public static void main(String[] args) throws JMException, ClassNotFoundException { int numberOfVariables = 20; int populationSize = 10; int maxEvaluations = 1000000; Problem problem; // The problem to solve Algorithm algorithm; // The algorithm to use // problem = new Sphere("Real", numberOfVariables) ; // problem = new Easom("Real") ; // problem = new Griewank("Real", populationSize) ; // problem = new Schwefel("Real", numberOfVariables) ; problem = new Rosenbrock("Real", numberOfVariables); // problem = new Rastrigin("Real", numberOfVariables) ; algorithm = new CMAES(problem); /* Algorithm parameters*/ algorithm.setInputParameter("populationSize", populationSize); algorithm.setInputParameter("maxEvaluations", maxEvaluations); /* 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 written to file FUN"); population.printObjectivesToFile("FUN"); System.out.println("Variables values have been written to file VAR"); population.printVariablesToFile("VAR"); } // main
/** * 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 the MOCell algorithm with default parameter settings * * @return an algorithm object * @throws jmetal.util.JMException */ public Algorithm configure() throws JMException { Algorithm algorithm; Operator crossover; Operator mutation; Operator improvement; // Operator for improvement HashMap parameters; // Operator parameters QualityIndicator indicators; // Creating the problem algorithm = new AbYSS(problem_); // Algorithm parameters algorithm.setInputParameter("populationSize", populationSize_); algorithm.setInputParameter("refSet1Size", refSet1Size_); algorithm.setInputParameter("refSet2Size", refSet2Size_); algorithm.setInputParameter("archiveSize", archiveSize_); algorithm.setInputParameter("maxEvaluations", maxEvaluations_); 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); parameters = new HashMap(); parameters.put("improvementRounds", 1); parameters.put("problem", problem_); parameters.put("mutation", mutation); improvement = new MutationLocalSearch(parameters); // Adding the operators to the algorithm algorithm.addOperator("crossover", crossover); algorithm.addOperator("improvement", improvement); /* 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; } // Constructor
/** * 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
/** * 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
/** * @param args Command line arguments. * @throws JMException * @throws IOException * @throws SecurityException Usage: three options - jmetal.metaheuristics.nsgaII.NSGAII_main - * jmetal.metaheuristics.nsgaII.NSGAII_main problemName - * jmetal.metaheuristics.nsgaII.NSGAII_main problemName paretoFrontFile */ public static void main(String[] args) throws JMException, SecurityException, IOException, 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 HashMap parameters; // Operator parameters // Logger object and file to store log messages // logger_ = Configuration.logger_ ; fileHandler_ = new FileHandler("NSGAII_main.log"); // logger_.addHandler(fileHandler_) ; problem = new QOP(); int corridas; String caso; nrocaso = 0; Poblacion population = new Poblacion(50); while (nrocaso < casosDePrueba.length) { corridas = 1; long initTime2 = System.currentTimeMillis(); while (corridas < 11) { algorithm = new NSGAII_G10(problem, nrocaso); caso = casosDePrueba[nrocaso]; // algorithm = new ssNSGAII(problem); // Algorithm parameters algorithm.setInputParameter("populationSize", 5); algorithm.setInputParameter("maxEvaluations", 2500); algorithm.setInputParameter("probMutacion", 1); // 10% algorithm.setInputParameter("nrocaso", nrocaso); algorithm.setInputParameter("corridas", corridas); // 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("BinaryTournament2", parameters) ; */ // Add the operators to the algorithm /*algorithm.addOperator("crossover",crossover); algorithm.addOperator("mutation",mutation); algorithm.addOperator("selection",selection);*/ // algorithm.addOperator("torneobinario", torneobinario); // Add the indicator object to the algorithm // System.out.println(" "+corridas); // Execute the Algorithm long initTime = System.currentTimeMillis(); // System.out.println(caso + "-" + corridas + " Test Genetico."); population = algorithm.execute(); long estimatedTime = System.currentTimeMillis() - initTime; // Result messages if (population != null) { // logger_.info("Total execution time: "+estimatedTime + "ms"); // logger_.info("Variables values have been writen to file VAR"); population.printVariablesToFile("VAR_p3" + caso); // logger_.info("Objectives values have been writen to file FUN"); population.printObjectivesToFile("FUN_p3" + caso); } else { System.out.println("No arrojo resultados"); } /*if (indicators != null) { logger_.info("Quality indicators") ; logger_.info("Hypervolume: " + indicators.getHypervolume(population)) ; logger_.info("GD : " + indicators.getGD(population)) ; logger_.info("IGD : " + indicators.getIGD(population)) ; logger_.info("Spread : " + indicators.getSpread(population)) ; logger_.info("Epsilon : " + indicators.getEpsilon(population)) ; int evaluations = ((Integer)algorithm.getOutputParameter("evaluations")).intValue(); logger_.info("Speed : " + evaluations + " evaluations") ; } // if*/ corridas++; } long estimatedTime2 = System.currentTimeMillis() - initTime2; long tiempo = estimatedTime2; long hora = tiempo / 3600000; long restohora = tiempo % 3600000; long minuto = restohora / 60000; long restominuto = restohora % 60000; long segundo = restominuto / 1000; long restosegundo = restominuto % 1000; String time = hora + ":" + minuto + ":" + segundo + "." + restosegundo; time = " Tiempo: " + time; String fin = casosDePrueba[nrocaso] + " FIN - Test Genetico. Tiempo:" + time; // fin += " - NÂș Generaciones: " + evaluations; System.out.println(fin); if (population != null) population.printFinalResults(); nrocaso++; } System.out.println("FIN Prueba Algoritmo Genetico. (Segment-Oriented)."); } // main
/** @param args the command line arguments -- modelname, alg_name, evaluation_times, [runid] */ public static void main(String[] args) throws Exception { try { String name = args[0]; URL location = Main.class.getProtectionDomain().getCodeSource().getLocation(); String loc = location.toString(); String project_path = loc.substring(5, loc.lastIndexOf("SPL/")) + "SPL/"; // with '/' at the end String fm = project_path + "dimacs_data/" + name + ".dimacs"; String augment = fm + ".augment"; String dead = fm + ".dead"; String mandatory = fm + ".mandatory"; String seed = fm + ".richseed"; String opfile = fm + ".sipop"; Problem p = new ProductLineProblem(fm, augment, mandatory, dead, seed); // Problem p = new ProductLineProblemNovelPrep(fm, augment, mandatory, dead, seed, // opfile); // GroupedProblem.grouping((ProductLineProblem) p, 100); System.exit(0); Algorithm a; int evaluation_times = Integer.parseInt(args[2]); String alg_name = args[1]; String runid = ""; if (args.length >= 4) { runid = args[3]; } switch (alg_name) { case "IBEA": a = new SPL_SettingsIBEA(p).configureICSE2013(evaluation_times); break; case "SIPIBEA": a = new SPL_SettingsIBEA(p).configureSIPIBEA(evaluation_times); break; case "SPEA2": a = new SPL_SettingsEMOs(p).configureSPEA2(evaluation_times); break; case "NSGA2": a = new SPL_SettingsEMOs(p).configureNSGA2(evaluation_times); break; case "IBEASEED": a = new SPL_SettingsIBEA(p).configureIBEASEED(evaluation_times); break; case "SATIBEA": // a = new SPL_SettingsIBEA(p).configureICSE15(1000, fm, ((ProductLineProblem) // p).getNumFeatures(), // ((ProductLineProblem) p).getConstraints()); a = new SPL_SettingsIBEA(p) .configureSATIBEA( evaluation_times, fm, ((ProductLineProblem) p).getNumFeatures(), ((ProductLineProblem) p).getConstraints()); break; default: