// This program 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.
//
// This program 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 this program. If not, see <http://www.gnu.org/licenses/>.
package org.uma.jmetal.experiment;
import org.uma.jmetal.algorithm.Algorithm;
import org.uma.jmetal.algorithm.multiobjective.nsgaii.NSGAIIBuilder;
import org.uma.jmetal.algorithm.multiobjective.smpso.SMPSOBuilder;
import org.uma.jmetal.algorithm.multiobjective.spea2.SPEA2Builder;
import org.uma.jmetal.operator.impl.crossover.SBXCrossover;
import org.uma.jmetal.operator.impl.mutation.PolynomialMutation;
import org.uma.jmetal.problem.DoubleProblem;
import org.uma.jmetal.problem.Problem;
import org.uma.jmetal.problem.multiobjective.zdt.ZDT1;
import org.uma.jmetal.problem.multiobjective.zdt.ZDT2;
import org.uma.jmetal.problem.multiobjective.zdt.ZDT3;
import org.uma.jmetal.problem.multiobjective.zdt.ZDT4;
import org.uma.jmetal.problem.multiobjective.zdt.ZDT6;
import org.uma.jmetal.qualityindicator.impl.Epsilon;
import org.uma.jmetal.qualityindicator.impl.GenerationalDistance;
import org.uma.jmetal.qualityindicator.impl.InvertedGenerationalDistance;
import org.uma.jmetal.qualityindicator.impl.InvertedGenerationalDistancePlus;
import org.uma.jmetal.qualityindicator.impl.Spread;
import org.uma.jmetal.qualityindicator.impl.hypervolume.PISAHypervolume;
import org.uma.jmetal.solution.DoubleSolution;
import org.uma.jmetal.util.JMetalException;
import org.uma.jmetal.util.archive.impl.CrowdingDistanceArchive;
import org.uma.jmetal.util.evaluator.impl.SequentialSolutionListEvaluator;
import org.uma.jmetal.util.experiment.Experiment;
import org.uma.jmetal.util.experiment.ExperimentBuilder;
import org.uma.jmetal.util.experiment.component.ComputeQualityIndicators;
import org.uma.jmetal.util.experiment.component.ExecuteAlgorithms;
import org.uma.jmetal.util.experiment.component.GenerateBoxplotsWithR;
import org.uma.jmetal.util.experiment.component.GenerateFriedmanTestTables;
import org.uma.jmetal.util.experiment.component.GenerateLatexTablesWithStatistics;
import org.uma.jmetal.util.experiment.component.GenerateReferenceParetoSetAndFrontFromDoubleSolutions;
import org.uma.jmetal.util.experiment.component.GenerateWilcoxonTestTablesWithR;
import org.uma.jmetal.util.experiment.util.ExperimentAlgorithm;
import org.uma.jmetal.util.experiment.util.ExperimentProblem;
import java.io.IOException;
import java.util.ArrayList;
import java.util.Arrays;
import java.util.List;
/**
* Example of experimental study based on solving the ZDT problems with algorithms NSGAII,
* SPEA2, and SMPSO
*
* This experiment assumes that the reference Pareto front are not known, so the names of files containing
* them and the directory where they are located must be specified.
*
* Six quality indicators are used for performance assessment.
