add sharing
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branches/paradiseo-moeo-1.0/src/moeoSharingDiversityAssignment.h
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branches/paradiseo-moeo-1.0/src/moeoSharingDiversityAssignment.h
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// -*- mode: c++; c-indent-level: 4; c++-member-init-indent: 8; comment-column: 35; -*-
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//-----------------------------------------------------------------------------
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// moeoSharingDiversityAssignment.h
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// (c) OPAC Team (LIFL), Dolphin Project (INRIA), 2007
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/*
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This library...
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Contact: paradiseo-help@lists.gforge.inria.fr, http://paradiseo.gforge.inria.fr
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*/
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//-----------------------------------------------------------------------------
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#ifndef MOEOSHARINGDIVERSITYASSIGNMENT_H_
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#define MOEOSHARINGDIVERSITYASSIGNMENT_H_
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#include <eoPop.h>
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#include <moeoComparator.h>
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#include <moeoDiversityAssignment.h>
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#include <distance/moeoDistance.h>
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#include <distance/moeoDistanceMatrix.h>
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/**
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* Sharing assignment scheme originally porposed by:
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* D. E. Goldberg, "Genetic Algorithms in Search, Optimization and Machine Learning", Addision-Wesley, MA, USA (1989).
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*/
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template < class MOEOT >
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class moeoSharingDiversityAssignment : public moeoDiversityAssignment < MOEOT >
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{
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public:
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/** the objective vector type of the solutions */
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typedef typename MOEOT::ObjectiveVector ObjectiveVector;
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/**
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* Ctor
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* @param _distance the distance used to compute the neighborhood of solutions (can be related to the decision space or the objective space)
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* @param _nicheSize neighborhood size in terms of radius distance (closely related to the way the distances are computed)
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* @param _alpha parameter used to regulate the shape of the sharing function
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*/
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moeoSharingDiversityAssignment(moeoDistance<MOEOT,double> & _distance, double _nicheSize = 0.5, double _alpha = 1.0) : distance(_distance), nicheSize(_nicheSize), alpha(_alpha)
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{}
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/**
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* Ctor with an euclidean distance (with normalized objective values) in the objective space is used as default
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* @param _nicheSize neighborhood size in terms of radius distance (closely related to the way the distances are computed)
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* @param _alpha parameter used to regulate the shape of the sharing function
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*/
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moeoSharingDiversityAssignment(double _nicheSize = 0.5, double _alpha = 1.0) : distance(defaultDistance), nicheSize(_nicheSize), alpha(_alpha)
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{}
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/**
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* Sets diversity values for every solution contained in the population _pop
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* @param _pop the population
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*/
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void operator()(eoPop < MOEOT > & _pop)
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{
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// 1 - set simuilarities
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setSimilarities(_pop);
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// 2 - a higher diversity is better, so the values need to be inverted
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moeoDiversityThenFitnessComparator < MOEOT > divComparator;
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double max = std::max_element(_pop.begin(), _pop.end(), divComparator)->diversity();
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for (unsigned i=0 ; i<_pop.size() ; i++)
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{
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_pop[i].diversity(max - _pop[i].diversity());
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}
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}
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/**
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* @warning NOT IMPLEMENTED, DO NOTHING !
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* Updates the diversity values of the whole population _pop by taking the deletion of the objective vector _objVec into account.
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* @param _pop the population
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* @param _objVec the objective vector
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* @warning NOT IMPLEMENTED, DO NOTHING !
