new version

git-svn-id: svn://scm.gforge.inria.fr/svnroot/paradiseo@267 331e1502-861f-0410-8da2-ba01fb791d7f

trunk/paradiseo-moeo/src/moeoFastNonDominatedSortingFitnessAssignment.h

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+// -*- mode: c++; c-indent-level: 4; c++-member-init-indent: 8; comment-column: 35; -*-
+
+//-----------------------------------------------------------------------------
+// moeoFastNonDominatedSortingFitnessAssignment.h
+// (c) OPAC Team (LIFL), Dolphin Project (INRIA), 2007
+/*
+    This library...
+
+    Contact: paradiseo-help@lists.gforge.inria.fr, http://paradiseo.gforge.inria.fr
+ */
+//-----------------------------------------------------------------------------
+
+#ifndef MOEOFASTNONDOMINATEDSORTINGFITNESSASSIGNMENT_H_
+#define MOEOFASTNONDOMINATEDSORTINGFITNESSASSIGNMENT_H_
+
+#include <eoPop.h>
+#include <moeoComparator.h>
+#include <moeoFitnessAssignment.h>
+#include <moeoObjectiveVectorComparator.h>
+
+/**
+ * Fitness assignment sheme based on Pareto-dominance count proposed in:
+ * N. Srinivas, K. Deb, "Multiobjective Optimization Using Nondominated Sorting in Genetic Algorithms", Evolutionary Computation vol. 2, no. 3, pp. 221-248 (1994)
+ * and in:
+ * K. Deb, A. Pratap, S. Agarwal, T. Meyarivan, "A Fast and Elitist Multi-Objective Genetic Algorithm: NSGA-II", IEEE Transactions on Evolutionary Computation, vol. 6, no. 2 (2002).
+ * This strategy is, for instance, used in NSGA and NSGA-II.
+ */
+template < class MOEOT >
+class moeoFastNonDominatedSortingFitnessAssignment : public moeoParetoBasedFitnessAssignment < MOEOT >
+{
+public:
+
+    /** the objective vector type of the solutions */
+    typedef typename MOEOT::ObjectiveVector ObjectiveVector;
+
+
+    /**
+     * Default ctor
+     */
+    moeoFastNonDominatedSortingFitnessAssignment() : comparator(paretoComparator)
+    {}
+
+
+    /**
+     * Ctor where you can choose your own way to compare objective vectors
+     * @param _comparator the functor used to compare objective vectors
+     */
+    moeoFastNonDominatedSortingFitnessAssignment(moeoObjectiveVectorComparator < ObjectiveVector > & _comparator) : comparator(_comparator)
+    {}
+
+
+    /**
+     * Sets the fitness values for every solution contained in the population _pop
+     * @param _pop the population
+     */
+    void operator()(eoPop < MOEOT > & _pop)
+    {
+        // number of objectives for the problem under consideration
+        unsigned nObjectives = MOEOT::ObjectiveVector::nObjectives();
+        if (nObjectives == 1)
+        {
+            // one objective
+            oneObjective(_pop);
+        }
+        else if (nObjectives == 2)
+        {
+            // two objectives (the two objectives function is still to implement)
+            mObjectives(_pop);
+        }
+        else if (nObjectives > 2)
+        {
+            // more than two objectives
+            mObjectives(_pop);
+        }
+        else
+        {
+            // problem with the number of objectives
+            throw std::runtime_error("Problem with the number of objectives in moeoNonDominatedSortingFitnessAssignment");
+        }
+        // a higher fitness is better, so the values need to be inverted
+        double max = _pop[0].fitness();
+        for (unsigned i=1 ; i<_pop.size() ; i++)
+        {
+            max = std::max(max, _pop[i].fitness());
+        }
+        for (unsigned i=0 ; i<_pop.size() ; i++)
+        {
+            _pop[i].fitness(max - _pop[i].fitness());
+        }
+    }
+
+
+    /**
+     * @warning NOT IMPLEMENTED, DO NOTHING !
+     * Updates the fitness values of the whole population _pop by taking the deletion of the objective vector _objVec into account.
+     * @param _pop the population
+     * @param _objVec the objective vector
+     * @warning NOT IMPLEMENTED, DO NOTHING !
+     */
