/* Copyright 2009-2015 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.Solution; import org.moeaframework.core.variable.EncodingUtils; import org.moeaframework.core.variable.RealVariable; import org.moeaframework.problem.AbstractProblem; /** * The Quagliarella problem. * <p> * Properties: * <ul> * <li>Disconnected Pareto set * <li>Convex Pareto front * </ul> * <p> * References: * <ol> * <li>Van Veldhuizen, D. A (1999). "Multiobjective Evolutionary Algorithms: * Classifications, Analyses, and New Innovations." Air Force Institute * of Technology, Ph.D. Thesis, Appendix B. * <li>Quagliarella, D., and Vicini, A. (1998). "Sub-population Policies for * a Parallel Multiobjective Genetic Algorithm with Applications to Wing * Design." In proceedings of the 1998 IEEE International Conference on * Systems, Man, and Cybernetics, pp. 3142-3147. * </ol> */ public class Quagliarella extends AbstractProblem { /** * Constructs the Quagliarella problem. */ public Quagliarella() { this(16); } public Quagliarella(int numberOfVariables) { super(numberOfVariables, 2); } @Override public void evaluate(Solution solution) { double[] x = EncodingUtils.getReal(solution); double A1 = 0.0; double A2 = 0.0; for (int i=0; i<numberOfVariables; i++) { A1 += Math.pow(x[i], 2.0) - 10.0*Math.cos(2.0*Math.PI*x[i]) + 10; A2 += Math.pow(x[i] - 1.5, 2.0) - 10.0*Math.cos(2.0*Math.PI*(x[i] - 1.5)) + 10; } solution.setObjective(0, Math.sqrt(A1 / numberOfVariables)); solution.setObjective(1, Math.sqrt(A2 / numberOfVariables)); } @Override public Solution newSolution() { Solution solution = new Solution(numberOfVariables, 2); for (int i=0; i<numberOfVariables; i++) { solution.setVariable(i, new RealVariable(-5.12, 5.12)); } return solution; } }