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//  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 .

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.*;
import org.uma.jmetal.qualityindicator.impl.*;
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.*;
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 the algorithms NSGAII,
 * SPEA2, and SMPSO
 *
 * This experiment assumes that the reference Pareto front are 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. Compute que quality indicators
 * 4. Generate Latex tables reporting means and medians
 * 5. Generate R scripts to produce latex tables with the result of applying the Wilcoxon Rank Sum Test
 * 6. Generate Latex tables with the ranking obtained by applying the Friedman test
 * 7. Generate R scripts to obtain boxplots
 *
 * @author Antonio J. Nebro 
 */

public class ZDTStudy {
  private static final int INDEPENDENT_RUNS = 25 ;

  public static void main(String[] args) throws IOException {
    if (args.length != 1) {
      throw new JMetalException("Missing argument: 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);

    List referenceFrontFileNames = Arrays.asList("ZDT1.pf", "ZDT2.pf", "ZDT3.pf", "ZDT4.pf", "ZDT6.pf");

    Experiment> experiment =
        new ExperimentBuilder>("ZDTStudy")
            .setAlgorithmList(algorithmList)
            .setProblemList(problemList)
            .setReferenceFrontDirectory("/pareto_fronts")
            .setReferenceFrontFileNames(referenceFrontFileNames)
            .setExperimentBaseDirectory(experimentBaseDirectory)
            .setOutputParetoFrontFileName("FUN")
            .setOutputParetoSetFileName("VAR")
            .setIndicatorList(Arrays.asList(
                new Epsilon(), new Spread(), new GenerationalDistance(),
                new PISAHypervolume(),
                new InvertedGenerationalDistance(),
                new InvertedGenerationalDistancePlus()))
            .setIndependentRuns(INDEPENDENT_RUNS)
            .setNumberOfCores(8)
            .build();

    new ExecuteAlgorithms<>(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 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 ;
  }
}




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