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/*
* <moeoAdditiveEpsilonBinaryMetric.h>
* Copyright (C) DOLPHIN Project-Team, INRIA Futurs, 2006-2007
* (C) OPAC Team, LIFL, 2002-2007
*
* Arnaud Liefooghe
*
* 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
*
*/
//-----------------------------------------------------------------------------
#ifndef MOEOADDITIVEEPSILONBINARYMETRIC_H_
#define MOEOADDITIVEEPSILONBINARYMETRIC_H_
#include <metric/moeoNormalizedSolutionVsSolutionBinaryMetric.h>
/**
* Additive epsilon binary metric allowing to compare two objective vectors as proposed in
* Zitzler E., Thiele L., Laumanns M., Fonseca C. M., Grunert da Fonseca V.:
* Performance Assessment of Multiobjective Optimizers: An Analysis and Review. IEEE Transactions on Evolutionary Computation 7(2), pp.117–132 (2003).
*/
template < class ObjectiveVector >
class moeoAdditiveEpsilonBinaryMetric : public moeoNormalizedSolutionVsSolutionBinaryMetric < ObjectiveVector, double >
{
public:
/**
* Returns the minimal distance by which the objective vector _o1 must be translated in all objectives
* so that it weakly dominates the objective vector _o2
* @warning don't forget to set the bounds for every objective before the call of this function
* @param _o1 the first objective vector
* @param _o2 the second objective vector
*/
double operator()(const ObjectiveVector & _o1, const ObjectiveVector & _o2)
{
// computation of the epsilon value for the first objective
double result = epsilon(_o1, _o2, 0);
// computation of the epsilon value for the other objectives
double tmp;
for (unsigned int i=1; i<ObjectiveVector::Traits::nObjectives(); i++)
{
tmp = epsilon(_o1, _o2, i);
result = std::max(result, tmp);
}
// returns the maximum epsilon value
return result;
}
private:
/** the bounds for every objective */
using moeoNormalizedSolutionVsSolutionBinaryMetric < ObjectiveVector, double > :: bounds;
/**
* Returns the epsilon value by which the objective vector _o1 must be translated in the objective _obj
* so that it dominates the objective vector _o2
* @param _o1 the first objective vector
* @param _o2 the second objective vector
* @param _obj the index of the objective
*/
double epsilon(const ObjectiveVector & _o1, const ObjectiveVector & _o2, const unsigned int _obj)
{
double result;
// if the objective _obj have to be minimized
if (ObjectiveVector::Traits::minimizing(_obj))
{
// _o1[_obj] - _o2[_obj]
result = ( (_o1[_obj] - bounds[_obj].minimum()) / bounds[_obj].range() ) - ( (_o2[_obj] - bounds[_obj].minimum()) / bounds[_obj].range() );
}
// if the objective _obj have to be maximized
else
{
// _o2[_obj] - _o1[_obj]
result = ( (_o2[_obj] - bounds[_obj].minimum()) / bounds[_obj].range() ) - ( (_o1[_obj] - bounds[_obj].minimum()) / bounds[_obj].range() );
}
return result;
}
};
#endif /*MOEOADDITIVEEPSILONBINARYMETRIC_H_*/