2d3587c1ee
git-svn-id: svn://scm.gforge.inria.fr/svnroot/paradiseo@656 331e1502-861f-0410-8da2-ba01fb791d7f
518 lines
19 KiB
C++
Executable file
518 lines
19 KiB
C++
Executable file
/*
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* <moeoIBMOLS.h>
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* Copyright (C) DOLPHIN Project-Team, INRIA Futurs, 2006-2007
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* (C) OPAC Team, LIFL, 2002-2007
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*
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* Arnaud Liefooghe
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*
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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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*
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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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*
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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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*
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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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*/
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//-----------------------------------------------------------------------------
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#ifndef MOEOIBMOLS_H_
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#define MOEOIBMOLS_H_
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#include <math.h>
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#include <eoContinue.h>
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#include <eoEvalFunc.h>
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#include <eoPop.h>
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#include <moMove.h>
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#include <moMoveInit.h>
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#include <moNextMove.h>
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#include <algo/moeoLS.h>
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#include <archive/moeoArchive.h>
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#include <fitness/moeoBinaryIndicatorBasedFitnessAssignment.h>
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#include <move/moeoMoveIncrEval.h>
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/**
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* Indicator-Based Multi-Objective Local Search (IBMOLS) as described in
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* Basseur M., Burke K. : "Indicator-Based Multi-Objective Local Search" (2007).
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*/
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template < class MOEOT, class Move >
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class moeoIBMOLS : public moeoLS < MOEOT, eoPop < MOEOT > & >
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{
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public:
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/** The type of objective vector */
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typedef typename MOEOT::ObjectiveVector ObjectiveVector;
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/**
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* Ctor.
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* @param _moveInit the move initializer
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* @param _nextMove the neighborhood explorer
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* @param _eval the full evaluation
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* @param _moveIncrEval the incremental evaluation
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* @param _fitnessAssignment the fitness assignment strategy
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* @param _continuator the stopping criteria
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*/
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moeoIBMOLS(
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moMoveInit < Move > & _moveInit,
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moNextMove < Move > & _nextMove,
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eoEvalFunc < MOEOT > & _eval,
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moeoMoveIncrEval < Move > & _moveIncrEval,
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moeoBinaryIndicatorBasedFitnessAssignment < MOEOT > & _fitnessAssignment,
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eoContinue < MOEOT > & _continuator
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) :
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moveInit(_moveInit),
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nextMove(_nextMove),
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eval(_eval),
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moveIncrEval(_moveIncrEval),
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fitnessAssignment (_fitnessAssignment),
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continuator (_continuator)
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{}
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/**
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* Apply the local search until a local archive does not change or
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* another stopping criteria is met and update the archive _arch with new non-dominated solutions.
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* @param _pop the initial population
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* @param _arch the (updated) archive
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*/
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void operator() (eoPop < MOEOT > & _pop, moeoArchive < MOEOT > & _arch)
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{
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// evaluation of the objective values
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/*
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for (unsigned int i=0; i<_pop.size(); i++)
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{
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eval(_pop[i]);
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}
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*/
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// fitness assignment for the whole population
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fitnessAssignment(_pop);
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// creation of a local archive
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moeoArchive < MOEOT > archive;
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// creation of another local archive (for the stopping criteria)
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moeoArchive < MOEOT > previousArchive;
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// update the archive with the initial population
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archive.update(_pop);
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do
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{
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previousArchive.update(archive);
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oneStep(_pop);
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archive.update(_pop);
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} while ( (! archive.equals(previousArchive)) && (continuator(_arch)) );
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_arch.update(archive);
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}
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private:
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/** the move initializer */
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moMoveInit < Move > & moveInit;
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/** the neighborhood explorer */
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moNextMove < Move > & nextMove;
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/** the full evaluation */
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eoEvalFunc < MOEOT > & eval;
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/** the incremental evaluation */
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moeoMoveIncrEval < Move > & moveIncrEval;
