org.uma.jmetal.runner.singleobjective.BinaryGenerationalGeneticAlgorithmRunner Maven / Gradle / Ivy
//
//
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.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 BinaryGenerationalGeneticAlgorithmRunner {
/**
* Usage: java org.uma.jmetal.runner.singleobjective.BinaryGenerationalGeneticAlgorithmRunner
*/
public static void main(String[] args) throws Exception {
Algorithm algorithm;
BinaryProblem problem = new OneMax(512) ;
CrossoverOperator crossoverOperator = new SinglePointCrossover(0.9) ;
MutationOperator mutationOperator = new BitFlipMutation(1.0 / problem.getNumberOfBits(0)) ;
SelectionOperator, BinarySolution> selectionOperator = new BinaryTournamentSelection();
algorithm = new GeneticAlgorithmBuilder(problem, crossoverOperator, mutationOperator)
.setPopulationSize(100)
.setMaxEvaluations(25000)
.setSelectionOperator(selectionOperator)
.build() ;
AlgorithmRunner algorithmRunner = new AlgorithmRunner.Executor(algorithm)
.execute() ;
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");
}
}
© 2015 - 2024 Weber Informatics LLC | Privacy Policy