*
* The steps to carry out the experiment are:
* 1. Configure the experiment
* 2. Execute the algorithms
* 3. Generate the reference Pareto fronts
* 4. Compute que quality indicators
* 5. Generate Latex tables reporting means and medians
* 6. Generate Latex tables with the result of applying the Wilcoxon Rank Sum Test
* 7. Generate R scripts to obtain boxplots
*
* @author Antonio J. Nebro <antonio@lcc.uma.es>
*/
public class ZDTStudy2 {
private static final int INDEPENDENT_RUNS = 25 ;
public static void main(String[] args) throws IOException {
if (args.length != 1) {
throw new JMetalException("Needed arguments: experimentBaseDirectory") ;
}
String experimentBaseDirectory = args[0] ;
List<ExperimentProblem<DoubleSolution>> problemList = new ArrayList<>();
problemList.add(new ExperimentProblem<>(new ZDT1()));
problemList.add(new ExperimentProblem<>(new ZDT2()));
problemList.add(new ExperimentProblem<>(new ZDT3()));
problemList.add(new ExperimentProblem<>(new ZDT4()));
problemList.add(new ExperimentProblem<>(new ZDT6()));
List<ExperimentAlgorithm<DoubleSolution, List<DoubleSolution>>> algorithmList =
configureAlgorithmList(problemList);
ExperimentBuilder<DoubleSolution, List<DoubleSolution>> zdt2Study = new ExperimentBuilder<DoubleSolution, List<DoubleSolution>>("ZDTStudy2");
zdt2Study.setAlgorithmList(algorithmList);
zdt2Study.setProblemList(problemList);
zdt2Study.setExperimentBaseDirectory(experimentBaseDirectory);
zdt2Study.setOutputParetoFrontFileName("FUN");
zdt2Study.setOutputParetoSetFileName("VAR");
zdt2Study.setReferenceFrontDirectory(experimentBaseDirectory + "/referenceFronts");
zdt2Study.setIndicatorList(Arrays.asList(
new Epsilon<DoubleSolution>(), new Spread<DoubleSolution>(), new GenerationalDistance<DoubleSolution>(),
new PISAHypervolume<DoubleSolution>(),
new InvertedGenerationalDistance<DoubleSolution>(), new InvertedGenerationalDistancePlus<DoubleSolution>()));
zdt2Study.setIndependentRuns(INDEPENDENT_RUNS);
zdt2Study.setNumberOfCores(8);
Experiment<DoubleSolution, List<DoubleSolution>> experiment = zdt2Study.build();
new ExecuteAlgorithms<>(experiment).run();
new GenerateReferenceParetoSetAndFrontFromDoubleSolutions(experiment).run();
new ComputeQualityIndicators<>(experiment).run() ;
new GenerateLatexTablesWithStatistics(experiment).run() ;
new GenerateWilcoxonTestTablesWithR<>(experiment).run() ;
new GenerateFriedmanTestTables<>(experiment).run();
new GenerateBoxplotsWithR<>(experiment).setRows(3).setColumns(3).setDisplayNotch().run() ;
}
/**
* The algorithm list is composed of pairs {@link Algorithm} + {@link Problem} which form part of a
* {@link TaggedAlgorithm}, which is a decorator for class {@link Algorithm}.
*
* @param problemList
* @return
*/
/**
* The algorithm list is composed of pairs {@link Algorithm} + {@link Problem} which form part of a
* {@link ExperimentAlgorithm}, which is a decorator for class {@link Algorithm}.
*
* @param problemList
* @return
*/
static List<ExperimentAlgorithm<DoubleSolution, List<DoubleSolution>>> configureAlgorithmList(
List<ExperimentProblem<DoubleSolution>> problemList) {
List<ExperimentAlgorithm<DoubleSolution, List<DoubleSolution>>> algorithms = new ArrayList<>();
for (int i = 0; i < problemList.size(); i++) {
double mutationProbability = 1.0 / problemList.get(i).getProblem().getNumberOfVariables();
double mutationDistributionIndex = 20.0;
Algorithm<List<DoubleSolution>> algorithm = new SMPSOBuilder((DoubleProblem) problemList.get(i).getProblem(),
new CrowdingDistanceArchive<DoubleSolution>(100))
.setMutation(new PolynomialMutation(mutationProbability, mutationDistributionIndex))
.setMaxIterations(250)
.setSwarmSize(100)
.setSolutionListEvaluator(new SequentialSolutionListEvaluator<DoubleSolution>())
.build();
algorithms.add(new ExperimentAlgorithm<>(algorithm, problemList.get(i).getTag()));
}
for (int i = 0; i < problemList.size(); i++) {
Algorithm<List<DoubleSolution>> algorithm = new NSGAIIBuilder<DoubleSolution>(
problemList.get(i).getProblem(),
new SBXCrossover(1.0, 20.0),
new PolynomialMutation(1.0 / problemList.get(i).getProblem().getNumberOfVariables(), 20.0))
.build();
algorithms.add(new ExperimentAlgorithm<>(algorithm, problemList.get(i).getTag()));
}
for (int i = 0; i < problemList.size(); i++) {
Algorithm<List<DoubleSolution>> algorithm = new SPEA2Builder<DoubleSolution>(
problemList.get(i).getProblem(),
new SBXCrossover(1.0, 10.0),
new PolynomialMutation(1.0 / problemList.get(i).getProblem().getNumberOfVariables(), 20.0))
.build();
algorithms.add(new ExperimentAlgorithm<>(algorithm, problemList.get(i).getTag()));
}
return algorithms ;
}
}