org.uma.jmetal.experiment.ZDTStudy2 Maven / Gradle / Ivy
// 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
*/
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> 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>> algorithmList =
configureAlgorithmList(problemList);
ExperimentBuilder> zdt2Study = new ExperimentBuilder>("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(), new Spread(), new GenerationalDistance(),
new PISAHypervolume(),
new InvertedGenerationalDistance(), new InvertedGenerationalDistancePlus()));
zdt2Study.setIndependentRuns(INDEPENDENT_RUNS);
zdt2Study.setNumberOfCores(8);
Experiment> 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>> configureAlgorithmList(
List> problemList) {
List>> 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> algorithm = new SMPSOBuilder((DoubleProblem) problemList.get(i).getProblem(),
new CrowdingDistanceArchive(100))
.setMutation(new PolynomialMutation(mutationProbability, mutationDistributionIndex))
.setMaxIterations(250)
.setSwarmSize(100)
.setSolutionListEvaluator(new SequentialSolutionListEvaluator())
.build();
algorithms.add(new ExperimentAlgorithm<>(algorithm, problemList.get(i).getTag()));
}
for (int i = 0; i < problemList.size(); i++) {
Algorithm> algorithm = new NSGAIIBuilder(
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> algorithm = new SPEA2Builder(
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 ;
}
}