/* 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.problem.misc; import org.moeaframework.core.PRNG; import org.moeaframework.core.Solution; import org.moeaframework.core.variable.EncodingUtils; import org.moeaframework.problem.AbstractProblem; import org.moeaframework.problem.AnalyticalProblem; /** * The Laumanns problem. The optimum points like on the line {@code (x, 0)} * with {@code -2 <= x <= 0}. * <p> * Properties: * <ul> * <li>Connected Pareto set * <li>Disconnected Pareto front * <li>Convex Pareto front * </ul> * <p> * References: * <ol> * <li>Laumanns, M., Rudolph, G., and Schwefel, H. (1998). "A Spatial * Predator-Prey Approach to Multi-Objective Optimization: A Preliminary * Study." Proceedings of the Parallel Problem Solving from Nature, * Springer, pp. 241-249. * <li>Van Veldhuizen, D. A (1999). "Multiobjective Evolutionary Algorithms: * Classifications, Analyses, and New Innovations." Air Force Institute * of Technology, Ph.D. Thesis, Appendix B. * </ol> */ public class Laumanns extends AbstractProblem implements AnalyticalProblem { /** * Constructs the Laumanns problem. */ public Laumanns() { super(2, 2); } @Override public void evaluate(Solution solution) { double x = EncodingUtils.getReal(solution.getVariable(0)); double y = EncodingUtils.getReal(solution.getVariable(1)); double f1 = Math.pow(x, 2.0) + Math.pow(y, 2.0); double f2 = Math.pow(x+2.0, 2.0) + Math.pow(y, 2.0); solution.setObjective(0, f1); solution.setObjective(1, f2); } @Override public Solution newSolution() { Solution solution = new Solution(2, 2); solution.setVariable(0, EncodingUtils.newReal(-50.0, 50.0)); solution.setVariable(1, EncodingUtils.newReal(-50.0, 50.0)); return solution; } @Override public Solution generate() { Solution solution = newSolution(); EncodingUtils.setReal(solution.getVariable(0), PRNG.nextDouble(-2.0, 0.0)); EncodingUtils.setReal(solution.getVariable(1), 0.0); evaluate(solution); return solution; } }