/* 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.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;
}
}