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/** the fitness assignment strategy */
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moeoBinaryIndicatorBasedFitnessAssignment < MOEOT > & fitnessAssignment;
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/** the stopping criteria */
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eoContinue < MOEOT > & continuator;
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/**
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* Apply one step of the local search to the population _pop
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* @param _pop the population
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*/
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void oneStep (eoPop < MOEOT > & _pop)
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{
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// the move
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Move move;
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// the objective vector and the fitness of the current solution
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ObjectiveVector x_objVec;
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double x_fitness;
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// the index, the objective vector and the fitness of the worst solution in the population (-1 implies that the worst is the newly created one)
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int worst_idx;
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ObjectiveVector worst_objVec;
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double worst_fitness;
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////////////////////////////////////////////
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// the indexes and the objective vectors of the extreme non-dominated points
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int ext_0_idx, ext_1_idx;
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ObjectiveVector ext_0_objVec, ext_1_objVec;
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unsigned int ind;
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////////////////////////////////////////////
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// the index of the current solution to be explored
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unsigned int i=0;
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// initilization of the move for the first individual
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moveInit(move, _pop[i]);
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while (i<_pop.size() && continuator(_pop))
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{
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// x = one neigbour of pop[i]
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// evaluate x in the objective space
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x_objVec = moveIncrEval(move, _pop[i]);
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// update every fitness values to take x into account and compute the fitness of x
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x_fitness = fitnessAssignment.updateByAdding(_pop, x_objVec);
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////////////////////////////////////////////////////////////////////////////////////////////////////////////
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////////////////////////////////////////////////////////////////////////////////////////////////////////////
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////////////////////////////////////////////////////////////////////////////////////////////////////////////
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// extreme solutions (min only!)
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ext_0_idx = -1;
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ext_0_objVec = x_objVec;
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ext_1_idx = -1;
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ext_1_objVec = x_objVec;
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for (unsigned int k=0; k<_pop.size(); k++)
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{
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// ext_0
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if (_pop[k].objectiveVector()[0] < ext_0_objVec[0])
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{
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ext_0_idx = k;
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ext_0_objVec = _pop[k].objectiveVector();
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}
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else if ( (_pop[k].objectiveVector()[0] == ext_0_objVec[0]) && (_pop[k].objectiveVector()[1] < ext_0_objVec[1]) )
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{
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ext_0_idx = k;
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ext_0_objVec = _pop[k].objectiveVector();
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}
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// ext_1
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else if (_pop[k].objectiveVector()[1] < ext_1_objVec[1])
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{
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ext_1_idx = k;
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ext_1_objVec = _pop[k].objectiveVector();
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}
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else if ( (_pop[k].objectiveVector()[1] == ext_1_objVec[1]) && (_pop[k].objectiveVector()[0] < ext_1_objVec[0]) )
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{
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ext_1_idx = k;
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ext_1_objVec = _pop[k].objectiveVector();
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}
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}
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// worst init
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if (ext_0_idx == -1)
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{
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ind = 0;
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while (ind == ext_1_idx)
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{
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ind++;
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}
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worst_idx = ind;
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worst_objVec = _pop[ind].objectiveVector();
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worst_fitness = _pop[ind].fitness();
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}
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else if (ext_1_idx == -1)
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{
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ind = 0;
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while (ind == ext_0_idx)
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{
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ind++;
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}
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worst_idx = ind;
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worst_objVec = _pop[ind].objectiveVector();
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worst_fitness = _pop[ind].fitness();
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}
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else
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{
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worst_idx = -1;
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worst_objVec = x_objVec;
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worst_fitness = x_fitness;
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}
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////////////////////////////////////////////////////////////////////////////////////////////////////////////
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////////////////////////////////////////////////////////////////////////////////////////////////////////////
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////////////////////////////////////////////////////////////////////////////////////////////////////////////
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// who is the worst ?
