Example #1
0
  /**
   * Configure the algorithm with the specified parameter experiments.settings
   *
   * @return an algorithm object
   * @throws jmetal.util.JMException
   */
  public Algorithm configure() throws JMException {
    Algorithm algorithm;
    Operator selection;
    Operator crossover;

    HashMap parameters; // Operator parameters

    // Creating the problem
    Object[] problemParams = {"Real"};
    problem_ = (new ProblemFactory()).getProblem(problemName_, problemParams);
    algorithm = new CellDE(problem_);

    // Algorithm parameters
    algorithm.setInputParameter("populationSize", populationSize_);
    algorithm.setInputParameter("archiveSize", archiveSize_);
    algorithm.setInputParameter("maxEvaluations", maxEvaluations_);
    algorithm.setInputParameter("feedBack", archiveFeedback_);

    // Crossover operator
    parameters = new HashMap();
    parameters.put("CR", CR_);
    parameters.put("F", F_);
    crossover = CrossoverFactory.getCrossoverOperator("DifferentialEvolutionCrossover", parameters);

    // Add the operators to the algorithm
    parameters = null;
    selection = SelectionFactory.getSelectionOperator("BinaryTournament", parameters);

    algorithm.addOperator("crossover", crossover);
    algorithm.addOperator("selection", selection);

    return algorithm;
  } // configure
  public static void main(String[] args) throws JMException, ClassNotFoundException {
    Problem problem; // The problem to solve
    Algorithm algorithm; // The algorithm to use
    Operator crossover; // Crossover operator
    Operator mutation; // Mutation operator
    Operator selection; // Selection operator

    // int bits ; // Length of bit string in the OneMax problem
    HashMap parameters; // Operator parameters

    int threads = 4; // 0 - use all the available cores
    IParallelEvaluator parallelEvaluator = new MultithreadedEvaluator(threads);

    // problem = new Sphere("Real", 10) ;
    problem = new Griewank("Real", 10);

    algorithm = new pgGA(problem, parallelEvaluator); // Generational GA

    /* Algorithm parameters*/
    algorithm.setInputParameter("populationSize", 100);
    algorithm.setInputParameter("maxEvaluations", 2500000);

    // Mutation and Crossover for Real codification
    parameters = new HashMap();
    parameters.put("probability", 0.9);
    parameters.put("distributionIndex", 20.0);
    crossover = CrossoverFactory.getCrossoverOperator("SBXCrossover", parameters);

    parameters = new HashMap();
    parameters.put("probability", 1.0 / problem.getNumberOfVariables());
    parameters.put("distributionIndex", 20.0);
    mutation = MutationFactory.getMutationOperator("PolynomialMutation", parameters);

    /* Selection Operator */
    parameters = null;
    selection = SelectionFactory.getSelectionOperator("BinaryTournament", parameters);

    /* Add the operators to the algorithm*/
    algorithm.addOperator("crossover", crossover);
    algorithm.addOperator("mutation", mutation);
    algorithm.addOperator("selection", selection);

    /* Execute the Algorithm */
    long initTime = System.currentTimeMillis();
    SolutionSet population = algorithm.execute();
    long estimatedTime = System.currentTimeMillis() - initTime;
    System.out.println("Total execution time: " + estimatedTime);

    /* Log messages */
    System.out.println("Objectives values have been writen to file FUN");
    population.printObjectivesToFile("FUN");
    System.out.println("Variables values have been writen to file VAR");
    population.printVariablesToFile("VAR");
  } // main
  /**
   * Configure SPEA2 with default parameter settings
   *
   * @return an algorithm object
   * @throws jmetal.util.JMException
   */
  public Algorithm configure() throws JMException {
    Algorithm algorithm;
    Operator crossover; // Crossover operator
    Operator mutation; // Mutation operator
    Operator selection; // Selection operator

    QualityIndicator indicators;

    HashMap parameters; // Operator parameters

    // Creating the problem
    algorithm = new SPEA2(problem_);

    // Algorithm parameters
    algorithm.setInputParameter("populationSize", populationSize_);
    algorithm.setInputParameter("archiveSize", archiveSize_);
    algorithm.setInputParameter("maxEvaluations", maxEvaluations_);

    // Mutation and Crossover for Real codification
    parameters = new HashMap();
    parameters.put("probability", crossoverProbability_);
    parameters.put("distributionIndex", crossoverDistributionIndex_);
    crossover = CrossoverFactory.getCrossoverOperator("SBXCrossover", parameters);

    parameters = new HashMap();
    parameters.put("probability", mutationProbability_);
    parameters.put("distributionIndex", mutationDistributionIndex_);
    mutation = MutationFactory.getMutationOperator("PolynomialMutation", parameters);

    // Selection operator
    parameters = null;
    selection = SelectionFactory.getSelectionOperator("BinaryTournament", parameters);

    // Add the operators to the algorithm
    algorithm.addOperator("crossover", crossover);
    algorithm.addOperator("mutation", mutation);
    algorithm.addOperator("selection", selection);

