/* 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;
}
}