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An Open Source Java Framework for Multiobjective Optimization
/* 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 .
*/
import org.moeaframework.Executor;
import org.moeaframework.core.NondominatedPopulation;
import org.moeaframework.core.Solution;
import org.moeaframework.core.variable.EncodingUtils;
import org.moeaframework.core.variable.RealVariable;
import org.moeaframework.problem.AbstractProblem;
/**
* Demonstrates how a new problem is defined and used within the MOEA
* Framework.
*/
public class Example4 {
/**
* Implementation of the DTLZ2 function.
*/
public static class MyDTLZ2 extends AbstractProblem {
/**
* Constructs a new instance of the DTLZ2 function, defining it
* to include 11 decision variables and 2 objectives.
*/
public MyDTLZ2() {
super(11, 2);
}
/**
* Constructs a new solution and defines the bounds of the decision
* variables.
*/
@Override
public Solution newSolution() {
Solution solution = new Solution(getNumberOfVariables(),
getNumberOfObjectives());
for (int i = 0; i < getNumberOfVariables(); i++) {
solution.setVariable(i, new RealVariable(0.0, 1.0));
}
return solution;
}
/**
* Extracts the decision variables from the solution, evaluates the
* Rosenbrock function, and saves the resulting objective value back to
* the solution.
*/
@Override
public void evaluate(Solution solution) {
double[] x = EncodingUtils.getReal(solution);
double[] f = new double[numberOfObjectives];
int k = numberOfVariables - numberOfObjectives + 1;
double g = 0.0;
for (int i = numberOfVariables - k; i < numberOfVariables; i++) {
g += Math.pow(x[i] - 0.5, 2.0);
}
for (int i = 0; i < numberOfObjectives; i++) {
f[i] = 1.0 + g;
for (int j = 0; j < numberOfObjectives - i - 1; j++) {
f[i] *= Math.cos(0.5 * Math.PI * x[j]);
}
if (i != 0) {
f[i] *= Math.sin(0.5 * Math.PI * x[numberOfObjectives - i - 1]);
}
}
solution.setObjectives(f);
}
}
public static void main(String[] args) {
//configure and run the DTLZ2 function
NondominatedPopulation result = new Executor()
.withProblemClass(MyDTLZ2.class)
.withAlgorithm("NSGAII")
.withMaxEvaluations(10000)
.run();
//display the results
System.out.format("Objective1 Objective2%n");
for (Solution solution : result) {
System.out.format("%.4f %.4f%n",
solution.getObjective(0),
solution.getObjective(1));
}
}
}