359 lines
13 KiB
C++
359 lines
13 KiB
C++
/*
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* <moeoHyperVolumeMetric.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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* Jeremie Humeau
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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 MOEOHYPERVOLUMEMETRIC_H_
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#define MOEOHYPERVOLUMEMETRIC_H_
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#include <metric/moeoMetric.h>
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/**
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* The contribution metric evaluates the proportion of non-dominated solutions given by a Pareto set relatively to another Pareto set
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* (Meunier, Talbi, Reininger: 'A multiobjective genetic algorithm for radio network optimization', in Proc. of the 2000 Congress on Evolutionary Computation, IEEE Press, pp. 317-324)
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*/
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template < class ObjectiveVector >
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class moeoHyperVolumeMetric : public moeoVectorUnaryMetric < ObjectiveVector , double >
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{
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public:
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/**
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* Constructor with a coefficient (rho)
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* @param _normalize allow to normalize data (default true)
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* @param _rho coefficient to determine the reference point.
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*/
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moeoHyperVolumeMetric(bool _normalize=true, double _rho=1.1): normalize(_normalize), rho(_rho), ref_point(NULL){
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bounds.resize(ObjectiveVector::Traits::nObjectives());
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// initialize bounds in case someone does not want to use them
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for (unsigned int i=0; i<ObjectiveVector::Traits::nObjectives(); i++)
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{
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bounds[i] = eoRealInterval(0,1);
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}
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}
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/**
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* Constructor with a reference point
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* @param _normalize allow to normalize data (default true)
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* @param _ref_point the reference point
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*/
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moeoHyperVolumeMetric(bool _normalize=true, ObjectiveVector& _ref_point=NULL): normalize(_normalize), rho(0.0), ref_point(_ref_point){
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bounds.resize(ObjectiveVector::Traits::nObjectives());
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// initialize bounds in case someone does not want to use them
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for (unsigned int i=0; i<ObjectiveVector::Traits::nObjectives(); i++)
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{
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bounds[i] = eoRealInterval(0,1);
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}
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}
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/**
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* Constructor with a reference point
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* @param _ref_point the reference point
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* @param _bounds bounds value
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*/
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moeoHyperVolumeMetric(ObjectiveVector& _ref_point, std::vector < eoRealInterval >& _bounds): normalize(false), rho(0.0), ref_point(_ref_point), bounds(_bounds){}
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/**
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* calculates and returns the HyperVolume value of a pareto front
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* @param _set the vector contains all objective Vector of pareto front
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*/
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double operator()(const std::vector < ObjectiveVector > & _set)
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{
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std::vector < std::vector<double> > front;
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//determine the reference point if a coefficient is passed in paremeter
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if(rho >= 1.0){
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//determine bounds
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setup(_set);
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//determine reference point
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for (unsigned int i=0; i<ObjectiveVector::Traits::nObjectives(); i++){
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if(normalize){
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if (ObjectiveVector::Traits::minimizing(i))
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ref_point[i]= rho;
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else
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ref_point[i]= 1-rho;
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}
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else{
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if (ObjectiveVector::Traits::minimizing(i))
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ref_point[i]= bounds[i].maximum() * rho;
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else
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ref_point[i]= bounds[i].maximum() * (1-rho);
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}
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}
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//if no normalization, reinit bounds to O..1 for
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if(!normalize)
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for (unsigned int i=0; i<ObjectiveVector::Traits::nObjectives(); i++)
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bounds[i] = eoRealInterval(0,1);
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}
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else if(normalize)
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setup(_set);
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front.resize(_set.size());
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for(unsigned int i=0; i < _set.size(); i++){
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front[i].resize(ObjectiveVector::Traits::nObjectives());
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for (unsigned int j=0; j<ObjectiveVector::Traits::nObjectives(); j++){
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if (ObjectiveVector::Traits::minimizing(j)){
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front[i][j]=ref_point[j] - ((_set[i][j] - bounds[j].minimum()) /bounds[j].range());
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}
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else{
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front[i][j]=((_set[i][j] - bounds[j].minimum()) /bounds[j].range()) - ref_point[j];
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}
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}
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}
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return calc_hypervolume(front, front.size(),ObjectiveVector::Traits::nObjectives());
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}
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/**
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* getter on bounds
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* @return bounds
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*/
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std::vector < eoRealInterval > getBounds(){
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return bounds;
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}
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/**
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* method caclulate bounds for the normalization
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* @param _set the vector of objective vectors
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*/
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void setup(const std::vector < ObjectiveVector > & _set){
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if(_set.size() < 1)
