
|
res-=(normalizer(_mo)[l]-normalizer(constraint)[l])*weight[l];
|
|
}
|
|
else{
|
|
if (normalizer(_mo)[l]<normalizer(constraint)[l])
|
|
//negative so we add it instead of removing it
|
|
res+=(normalizer(_mo)[l]-normalizer(constraint)[l])*weight[l];
|
|
}
|
|
}
|
|
}
|
|
}
|
|
return res;
|
|
}
|
|
|
|
/**
|
|
* Sets the fitness values for every solution contained in the population _pop (and in the archive)
|
|
* @param _pop the population
|
|
*/
|
|
void operator()(eoPop < MOEOT > & _pop)
|
|
{
|
|
for(unsigned int k=0; k<_pop.size(); k++)
|
|
operator()(_pop[k]);
|
|
}
|
|
|
|
/**
|
|
* Warning: no yet implemented: Updates the fitness 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)
|
|
{
|
|
//std::cout << "WARNING : updateByDeleting not implemented in moeoAssignmentFitnessAssignment" << std::endl;
|
|
}
|
|
|
|
private:
|
|
|
|
//dummy evaluation function
|
|
class DummyEval: public eoEvalFunc<MOEOT>{
|
|
void operator()(MOEOT &moeo){
|
|
}
|
|
} defaultEval;
|
|
|
|
//the vector of weight
|
|
std::vector<double> weight;
|
|
|
|
//the vector of constraints
|
|
ObjectiveVector constraint;
|
|
|
|
//index of the objective to optimize
|
|
int to_optimize;
|
|
|
|
//the normalizer
|
|
moeoObjectiveVectorNormalizer<MOEOT>& normalizer;
|
|
|
|
//the evaluation function
|
|
eoEvalFunc<MOEOT> &eval;
|
|
|
|
//true if the evaluation has to be done
|
|
bool to_eval;
|
|
|
|
};
|
|
|
|
#endif /*MOEOAGGREGATIONFITNESSASSIGNMENT_H_*/
|