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*/
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void updateByDeleting(eoPop < MOEOT > & _pop, ObjectiveVector & _objVec)
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{
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cout << "WARNING : updateByDeleting not implemented in moeoSharingDiversityAssignment" << endl;
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}
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protected:
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/** the distance used to compute the neighborhood of solutions */
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moeoDistance < MOEOT , double > & distance;
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/** euclidean distancein the objective space (can be used as default) */
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moeoEuclideanDistance < MOEOT > defaultDistance;
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/** neighborhood size in terms of radius distance */
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double nicheSize;
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/** parameter used to regulate the shape of the sharing function */
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double alpha;
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/**
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* Sets similarities for every solution contained in the population _pop
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* @param _pop the population
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*/
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virtual void setSimilarities(eoPop < MOEOT > & _pop)
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{
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// compute distances between every individuals
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moeoDistanceMatrix < MOEOT , double > dMatrix (_pop.size(), distance);
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dMatrix(_pop);
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// compute similarities
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double sum;
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for (unsigned i=0; i<_pop.size(); i++)
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{
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sum = 0.0;
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for (unsigned j=0; j<_pop.size(); j++)
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{
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sum += sh(dMatrix[i][j]);
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}
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_pop[i].diversity(sum);
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}
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}
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/**
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* Sharing function
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* @param _dist the distance value
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*/
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double sh(double _dist)
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{
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double result;
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if (_dist < nicheSize)
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{
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result = 1.0 - pow(_dist / nicheSize, alpha);
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}
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else
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{
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result = 0.0;
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}
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return result;
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}
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};
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/**
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* Sharing assignment scheme on the way it is used in NSGA.
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*/
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template < class MOEOT >
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class moeoFrontByFrontSharingDiversityAssignment : public moeoSharingDiversityAssignment < MOEOT >
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{
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public:
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/** the objective vector type of the solutions */
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typedef typename MOEOT::ObjectiveVector ObjectiveVector;
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/**
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* Ctor
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* @param _distance the distance used to compute the neighborhood of solutions (can be related to the decision space or the objective space)
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* @param _nicheSize neighborhood size in terms of radius distance (closely related to the way the distances are computed)
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* @param _alpha parameter used to regulate the shape of the sharing function
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*/
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moeoFrontByFrontSharingDiversityAssignment(moeoDistance<MOEOT,double> & _distance, double _nicheSize = 0.5, double _alpha = 2.0) : moeoSharingDiversityAssignment < MOEOT >(_distance, _nicheSize, _alpha)
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{}
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/**
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* Ctor with an euclidean distance (with normalized objective values) in the objective space is used as default
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* @param _nicheSize neighborhood size in terms of radius distance (closely related to the way the distances are computed)
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* @param _alpha parameter used to regulate the shape of the sharing function
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*/
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moeoFrontByFrontSharingDiversityAssignment(double _nicheSize = 0.5, double _alpha = 2.0) : moeoSharingDiversityAssignment < MOEOT >(_nicheSize, _alpha)
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{}
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/**
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* @warning NOT IMPLEMENTED, DO NOTHING !
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* Updates the diversity values of the whole population _pop by taking the deletion of the objective vector _objVec into account.
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* @param _pop the population
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* @param _objVec the objective vector
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* @warning NOT IMPLEMENTED, DO NOTHING !
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*/
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void updateByDeleting(eoPop < MOEOT > & _pop, ObjectiveVector & _objVec)
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{
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cout << "WARNING : updateByDeleting not implemented in moeoSharingDiversityAssignment" << endl;
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}
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private:
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using moeoSharingDiversityAssignment < MOEOT >::distance;
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using moeoSharingDiversityAssignment < MOEOT >::nicheSize;
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using moeoSharingDiversityAssignment < MOEOT >::sh;
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using moeoSharingDiversityAssignment < MOEOT >::operator();
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/**
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* Sets similarities FRONT BY FRONT for every solution contained in the population _pop
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* @param _pop the population
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*/
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void setSimilarities(eoPop < MOEOT > & _pop)
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{
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// compute distances between every individuals
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moeoDistanceMatrix < MOEOT , double > dMatrix (_pop.size(), distance);
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dMatrix(_pop);
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// sets the distance to bigger than the niche size for every couple of solutions that do not belong to the same front
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for (unsigned i=0; i<_pop.size(); i++)
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{
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for (unsigned j=0; j<i; j++)
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{
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if (_pop[i].fitness() != _pop[j].fitness())
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{
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dMatrix[i][j] = nicheSize;
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dMatrix[j][i] = nicheSize;
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}
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}
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}
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// compute similarities
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double sum;
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for (unsigned i=0; i<_pop.size(); i++)
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{
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sum = 0.0;
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for (unsigned j=0; j<_pop.size(); j++)
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{
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sum += sh(dMatrix[i][j]);
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}
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_pop[i].diversity(sum);
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}
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}
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};
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#endif /*MOEOSHARINGDIVERSITYASSIGNMENT_H_*/
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