org.uma.jmetal.runner.multiobjective.SMPSOHvRunner Maven / Gradle / Ivy
// SMPSORunner.java
//
// Author:
// Antonio J. Nebro
//
// Copyright (c) 2014 Antonio J. Nebro
//
// 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.runner.multiobjective;
import org.uma.jmetal.algorithm.Algorithm;
import org.uma.jmetal.algorithm.multiobjective.smpso.SMPSO;
import org.uma.jmetal.algorithm.multiobjective.smpso.SMPSOBuilder;
import org.uma.jmetal.operator.MutationOperator;
import org.uma.jmetal.operator.impl.mutation.PolynomialMutation;
import org.uma.jmetal.problem.DoubleProblem;
import org.uma.jmetal.qualityindicator.impl.hypervolume.PISAHypervolume;
import org.uma.jmetal.runner.AbstractAlgorithmRunner;
import org.uma.jmetal.solution.DoubleSolution;
import org.uma.jmetal.util.AlgorithmRunner;
import org.uma.jmetal.util.JMetalLogger;
import org.uma.jmetal.util.ProblemUtils;
import org.uma.jmetal.util.archive.BoundedArchive;
import org.uma.jmetal.util.archive.impl.HypervolumeArchive;
import org.uma.jmetal.util.evaluator.impl.SequentialSolutionListEvaluator;
import org.uma.jmetal.util.pseudorandom.impl.MersenneTwisterGenerator;
import java.util.List;
/**
* Class for configuring and running the SMPSO algorithm using an HypervolumeArchive, i.e, the
* SMPSOhv algorithm described in:
* A.J Nebro, J.J. Durillo, C.A. Coello Coello. Analysis of Leader Selection Strategies in a
* Multi-Objective Particle Swarm Optimizer. 2013 IEEE Congress on Evolutionary Computation. June 2013
* DOI: 10.1109/CEC.2013.6557955
*
* @author Antonio J. Nebro
*/
public class SMPSOHvRunner extends AbstractAlgorithmRunner {
/**
* @param args Command line arguments. The first (optional) argument specifies
* the problem to solve.
* @throws org.uma.jmetal.util.JMetalException
* @throws java.io.IOException
* @throws SecurityException
* Invoking command:
java org.uma.jmetal.runner.multiobjective.SMPSOHvRunner problemName [referenceFront]
*/
public static void main(String[] args) throws Exception {
DoubleProblem problem;
Algorithm> algorithm;
MutationOperator mutation;
String referenceParetoFront = "" ;
String problemName ;
if (args.length == 1) {
problemName = args[0];
} else if (args.length == 2) {
problemName = args[0] ;
referenceParetoFront = args[1] ;
} else {
//problemName = "org.uma.jmetal.problem.multiobjective.dtlz.DTLZ1";
//referenceParetoFront = "jmetal-problem/src/test/resources/pareto_fronts/DTLZ1.3D.pf" ;
problemName = "org.uma.jmetal.problem.multiobjective.zdt.ZDT4";
referenceParetoFront = "jmetal-problem/src/test/resources/pareto_fronts/ZDT4.pf" ;
}
problem = (DoubleProblem) ProblemUtils. loadProblem(problemName);
BoundedArchive archive =
new HypervolumeArchive(100, new PISAHypervolume()) ;
double mutationProbability = 1.0 / problem.getNumberOfVariables() ;
double mutationDistributionIndex = 20.0 ;
mutation = new PolynomialMutation(mutationProbability, mutationDistributionIndex) ;
algorithm = new SMPSOBuilder(problem, archive)
.setMutation(mutation)
.setMaxIterations(250)
.setSwarmSize(100)
.setRandomGenerator(new MersenneTwisterGenerator())
.setSolutionListEvaluator(new SequentialSolutionListEvaluator())
.build();
AlgorithmRunner algorithmRunner = new AlgorithmRunner.Executor(algorithm)
.execute();
List population = ((SMPSO)algorithm).getResult();
long computingTime = algorithmRunner.getComputingTime();
JMetalLogger.logger.info("Total execution time: " + computingTime + "ms");
printFinalSolutionSet(population);
if (!referenceParetoFront.equals("")) {
printQualityIndicators(population, referenceParetoFront) ;
}
}
}