/* Copyright 2009-2016 David Hadka * * This file is part of the MOEA Framework. * * The MOEA Framework is free software: you can redistribute it and/or modify * it under the terms of the GNU Lesser General Public License as published by * the Free Software Foundation, either version 3 of the License, or (at your * option) any later version. * * The MOEA Framework is distributed in the hope that it will be useful, but * WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY * or FITNESS FOR A PARTICULAR PURPOSE. See the GNU Lesser General Public * License for more details. * * You should have received a copy of the GNU Lesser General Public License * along with the MOEA Framework. If not, see <http://www.gnu.org/licenses/>. */ package org.moeaframework.algorithm; import org.moeaframework.core.EpsilonBoxDominanceArchive; import org.moeaframework.core.EpsilonBoxEvolutionaryAlgorithm; import org.moeaframework.core.Initialization; import org.moeaframework.core.NondominatedSortingPopulation; import org.moeaframework.core.Population; import org.moeaframework.core.Problem; import org.moeaframework.core.Selection; import org.moeaframework.core.Solution; import org.moeaframework.core.Variation; /** * Implementation of NSGA-II, with the ability to attach an optional * ε-dominance archive. * <p> * References: * <ol> * <li>Deb, K. et al. "A Fast Elitist Multi-Objective Genetic Algorithm: * NSGA-II." IEEE Transactions on Evolutionary Computation, 6:182-197, * 2000. * <li>Kollat, J. B., and Reed, P. M. "Comparison of Multi-Objective * Evolutionary Algorithms for Long-Term Monitoring Design." Advances in * Water Resources, 29(6):792-807, 2006. * </ol> */ public class NSGAII extends AbstractEvolutionaryAlgorithm implements EpsilonBoxEvolutionaryAlgorithm { /** * The selection operator. */ private final Selection selection; /** * The variation operator. */ private final Variation variation; /** * Constructs the NSGA-II algorithm with the specified components. * * @param problem the problem being solved * @param population the population used to store solutions * @param archive the archive used to store the result; can be {@code null} * @param selection the selection operator * @param variation the variation operator * @param initialization the initialization method */ public NSGAII(Problem problem, NondominatedSortingPopulation population, EpsilonBoxDominanceArchive archive, Selection selection, Variation variation, Initialization initialization) { super(problem, population, archive, initialization); this.variation = variation; this.selection = selection; } @Override public void iterate() { NondominatedSortingPopulation population = getPopulation(); EpsilonBoxDominanceArchive archive = getArchive(); Population offspring = new Population(); int populationSize = population.size(); while (offspring.size() < populationSize) { Solution[] parents = selection.select(variation.getArity(), population); Solution[] children = variation.evolve(parents); offspring.addAll(children); } evaluateAll(offspring); if (archive != null) { archive.addAll(offspring); } population.addAll(offspring); population.truncate(populationSize); } @Override public EpsilonBoxDominanceArchive getArchive() { return (EpsilonBoxDominanceArchive)super.getArchive(); } @Override public NondominatedSortingPopulation getPopulation() { return (NondominatedSortingPopulation)super.getPopulation(); } }