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for (unsigned int j=0; j<_pop.size(); j++)
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{
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if ( (j!=ext_0_idx) && (j!=ext_1_idx) )
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{
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if (_pop[j].fitness() < worst_fitness)
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{
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worst_idx = j;
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worst_objVec = _pop[j].objectiveVector();
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worst_fitness = _pop[j].fitness();
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}
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}
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}
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// if the worst solution is the new one
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if (worst_idx == -1)
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{
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// if all its neighbours have been explored,
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// let's explore the neighborhoud of the next individual
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if (! nextMove(move, _pop[i]))
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{
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i++;
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if (i<_pop.size())
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{
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// initilization of the move for the next individual
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moveInit(move, _pop[i]);
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}
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}
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}
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// if the worst solution is located before _pop[i]
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else if (worst_idx <= i)
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{
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// the new solution takes place insteed of _pop[worst_idx]
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_pop[worst_idx] = _pop[i];
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move(_pop[worst_idx]);
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_pop[worst_idx].objectiveVector(x_objVec);
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_pop[worst_idx].fitness(x_fitness);
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// let's explore the neighborhoud of the next individual
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i++;
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if (i<_pop.size())
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{
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// initilization of the move for the next individual
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moveInit(move, _pop[i]);
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}
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}
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// if the worst solution is located after _pop[i]
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else if (worst_idx > i)
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{
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// the new solution takes place insteed of _pop[i+1] and _pop[worst_idx] is deleted
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_pop[worst_idx] = _pop[i+1];
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_pop[i+1] = _pop[i];
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move(_pop[i+1]);
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_pop[i+1].objectiveVector(x_objVec);
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_pop[i+1].fitness(x_fitness);
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// let's explore the neighborhoud of the individual _pop[i+2]
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i += 2;
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if (i<_pop.size())
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{
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// initilization of the move for the next individual
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moveInit(move, _pop[i]);
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}
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}
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// update fitness values
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fitnessAssignment.updateByDeleting(_pop, worst_objVec);
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}
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}
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// INUTILE !!!!
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/**
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* Apply one step of the local search to the population _pop
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* @param _pop the population
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*/
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void new_oneStep (eoPop < MOEOT > & _pop)
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{
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// the move
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Move move;
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// the objective vector and the fitness of the current solution
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ObjectiveVector x_objVec;
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double x_fitness;
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// the index, the objective vector and the fitness of the worst solution in the population (-1 implies that the worst is the newly created one)
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int worst_idx;
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ObjectiveVector worst_objVec;
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double worst_fitness;
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////////////////////////////////////////////
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// the index of the extreme non-dominated points
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int ext_0_idx, ext_1_idx;
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unsigned int ind;
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////////////////////////////////////////////
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// the index current of the current solution to be explored
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unsigned int i=0;
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// initilization of the move for the first individual
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moveInit(move, _pop[i]);
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while (i<_pop.size() && continuator(_pop))
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{
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// x = one neigbour of pop[i]
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// evaluate x in the objective space
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x_objVec = moveIncrEval(move, _pop[i]);
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// update every fitness values to take x into account and compute the fitness of x
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x_fitness = fitnessAssignment.updateByAdding(_pop, x_objVec);
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////////////////////////////////////////////////////////////////////////////////////////////////////////////
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////////////////////////////////////////////////////////////////////////////////////////////////////////////
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////////////////////////////////////////////////////////////////////////////////////////////////////////////
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// extremes solutions
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OneObjectiveComparator comp0(0);
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ext_0_idx = std::min_element(_pop.begin(), _pop.end(), comp0) - _pop.begin();
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OneObjectiveComparator comp1(1);
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ext_1_idx = std::min_element(_pop.begin(), _pop.end(), comp1) - _pop.begin();
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// new = extreme ?