+    void updateByDeleting(eoPop < MOEOT > & _pop, ObjectiveVector & _objVec)
+    {
+        cout << "WARNING : updateByDeleting not implemented in moeoNonDominatedSortingFitnessAssignment" << endl;
+    }
+
+
+private:
+
+    /** Functor to compare two objective vectors */
+    moeoObjectiveVectorComparator < ObjectiveVector > & comparator;
+    /** Functor to compare two objective vectors according to Pareto dominance relation */
+    moeoParetoObjectiveVectorComparator < ObjectiveVector > paretoComparator;
+
+
+
+
+    /**
+     * Sets the fitness values for mono-objective problems
+     * @param _pop the population
+     */
+    void oneObjective (eoPop < MOEOT > & _pop)
+    {
+        // Functor to compare two solutions on the first objective, then on the second, and so on
+        moeoObjectiveComparator < MOEOT > objComparator;
+        std::sort(_pop.begin(), _pop.end(), objComparator);
+        for (unsigned i=0; i<_pop.size(); i++)
+        {
+            _pop[i].fitness(i+1);
+        }
+    }
+
+
+    /**
+     * Sets the fitness values for bi-objective problems with a complexity of O(n log n), where n stands for the population size
+     * @param _pop the population
+     */
+    void twoObjectives (eoPop < MOEOT > & _pop)
+    {
+        //... TO DO !
+    }
+
+
+    /**
+     * Sets the fitness values for problems with more than two objectives with a complexity of O(n² log n), where n stands for the population size
+     * @param _pop the population
+     */
+    void mObjectives (eoPop < MOEOT > & _pop)
+    {
+        // S[i] = indexes of the individuals dominated by _pop[i]
+        std::vector < std::vector<unsigned> > S(_pop.size());
+        // n[i] = number of individuals that dominate the individual _pop[i]
+        std::vector < unsigned > n(_pop.size(), 0);
+        // fronts: F[i] = indexes of the individuals contained in the ith front
+        std::vector < std::vector<unsigned> > F(_pop.size()+1);
+        // used to store the number of the first front
+        F[1].reserve(_pop.size());
+        for (unsigned p=0; p<_pop.size(); p++)
+        {
+            for (unsigned q=0; q<_pop.size(); q++)
+            {
+                // if p dominates q
+                if ( comparator(_pop[p].objectiveVector(), _pop[q].objectiveVector()) )
+                {
+                    // add q to the set of solutions dominated by p
+                    S[p].push_back(q);
+                }
+                // if q dominates p
+                else if  ( comparator(_pop[q].objectiveVector(), _pop[p].objectiveVector()) )
+                {
+                    // increment the domination counter of p
+                    n[p]++;
+                }
+            }
+            // if no individual dominates p
+            if (n[p] == 0)
+            {
+                // p belongs to the first front
+                _pop[p].fitness(1);
+                F[1].push_back(p);
+            }
+        }
+        // front counter
+        unsigned counter=1;
+        unsigned p,q;
+        while (! F[counter].empty())
+        {
+            // used to store the number of the next front
+            F[counter+1].reserve(_pop.size());
+            for (unsigned i=0; i<F[counter].size(); i++)
+            {
+                p = F[counter][i];
+                for (unsigned j=0; j<S[p].size(); j++)
+                {
+                    q = S[p][j];
+                    n[q]--;
+                    // if no individual dominates q anymore
+                    if (n[q] == 0)
+                    {
+                        // q belongs to the next front
+                        _pop[q].fitness(counter+1);
+                        F[counter+1].push_back(q);
+                    }
+                }
+            }
+            counter++;
+        }
+    }
+
+};
+
+#endif /*MOEOFASTNONDOMINATEDSORTINGFITNESSASSIGNMENT_H_*/