TestBinaryTournamentSelectionCrowdedComparison.java example

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/**
 * Copyright (C) 2010-2017 Gordon Fraser, Andrea Arcuri and EvoSuite
 * contributors
 *
 * This file is part of EvoSuite.
 *
 * EvoSuite 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 3.0 of the License, or
 * (at your option) any later version.
 *
 * EvoSuite 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 Public License for more details.
 *
 * You should have received a copy of the GNU Lesser General Public
 * License along with EvoSuite. If not, see <http://www.gnu.org/licenses/>.
 */
package org.evosuite.ga.operators.selection;

import java.util.ArrayList;
import java.util.List;

import org.evosuite.Properties;
import org.evosuite.ga.NSGAChromosome;
import org.evosuite.ga.metaheuristics.NSGAII;
import org.junit.Assert;
import org.junit.BeforeClass;
import org.junit.Test;

/**
 * Test Binary Tournament Selection using Crowded Comparison
 * 
 * @author José Campos
 */
@SuppressWarnings({ "rawtypes", "unchecked" })
public class TestBinaryTournamentSelectionCrowdedComparison
{
	@BeforeClass
	public static void setUp() {
		Properties.RANDOM_SEED = 1l;
	}

	@Test
	public void testNonDominationRankMinimize()
	{
		NSGAII<NSGAChromosome> ga = new NSGAII<NSGAChromosome>(null);
		BinaryTournamentSelectionCrowdedComparison ts = new BinaryTournamentSelectionCrowdedComparison(false);
		ts.setMaximize(false);
		ga.setSelectionFunction(ts);

		NSGAChromosome c1 = new NSGAChromosome();
		NSGAChromosome c2 = new NSGAChromosome();

		// Set Rank
		c1.setRank(1);
		c2.setRank(0);

		List<NSGAChromosome> population = new ArrayList<NSGAChromosome>();
		population.add(c1);
		population.add(c2);

		Assert.assertTrue(ts.getIndex(population) == 1);
	}

	@Test
	public void testNonDominationRankMaximize()
	{
		NSGAII<NSGAChromosome> ga = new NSGAII<NSGAChromosome>(null);
		BinaryTournamentSelectionCrowdedComparison ts = new BinaryTournamentSelectionCrowdedComparison(true);
		ts.setMaximize(true);
		ga.setSelectionFunction(ts);

		NSGAChromosome c1 = new NSGAChromosome();
		NSGAChromosome c2 = new NSGAChromosome();

		// Set Rank
		c1.setRank(1);
		c2.setRank(0);

		List<NSGAChromosome> population = new ArrayList<NSGAChromosome>();
		population.add(c1);
		population.add(c2);

		Assert.assertTrue(ts.getIndex(population) == 0);
	}

	@Test
	public void testCrowdingDistanceMinimize()
	{
		NSGAII<NSGAChromosome> ga = new NSGAII<NSGAChromosome>(null);
		BinaryTournamentSelectionCrowdedComparison ts = new BinaryTournamentSelectionCrowdedComparison(false);
		ts.setMaximize(false);
		ga.setSelectionFunction(ts);

		NSGAChromosome c1 = new NSGAChromosome();
		NSGAChromosome c2 = new NSGAChromosome();

		// Set Rank
		c1.setRank(0);
		c2.setRank(0);

		// Set Distance
		c1.setDistance(0.1);
		c2.setDistance(0.5);

		List<NSGAChromosome> population = new ArrayList<NSGAChromosome>();
		population.add(c1);
		population.add(c2);

		Assert.assertTrue(ts.getIndex(population) == 1);
	}

	@Test
	public void testCrowdingDistanceMaximize()
	{
		NSGAII<NSGAChromosome> ga = new NSGAII<NSGAChromosome>(null);
		BinaryTournamentSelectionCrowdedComparison ts = new BinaryTournamentSelectionCrowdedComparison(true);
		ts.setMaximize(true);
		ga.setSelectionFunction(ts);

		NSGAChromosome c1 = new NSGAChromosome();
		NSGAChromosome c2 = new NSGAChromosome();

		// Set Rank
		c1.setRank(0);
		c2.setRank(0);

		// Set Distance
		c1.setDistance(0.1);
		c2.setDistance(0.5);

		List<NSGAChromosome> population = new ArrayList<NSGAChromosome>();
		population.add(c1);
		population.add(c2);

		Assert.assertTrue(ts.getIndex(population) == 1);
	}
}