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102
trunk/paradiseo-mo/src/algo/moRandomNeutralWalk.h
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102
trunk/paradiseo-mo/src/algo/moRandomNeutralWalk.h
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/*
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<moRandomNeutralWalk.h>
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Copyright (C) DOLPHIN Project-Team, INRIA Lille - Nord Europe, 2006-2010
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Sebastien Verel, Arnaud Liefooghe, Jeremie Humeau
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This software is governed by the CeCILL license under French law and
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abiding by the rules of distribution of free software. You can ue,
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modify and/ or redistribute the software under the terms of the CeCILL
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license as circulated by CEA, CNRS and INRIA at the following URL
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"http://www.cecill.info".
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In this respect, the user's attention is drawn to the risks associated
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with loading, using, modifying and/or developing or reproducing the
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software by the user in light of its specific status of free software,
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that may mean that it is complicated to manipulate, and that also
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therefore means that it is reserved for developers and experienced
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professionals having in-depth computer knowledge. Users are therefore
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encouraged to load and test the software's suitability as regards their
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requirements in conditions enabling the security of their systems and/or
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data to be ensured and, more generally, to use and operate it in the
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same conditions as regards security.
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The fact that you are presently reading this means that you have had
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knowledge of the CeCILL license and that you accept its terms.
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ParadisEO WebSite : http://paradiseo.gforge.inria.fr
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Contact: paradiseo-help@lists.gforge.inria.fr
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*/
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#ifndef _moRandomNeutralWalk_h
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#define _moRandomNeutralWalk_h
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#include <algo/moLocalSearch.h>
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#include <explorer/moRandomNeutralWalkExplorer.h>
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#include <continuator/moTrueContinuator.h>
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#include <eval/moEval.h>
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#include <eoEvalFunc.h>
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/********************************************************
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* Random Neutral Walk:
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* Random Neutral walk local search
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*
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* At each iteration,
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* one random neighbor with the same fitness is selected and replace the current solution
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* the algorithm stops when the number of steps is reached
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********************************************************/
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template<class Neighbor>
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class moRandomNeutralWalk: public moLocalSearch<Neighbor>
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{
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public:
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typedef typename Neighbor::EOT EOT;
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typedef moNeighborhood<Neighbor> Neighborhood ;
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/**
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* Simple constructor for a random walk
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* @param _neighborhood the neighborhood
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* @param _fullEval the full evaluation function
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* @param _eval neighbor's evaluation function
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* @param _nbStepMax number of step of the walk
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*/
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moRandomNeutralWalk(Neighborhood& _neighborhood, eoEvalFunc<EOT>& _fullEval, moEval<Neighbor>& _eval, unsigned _nbStepMax):
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moLocalSearch<Neighbor>(explorer, trueCont, _fullEval),
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explorer(_neighborhood, _eval, defaultSolNeighborComp, _nbStepMax)
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{}
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/**
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* Simple constructor for a random walk
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* @param _neighborhood the neighborhood
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* @param _fullEval the full evaluation function
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* @param _eval neighbor's evaluation function
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* @param _nbStepMax number of step of the walk
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* @param _cont an external continuator
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*/
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moRandomNeutralWalk(Neighborhood& _neighborhood, eoEvalFunc<EOT>& _fullEval, moEval<Neighbor>& _eval, unsigned _nbStepMax, moContinuator<Neighbor>& _cont):
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moLocalSearch<Neighbor>(explorer, _cont, _fullEval),
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explorer(_neighborhood, _eval, defaultSolNeighborComp, _nbStepMax)
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{}
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/**
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* Simple constructor for a random walk
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* @param _neighborhood the neighborhood
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* @param _fullEval the full evaluation function
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* @param _eval neighbor's evaluation function
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* @param _nbStepMax number of step of the walk
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* @param _cont an external continuator
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* @param _comp a solution vs neighbor comparator
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*/
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moRandomNeutralWalk(Neighborhood& _neighborhood, eoEvalFunc<EOT>& _fullEval, moEval<Neighbor>& _eval, unsigned _nbStepMax, moContinuator<Neighbor>& _cont, moSolNeighborComparator<Neighbor>& _comp):
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moLocalSearch<Neighbor>(explorer, _cont, _fullEval),
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explorer(_neighborhood, _eval, _comp, _nbStepMax)
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{}
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private:
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// always true continuator
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moTrueContinuator<Neighbor> trueCont;
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// the explorer of the random walk
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moRandomNeutralWalkExplorer<Neighbor> explorer;
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// compare the fitness values of the solution and the neighbor: true if strictly greater
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moSolNeighborComparator<Neighbor> defaultSolNeighborComp;
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};
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#endif
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102
trunk/paradiseo-mo/src/sampling/moFitnessCloudSampling.h
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102
trunk/paradiseo-mo/src/sampling/moFitnessCloudSampling.h
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/*
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<moFitnessCloudSampling.h>
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Copyright (C) DOLPHIN Project-Team, INRIA Lille - Nord Europe, 2006-2010
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Sebastien Verel, Arnaud Liefooghe, Jeremie Humeau
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This software is governed by the CeCILL license under French law and
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abiding by the rules of distribution of free software. You can use,
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modify and/ or redistribute the software under the terms of the CeCILL
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license as circulated by CEA, CNRS and INRIA at the following URL
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"http://www.cecill.info".
