org.uma.jmetal.runner.singleobjective.ParallelGenerationalGeneticAlgorithmRunner Maven / Gradle / Ivy

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package org.uma.jmetal.runner.singleobjective;

import org.uma.jmetal.algorithm.Algorithm;
import org.uma.jmetal.algorithm.singleobjective.geneticalgorithm.GeneticAlgorithmBuilder;
import org.uma.jmetal.operator.CrossoverOperator;
import org.uma.jmetal.operator.MutationOperator;
import org.uma.jmetal.operator.SelectionOperator;
import org.uma.jmetal.operator.impl.crossover.SinglePointCrossover;
import org.uma.jmetal.operator.impl.mutation.BitFlipMutation;
import org.uma.jmetal.operator.impl.selection.BinaryTournamentSelection;
import org.uma.jmetal.problem.BinaryProblem;
import org.uma.jmetal.problem.singleobjective.OneMax;
import org.uma.jmetal.solution.BinarySolution;
import org.uma.jmetal.util.AlgorithmRunner;
import org.uma.jmetal.util.JMetalLogger;
import org.uma.jmetal.util.evaluator.impl.MultithreadedSolutionListEvaluator;
import org.uma.jmetal.util.fileoutput.SolutionListOutput;
import org.uma.jmetal.util.fileoutput.impl.DefaultFileOutputContext;

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

/**
 * Class to configure and run a parallel (multithreaded) generational genetic algorithm. The number
 * of cores is specified as an optional parameter. A default value is used is the parameter is not
 * provided. The target problem is OneMax
 *
 * @author Antonio J. Nebro 
 */
public class ParallelGenerationalGeneticAlgorithmRunner {
  private static final int DEFAULT_NUMBER_OF_CORES = 0 ;
  /**
   * Usage: java org.uma.jmetal.runner.singleobjective.ParallelGenerationalGeneticAlgorithmRunner [cores]
   */
  public static void main(String[] args) throws Exception {
    Algorithm algorithm;
    BinaryProblem problem = new OneMax(512) ;

    int numberOfCores ;
    if (args.length == 1) {
      numberOfCores = Integer.valueOf(args[0]) ;
    } else {
      numberOfCores = DEFAULT_NUMBER_OF_CORES ;
    }

    CrossoverOperator crossoverOperator = new SinglePointCrossover(0.9) ;
    MutationOperator mutationOperator = new BitFlipMutation(1.0 / problem.getNumberOfBits(0)) ;
    SelectionOperator, BinarySolution> selectionOperator = new BinaryTournamentSelection();

    GeneticAlgorithmBuilder builder = new GeneticAlgorithmBuilder(
        problem, crossoverOperator, mutationOperator)
        .setPopulationSize(100)
        .setMaxEvaluations(25000)
        .setSelectionOperator(selectionOperator)
        .setSolutionListEvaluator(new MultithreadedSolutionListEvaluator(numberOfCores, problem)) ;

    algorithm = builder.build() ;

    AlgorithmRunner algorithmRunner = new AlgorithmRunner.Executor(algorithm)
        .execute() ;

    builder.getEvaluator().shutdown();

    BinarySolution solution = algorithm.getResult() ;
    List population = new ArrayList<>(1) ;
    population.add(solution) ;

    long computingTime = algorithmRunner.getComputingTime() ;

    new SolutionListOutput(population)
        .setSeparator("\t")
        .setVarFileOutputContext(new DefaultFileOutputContext("VAR.tsv"))
        .setFunFileOutputContext(new DefaultFileOutputContext("FUN.tsv"))
        .print();

    JMetalLogger.logger.info("Total execution time: " + computingTime + "ms");
    JMetalLogger.logger.info("Objectives values have been written to file FUN.tsv");
    JMetalLogger.logger.info("Variables values have been written to file VAR.tsv");
  }
}