/* 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.RealVariable;
import org.moeaframework.problem.AbstractProblem;
/**
* The Osyczka (2) problem.
* <p>
* Properties:
* <ul>
* <li>Disconnected Pareto set
* <li>Disconnected Pareto front
* <li>Constrained
* </ul>
* <p>
* References:
* <ol>
* <li>Osyczka, A. and Kundu, S. (1995). "A New Method to Solve Generalized
* Multicriteria Optimization Problems using the Simple Genetic
* Algorithm." Structural Optimization, vol. 10, pp. 94-99.
* <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 Osyczka2 extends AbstractProblem {
/**
* Constructs the Osyczka (2) problem.
*/
public Osyczka2() {
super(6, 2, 6);
}
@Override
public void evaluate(Solution solution) {
double x1 = ((RealVariable)solution.getVariable(0)).getValue();
double x2 = ((RealVariable)solution.getVariable(1)).getValue();
double x3 = ((RealVariable)solution.getVariable(2)).getValue();
double x4 = ((RealVariable)solution.getVariable(3)).getValue();
double x5 = ((RealVariable)solution.getVariable(4)).getValue();
double x6 = ((RealVariable)solution.getVariable(5)).getValue();
double f1 = -(25.0*Math.pow(x1 - 2.0, 2.0) + Math.pow(x2 - 2.0, 2.0) +
Math.pow(x3 - 1.0, 2.0) + Math.pow(x4 - 4.0, 2.0) +
Math.pow(x5 - 1.0, 2.0));
double f2 = Math.pow(x1, 2.0) + Math.pow(x2, 2.0) + Math.pow(x3, 2.0) +
Math.pow(x4, 2.0) + Math.pow(x5, 2.0) + Math.pow(x6, 2.0);
double c1 = x1 + x2 - 2.0;
double c2 = 6.0 - x1 - x2;
double c3 = 2.0 - x2 + x1;
double c4 = 2.0 - x1 + 3.0*x2;
double c5 = 4.0 - Math.pow(x3 - 3.0, 2.0) - x4;
double c6 = Math.pow(x5 - 3.0, 2.0) + x6 - 4.0;
solution.setObjective(0, f1);
solution.setObjective(1, f2);
solution.setConstraint(0, c1 >= 0.0 ? 0.0 : c1);
solution.setConstraint(1, c2 >= 0.0 ? 0.0 : c2);
solution.setConstraint(2, c3 >= 0.0 ? 0.0 : c3);
solution.setConstraint(3, c4 >= 0.0 ? 0.0 : c4);
solution.setConstraint(4, c5 >= 0.0 ? 0.0 : c5);
solution.setConstraint(5, c6 >= 0.0 ? 0.0 : c6);
}
@Override
public Solution newSolution() {
Solution solution = new Solution(6, 2, 6);
solution.setVariable(0, new RealVariable(0.0, 10.0));
solution.setVariable(1, new RealVariable(0.0, 10.0));
solution.setVariable(2, new RealVariable(1.0, 5.0));
solution.setVariable(3, new RealVariable(0.0, 6.0));
solution.setVariable(4, new RealVariable(1.0, 5.0));
solution.setVariable(5, new RealVariable(0.0, 10.0));
return solution;
}
}