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throw("Error in moeoHyperVolumeUnaryMetric::setup -> argument1: vector<ObjectiveVector> size must be greater than 0");
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else{
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typename ObjectiveVector::Type min, max;
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unsigned int nbObj=ObjectiveVector::Traits::nObjectives();
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bounds.resize(nbObj);
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for (unsigned int i=0; i<nbObj; i++){
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min = _set[0][i];
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max = _set[0][i];
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for (unsigned int j=1; j<_set.size(); j++){
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min = std::min(min, _set[j][i]);
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max = std::max(max, _set[j][i]);
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}
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bounds[i] = eoRealInterval(min, max);
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}
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}
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}
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/**
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* method calculate if a point dominates another one regarding the x first objective
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* @param _point1 a vector of distances
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* @param _point2 a vector of distances
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* @param _no_objectives a number of objectives
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* @return true if '_point1' dominates '_point2' with respect to the first 'no_objectives' objectives
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*/
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bool dominates(std::vector<double>& _point1, std::vector<double>& _point2, unsigned int _no_objectives){
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unsigned int i;
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bool better_in_any_objective = false;
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bool worse_in_any_objective = false;
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for(i=0; i < _no_objectives && !worse_in_any_objective; i++){
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if(_point1[i] > _point2[i])
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better_in_any_objective = true;
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else if(_point1[i] < _point2[i])
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worse_in_any_objective = true;
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}
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//_point1 dominates _point2 if it is better than _point2 on a objective and if it is never worse in any other objectives
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return(!worse_in_any_objective && better_in_any_objective);
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}
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/**
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* swap two elements of a vector
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* @param _front the vector
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* @param _i index of the first element to swap
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* @param _j index of the second element to swap
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*/
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void swap(std::vector< std::vector<double> >& _front, unsigned int _i, unsigned int _j){
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std::vector<double> tmp;
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tmp=_front[_i];
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_front[_i]=_front[_j];
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_front[_j]=tmp;
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//another way (don't work on visual studio)
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// _front.push_back(_front[_i]);
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// _front[_i]= _front[_j];
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// _front[_j]=_front.back();
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// _front.pop_back();
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}
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/**
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* collect all nondominated points regarding the first '_no_objectives' objectives (dominated points are stored at the end of _front)
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* @param _front the front
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* @param _no_points the number of points of the front to consider (index 0 to _no_points are considered)
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* @param _no_objectives the number of objective to consider
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* @return the index of the last nondominated point
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*/
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unsigned int filter_nondominated_set( std::vector < std::vector< double > >& _front, unsigned int _no_points, unsigned int _no_objectives){
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unsigned int i,j,n;
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n=_no_points;
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i=0;
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while(i < n){
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j=i+1;
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while(j < n){
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//if a point 'A' (index i) dominates another one 'B' (index j), swap 'B' with the point of index n-1
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if( dominates(_front[i], _front[j], _no_objectives)){
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n--;
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swap(_front, j, n);
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}
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//if a point 'B'(index j) dominates another one 'A' (index i), swap 'A' with the point of index n-1
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else if( dominates(_front[j], _front[i], _no_objectives)){
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n--;
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swap(_front, i, n);
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i--;
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break;
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}
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else
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j++;
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}
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i++;
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}
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return n;
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}
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/**
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* find a minimum value
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* @param _front the front
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* @param _no_points the number of points of the front to consider (index 0 to _no_points are considered)
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* @param _objective the objective to consider
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* @return the minimum value regarding dimension '_objective' consider points O to _no_points in '_front'
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*/
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double surface_unchanged_to(std::vector < std::vector< double > >& _front, unsigned int _no_points, unsigned int _objective){
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unsigned int i;
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double min, value;
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if(_no_points < 1)
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throw("Error in moeoHyperVolumeUnaryMetric::surface_unchanged_to -> argument2: _no_points must be greater than 0");
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min = _front[0][_objective];
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for(i=1; i < _no_points; i++){
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value = _front[i][_objective];
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if(value < min)
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min = value;
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}
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return min;
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}
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/**
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* remove all points having a value <= 'threshold' regarding the dimension 'objective', only points of index 0 to _no_points are considered.