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As a counterpart to the access to the source code and rights to copy,
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modify and redistribute granted by the license, users are provided only
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with a limited warranty and the software's author, the holder of the
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economic rights, and the successive licensors have only limited liability.
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In this respect, the user's attention is drawn to the risks associated
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with loading, using, modifying and/or developing or reproducing the
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software by the user in light of its specific status of free software,
|
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that may mean that it is complicated to manipulate, and that also
|
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therefore means that it is reserved for developers and experienced
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professionals having in-depth computer knowledge. Users are therefore
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encouraged to load and test the software's suitability as regards their
|
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requirements in conditions enabling the security of their systems and/or
|
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data to be ensured and, more generally, to use and operate it in the
|
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same conditions as regards security.
|
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The fact that you are presently reading this means that you have had
|
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knowledge of the CeCILL license and that you accept its terms.
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ParadisEO WebSite : http://paradiseo.gforge.inria.fr
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Contact: paradiseo-help@lists.gforge.inria.fr
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*/
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#ifndef moFitnessCloudSampling_h
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#define moFitnessCloudSampling_h
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#include <eoInit.h>
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#include <neighborhood/moNeighborhood.h>
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#include <eval/moEval.h>
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#include <eoEvalFunc.h>
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#include <algo/moDummyLS.h>
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#include <continuator/moFitnessStat.h>
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#include <continuator/moNeighborFitnessStat.h>
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#include <sampling/moSampling.h>
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/**
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* To compute an estimation of the fitness cloud,
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* i.e. the scatter plot of solution fitness versus neighbor fitness:
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*
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* This class do nothing. See others mo(...)FitnessCloudSampling classes
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* with different fitness sampling methods
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*/
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template <class Neighbor>
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class moFitnessCloudSampling : public moSampling<Neighbor>
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{
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public:
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typedef typename Neighbor::EOT EOT ;
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using moSampling<Neighbor>::localSearch;
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/**
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* Default Constructor
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* @param _init initialisation method of the solution
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* @param _neighborhood neighborhood to get a neighbor
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* @param _fullEval Fitness function, full evaluation function
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* @param _eval neighbor evaluation, incremental evaluation function
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* @param _nbSol Number of solutions in the sample
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*/
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moFitnessCloudSampling(eoInit<EOT> & _init,
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moNeighborhood<Neighbor> & _neighborhood,
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eoEvalFunc<EOT>& _fullEval,
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moEval<Neighbor>& _eval,
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unsigned int _nbSol) :
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moSampling<Neighbor>(_init, * new moDummyLS<Neighbor>(_fullEval), fitnessStat),
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neighborhood(_neighborhood),
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fullEval(_fullEval),
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eval(_eval),
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nbSol(_nbSol)
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{
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// std::cout << "moFitnessCloudSampling: Warming to nothing will be sample." << std::endl;
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}
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/**
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* default destructor
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*/
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~moFitnessCloudSampling() {
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// delete the pointer on the local search which has been constructed in the constructor
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delete localSearch;
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}
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protected:
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moNeighborhood<Neighbor> & neighborhood;
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eoEvalFunc<EOT>& fullEval;
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moEval<Neighbor>& eval;
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unsigned int nbSol;
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moFitnessStat<EOT> fitnessStat;
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};
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#endif
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