    /* Deleted since jMetal 4.2
    // Creating the indicator object
    if ((paretoFrontFile_!=null) && (!paretoFrontFile_.equals(""))) {
       indicators = new QualityIndicator(problem_, paretoFrontFile_);
       algorithm.setInputParameter("indicators", indicators) ;
    } // if
    */

    return algorithm;
  } // configure
Example #4
0
  /**
   * Configure the MOCell algorithm with default parameter experiments.settings
   *
   * @return an algorithm object
   * @throws jmetal.util.JMException
   */
  public Algorithm configure() throws JMException {
    Algorithm algorithm;

    Crossover crossover;
    Mutation mutation;
    Operator selection;

    HashMap parameters; // Operator parameters

    // Selecting the algorithm: there are six MOCell variants
    Object[] problemParams = {"Real"};
    problem_ = (new ProblemFactory()).getProblem(problemName_, problemParams);
    // algorithm = new sMOCell1(problem_) ;
    // algorithm = new sMOCell2(problem_) ;
    // algorithm = new aMOCell1(problem_) ;
    // algorithm = new aMOCell2(problem_) ;
    // algorithm = new aMOCell3(problem_) ;
    algorithm = new MOCell(problem_);

    // Algorithm parameters
    algorithm.setInputParameter("populationSize", populationSize_);
    algorithm.setInputParameter("maxEvaluations", maxEvaluations_);
    algorithm.setInputParameter("archiveSize", archiveSize_);
    algorithm.setInputParameter("feedBack", feedback_);

    // Mutation and Crossover for Real codification
    parameters = new HashMap();
    parameters.put("probability", crossoverProbability_);
    parameters.put("distributionIndex", crossoverDistributionIndex_);
    crossover = CrossoverFactory.getCrossoverOperator("SBXCrossover", parameters);

    parameters = new HashMap();
    parameters.put("probability", mutationProbability_);
    parameters.put("distributionIndex", mutationDistributionIndex_);
    mutation = MutationFactory.getMutationOperator("PolynomialMutation", parameters);

    // Selection Operator
    parameters = null;
    selection = SelectionFactory.getSelectionOperator("BinaryTournament", parameters);

    // Add the operators to the algorithm
    algorithm.addOperator("crossover", crossover);
    algorithm.addOperator("mutation", mutation);
    algorithm.addOperator("selection", selection);

    return algorithm;
  } // configure
  public SPEA2Search(Builder builder) throws JMException {
    super(builder);

    this.populationSize = builder.populationSize;
    this.maxEvaluations = builder.maxEvaluations;
    this.archiveSize = builder.archiveSize;
    this.crossoverOperatorName = builder.crossoverOperatorName;
    this.crossoverProbability = builder.crossoverProbability;
    this.mutationOperatorName = builder.mutationOperatorName;
    if (builder.mutationProbability != 0) this.mutationProbability = builder.mutationProbability;
    this.selectionOperatorName = builder.selectionOperatorName;

    this.problem = new SeaCloudsProblem(this.appMap, this.suitableCloudOfferMap, this.topology);

    this.algorithm = new SPEA2(this.problem);
    this.metaHeuristicName = this.getAlgorithm().getClass().getSimpleName();

    // Algorithm parameters
    this.algorithm.setInputParameter("populationSize", this.populationSize);
    this.algorithm.setInputParameter("maxEvaluations", this.maxEvaluations);
    this.algorithm.setInputParameter("archiveSize", this.archiveSize);

    // Crossover Operator
    this.parameters = new HashMap();
    this.parameters.put("probability", this.crossoverProbability);
    // this.crossover = CrossoverFactory.getCrossoverOperator(
    // "MultiPointCrossover", this.parameters);
    this.crossover =
        CrossoverFactory.getCrossoverOperator(
            this.crossoverOperatorName.getCrossoverOperatorValue(), this.parameters);

    this.parameters.clear();

    // Mutation Operator
    this.parameters.put("probability", this.mutationProbability);
    // this.mutation = MutationFactory.getMutationOperator(
    // "PACandNumOfInstancesMutation", this.parameters);
    this.mutation =
        MutationFactory.getMutationOperator(
            this.mutationOperatorName.getMutationOperatorValue(), this.parameters);

    this.parameters.clear();

    // Selection Operator
    // this.selection =
    // SelectionFactory.getSelectionOperator("BinaryTournament",
    // this.parameters);
    if ((builder
            .selectionOperatorName
            .getSelectionOperatorValue()
            .equals(SelectionOperatorName.BEST_SOLUTION.getSelectionOperatorValue()))
        || (builder
            .selectionOperatorName
            .getSelectionOperatorValue()
            .equals(SelectionOperatorName.WORST_SOLUTION.getSelectionOperatorValue()))) {
      //       Comparator comparator = new DominanceComparator();
      Comparator comparator = new EqualSolutions();
      this.parameters.put("comparator", comparator);
    }
    this.selection =
        SelectionFactory.getSelectionOperator(
            this.selectionOperatorName.getSelectionOperatorValue(), this.parameters);

    // Add the operators to the algorithm
    this.algorithm.addOperator("crossover", this.crossover);
    this.algorithm.addOperator("mutation", this.mutation);
    this.algorithm.addOperator("selection", this.selection);
  }