org.uma.jmetal.runner.singleobjective.GenerationalGeneticAlgorithmDoubleEncodingRunner 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.SBXCrossover;
import org.uma.jmetal.operator.impl.mutation.PolynomialMutation;
import org.uma.jmetal.operator.impl.selection.BinaryTournamentSelection;
import org.uma.jmetal.problem.DoubleProblem;
import org.uma.jmetal.problem.singleobjective.Sphere;
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)) ;
}
}