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if (x_objVec[0] < _pop[ext_0_idx].objectiveVector()[0])
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{
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ext_0_idx = -1;
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}
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else if ( (x_objVec[0] == _pop[ext_0_idx].objectiveVector()[0]) && (x_objVec[1] < _pop[ext_0_idx].objectiveVector()[1]) )
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{
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ext_0_idx = -1;
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}
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else if (x_objVec[1] < _pop[ext_1_idx].objectiveVector()[1])
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{
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ext_1_idx = -1;
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}
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else if ( (x_objVec[1] == _pop[ext_1_idx].objectiveVector()[1]) && (x_objVec[0] < _pop[ext_1_idx].objectiveVector()[0]) )
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{
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ext_1_idx = -1;
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}
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// worst init
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if (ext_0_idx == -1)
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{
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ind = 0;
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while (ind == ext_1_idx)
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{
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ind++;
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}
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worst_idx = ind;
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worst_objVec = _pop[ind].objectiveVector();
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worst_fitness = _pop[ind].fitness();
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}
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else if (ext_1_idx == -1)
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{
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ind = 0;
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while (ind == ext_0_idx)
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{
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ind++;
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}
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worst_idx = ind;
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worst_objVec = _pop[ind].objectiveVector();
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worst_fitness = _pop[ind].fitness();
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}
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else
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{
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worst_idx = -1;
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worst_objVec = x_objVec;
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worst_fitness = x_fitness;
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}
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////////////////////////////////////////////////////////////////////////////////////////////////////////////
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////////////////////////////////////////////////////////////////////////////////////////////////////////////
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////////////////////////////////////////////////////////////////////////////////////////////////////////////
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// who is the worst ?
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for (unsigned int j=0; j<_pop.size(); j++)
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{
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if ( (j!=ext_0_idx) && (j!=ext_1_idx) )
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{
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if (_pop[j].fitness() < worst_fitness)
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{
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worst_idx = j;
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worst_objVec = _pop[j].objectiveVector();
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worst_fitness = _pop[j].fitness();
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}
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}
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}
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// if the worst solution is the new one
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if (worst_idx == -1)
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{
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// if all its neighbours have been explored,
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// let's explore the neighborhoud of the next individual
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if (! nextMove(move, _pop[i]))
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{
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i++;
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if (i<_pop.size())
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{
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// initilization of the move for the next individual
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moveInit(move, _pop[i]);
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}
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}
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}
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// if the worst solution is located before _pop[i]
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else if (worst_idx <= i)
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{
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// the new solution takes place insteed of _pop[worst_idx]
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_pop[worst_idx] = _pop[i];
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move(_pop[worst_idx]);
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_pop[worst_idx].objectiveVector(x_objVec);
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_pop[worst_idx].fitness(x_fitness);
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// let's explore the neighborhoud of the next individual
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i++;
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if (i<_pop.size())
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{
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// initilization of the move for the next individual
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moveInit(move, _pop[i]);
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}
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}
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// if the worst solution is located after _pop[i]
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else if (worst_idx > i)
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{
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// the new solution takes place insteed of _pop[i+1] and _pop[worst_idx] is deleted
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_pop[worst_idx] = _pop[i+1];
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_pop[i+1] = _pop[i];
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move(_pop[i+1]);
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_pop[i+1].objectiveVector(x_objVec);
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_pop[i+1].fitness(x_fitness);
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// let's explore the neighborhoud of the individual _pop[i+2]
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i += 2;
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if (i<_pop.size())
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{
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// initilization of the move for the next individual
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moveInit(move, _pop[i]);
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}
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}
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// update fitness values
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fitnessAssignment.updateByDeleting(_pop, worst_objVec);
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}
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}
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//////////////////////////////////////////////////////////////////////////////////////////
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class OneObjectiveComparator : public moeoComparator < MOEOT >
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{
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public:
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OneObjectiveComparator(unsigned int _obj) : obj(_obj)
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{
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if (obj > MOEOT::ObjectiveVector::nObjectives())
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{
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throw std::runtime_error("Problem with the index of objective in OneObjectiveComparator");
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}
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}
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const bool operator()(const MOEOT & _moeo1, const MOEOT & _moeo2)
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{
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if (_moeo1.objectiveVector()[obj] < _moeo2.objectiveVector()[obj])
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{
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return true;
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}
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else
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{
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return (_moeo1.objectiveVector()[obj] == _moeo2.objectiveVector()[obj]) && (_moeo1.objectiveVector()[(obj+1)%2] < _moeo2.objectiveVector()[(obj+1)%2]);
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}
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}
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private:
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unsigned int obj;
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};
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//////////////////////////////////////////////////////////////////////////////////////////
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};
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#endif /*MOEOIBMOLS_H_*/
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