org.uma.jmetal.runner.singleobjective.GenerationalGeneticAlgorithmDoubleEncodingRunner 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.SBXCrossover;
import org.uma.jmetal.operator.impl.crossover.SinglePointCrossover;
import org.uma.jmetal.operator.impl.mutation.BitFlipMutation;
import org.uma.jmetal.operator.impl.mutation.PolynomialMutation;
import org.uma.jmetal.operator.impl.selection.BinaryTournamentSelection;
import org.uma.jmetal.problem.BinaryProblem;
import org.uma.jmetal.problem.DoubleProblem;
import org.uma.jmetal.problem.singleobjective.OneMax;
import org.uma.jmetal.problem.singleobjective.Sphere;
import org.uma.jmetal.solution.BinarySolution;
import org.uma.jmetal.solution.DoubleSolution;
import org.uma.jmetal.util.AlgorithmRunner;
import org.uma.jmetal.util.JMetalLogger;
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 generational genetic algorithm. The target problem is OneMax.
 *
 * @author Antonio J. Nebro 
 */
public class GenerationalGeneticAlgorithmDoubleEncodingRunner {
  /**
   * Usage: java org.uma.jmetal.runner.singleobjective.GenerationalGeneticAlgorithmDoubleEncodingRunner
   */
  public static void main(String[] args) throws Exception {
    Algorithm algorithm;
    DoubleProblem problem = new Sphere(20) ;

    CrossoverOperator crossover =
            new SBXCrossover(0.9, 20.0) ;
    MutationOperator mutation =
            new PolynomialMutation(1.0 / problem.getNumberOfVariables(), 20.0) ;
    SelectionOperator, DoubleSolution> selection = new BinaryTournamentSelection() ;

    algorithm = new GeneticAlgorithmBuilder<>(problem, crossover, mutation)
            .setPopulationSize(100)
            .setMaxEvaluations(25000)
            .setSelectionOperator(selection)
            .build() ;

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

    DoubleSolution 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");

    JMetalLogger.logger.info("Fitness: " + solution.getObjective(0)) ;
  }
}