moeoAchievementFitnessAssignment.h

/* 
* <moeoAchievementFitnessAssignment.h>
* Copyright (C) DOLPHIN Project-Team, INRIA Futurs, 2006-2007
* (C) OPAC Team, LIFL, 2002-2007
*
* AbdelHakim Deneche, 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 MOEOACHIEVEMENTFITNESSASSIGNMENT_H_
#define MOEOACHIEVEMENTFITNESSASSIGNMENT_H_

#include <vector>
#include <eoPop.h>
#include <fitness/moeoScalarFitnessAssignment.h>

template < class MOEOT >
class moeoAchievementFitnessAssignment : public moeoScalarFitnessAssignment < MOEOT >
{
public:

    typedef typename MOEOT::ObjectiveVector ObjectiveVector;


    moeoAchievementFitnessAssignment(ObjectiveVector & _reference, std::vector < double > & _lambdas, double _spn=0.0001) : reference(_reference), lambdas(_lambdas), spn(_spn)
    {
        // consistency check
        if ((spn < 0.0) || (spn > 1.0))
        {
            std::cout << "Warning, the arbitrary small positive number should be > 0 and <<1, adjusted to 0.0001\n";
            spn = 0.0001;
        }
    }


    moeoAchievementFitnessAssignment(ObjectiveVector & _reference, double _spn=0.0001) : reference(_reference), spn(_spn)
    {
        // compute the default values for lambdas
        lambdas  = std::vector < double > (ObjectiveVector::nObjectives());
        for (unsigned int i=0 ; i<lambdas.size(); i++)
        {
            lambdas[i] = 1.0 / ObjectiveVector::nObjectives();
        }
        // consistency check
        if ((spn < 0.0) || (spn > 1.0))
        {
            std::cout << "Warning, the arbitrary small positive number should be > 0 and <<1, adjusted to 0.0001\n";
            spn = 0.0001;
        }
    }


    virtual void operator()(eoPop < MOEOT > & _pop)
    {
        for (unsigned int i=0; i<_pop.size() ; i++)
        {
            compute(_pop[i]);
        }
    }


    void updateByDeleting(eoPop < MOEOT > & _pop, ObjectiveVector & _objVec)
    {
        // nothing to do ;-)
    }


    void setReference(const ObjectiveVector & _reference)
    {
        reference = _reference;
    }


private:

    ObjectiveVector reference;
    std::vector < double > lambdas;
    double spn;


    double inf() const
    {
        return std::numeric_limits<double>::max();
    }


    void compute(MOEOT & _moeo)
    {
        unsigned int nobj = MOEOT::ObjectiveVector::nObjectives();
        double temp;
        double min = inf();
        double sum = 0;
        for (unsigned int obj=0; obj<nobj; obj++)
        {
            temp = lambdas[obj] * (reference[obj] - _moeo.objectiveVector()[obj]);
            min = std::min(min, temp);
            sum += temp;
        }
        _moeo.fitness(min + spn*sum);
    }

};

#endif /*MOEOACHIEVEMENTFITNESSASSIGNMENT_H_*/

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