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* points removed are swap at the end of the front.
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* @param _front the front
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* @param _no_points the number of points of the front to consider (index 0 to _no_points are considered)
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* @param _objective the objective to consider
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* @param _threshold the threshold
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* @return index of the last points of '_front' greater than the threshold
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*/
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unsigned int reduce_nondominated_set(std::vector < std::vector< double > >& _front, unsigned int _no_points, unsigned int _objective, double _threshold){
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unsigned int i,n ;
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n=_no_points;
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for(i=0; i < n ; i++)
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if(_front[i][_objective] <= _threshold){
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n--;
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swap(_front, i, n);
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i--; //ATTENTION I had this to reconsider the point copied to index i (it can be useless verify algorythimic in calc_hypervolume)
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}
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return n;
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}
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/**
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* calculate hypervolume of the front (data are redrafted before)
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* @param _front the front
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* @param _no_points the number of points of the front to consider (index 0 to _no_points are considered)
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* @param _no_objectives the number of objective to consider
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* @return the hypervolume of the front
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*/
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double calc_hypervolume(std::vector < std::vector< double > >& _front, unsigned int _no_points, unsigned int _no_objectives){
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unsigned int n;
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double volume, distance;
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volume=0;
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distance=0;
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n=_no_points;
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while(n > 0){
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unsigned int no_nondominated_points;
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double temp_vol, temp_dist;
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//get back the index of non dominated points of the front regarding the first "_nb_objectives - 1" objectives
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//So one dimension is not determinante for the dominance
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no_nondominated_points = filter_nondominated_set(_front, n, _no_objectives - 1);
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temp_vol=0;
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//if there are less than 3 objectifs take the fisrt objectif of the first point of front to begin computation of hypervolume
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if(_no_objectives < 3){
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if(_no_objectives < 1)
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throw("Error in moeoHyperVolumeUnaryMetric::calc_hypervolume -> argument3: _no_objectives must be greater than 0");
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temp_vol=_front[0][0];
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}
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//else if there at least 3 objectives, a recursive computation of hypervolume starts with _no_objectives -1 on the filter_nondominated_set calculating previously.
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else
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temp_vol= calc_hypervolume(_front, no_nondominated_points, _no_objectives - 1);
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//search the next minimum distance on the dimension _no_objectives -1
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temp_dist = surface_unchanged_to(_front, n, _no_objectives - 1);
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//calculate the area
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volume+= temp_vol * (temp_dist - distance);
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//change distance to have the good lenght on next step
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distance= temp_dist;
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//remove all points <= distance on dimension _no_objectives
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n=reduce_nondominated_set(_front, n , _no_objectives - 1, distance);
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}
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return volume;
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}
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private:
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/*boolean indicates if data must be normalized or not*/
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bool normalize;
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double rho;
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ObjectiveVector ref_point;
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/*vectors contains bounds for normalization*/
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std::vector < eoRealInterval > bounds;
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};
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#endif /*MOEOHYPERVOLUMEMETRIC_H_*/
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