a = new SPL_SettingsIBEA(p).configureICSE2013(evaluation_times); } long start = System.currentTimeMillis(); SolutionSet pop = a.execute(); float total_time = (System.currentTimeMillis() - start) / 1000.0f; String file_tag = name + "_" + alg_name + '_' + evaluation_times / 1000 + "k_" + runid + ".txt"; String file_path = project_path + "j_res/" + file_tag; File file = new File(file_path); if (!file.exists()) { file.createNewFile(); } FileWriter fw = new FileWriter(file.getAbsoluteFile()); BufferedWriter bw = new BufferedWriter(fw); for (int i = 0; i < pop.size(); i++) { Variable v = pop.get(i).getDecisionVariables()[0]; bw.write((Binary) v + "\n"); System.out.println("Conf" + (i + 1) + ": " + (Binary) v + " "); } bw.write("~~~\n"); for (int i = 0; i < pop.size(); i++) { Variable v = pop.get(i).getDecisionVariables()[0]; for (int j = 0; j < pop.get(i).getNumberOfObjectives(); j++) { bw.write(pop.get(i).getObjective(j) + " "); System.out.print(pop.get(i).getObjective(j) + " "); } bw.write("\n"); System.out.println(""); } System.out.println(total_time); bw.write("~~~\n" + total_time + "\n"); bw.close(); fw.close(); } catch (Exception e) { e.printStackTrace(); } }
/** * @param args Command line arguments. The first (optional) argument specifies the problem to * solve. * @throws JMException */ public static void main(String[] args) throws JMException, IOException, 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 QualityIndicator indicators; // Object to get quality indicators HashMap parameters; // Operator parameters // Logger object and file to store log messages logger_ = Configuration.logger_; fileHandler_ = new FileHandler("FastPGA_main.log"); logger_.addHandler(fileHandler_); indicators = null; if (args.length == 1) { Object[] params = {"Real"}; problem = (new ProblemFactory()).getProblem(args[0], params); } // if else if (args.length == 2) { Object[] params = {"Real"}; problem = (new ProblemFactory()).getProblem(args[0], params); indicators = new QualityIndicator(problem, args[1]); } // if else { // Default problem problem = new Kursawe("Real", 3); // problem = new Kursawe("BinaryReal", 3); // problem = new Water("Real"); // problem = new ZDT1("ArrayReal", 100); // problem = new ConstrEx("Real"); // problem = new DTLZ1("Real"); // problem = new OKA2("Real") ; } // else algorithm = new FastPGA(problem); algorithm.setInputParameter("maxPopSize", 100); algorithm.setInputParameter("initialPopulationSize", 100); algorithm.setInputParameter("maxEvaluations", 25000); algorithm.setInputParameter("a", 20.0); algorithm.setInputParameter("b", 1.0); algorithm.setInputParameter("c", 20.0); algorithm.setInputParameter("d", 0.0); // Parameter "termination" // If the preferred stopping criterium is PPR based, termination must // be set to 0; otherwise, if the algorithm is intended to iterate until // a give number of evaluations is carried out, termination must be set to // that number algorithm.setInputParameter("termination", 1); // Mutation and Crossover for Real codification parameters = new HashMap(); parameters.put("probability", 0.9); parameters.put("distributionIndex", 20.0); crossover = CrossoverFactory.getCrossoverOperator("SBXCrossover", parameters); // crossover.setParameter("probability",0.9); // crossover.setParameter("distributionIndex",20.0); parameters = new HashMap(); parameters.put("probability", 1.0 / problem.getNumberOfVariables()); parameters.put("distributionIndex", 20.0); mutation = MutationFactory.getMutationOperator("PolynomialMutation", parameters); // Mutation and Crossover for Binary codification parameters = new HashMap(); parameters.put("comparator", new FPGAFitnessComparator()); selection = new BinaryTournament(parameters); algorithm.addOperator("crossover", crossover); algorithm.addOperator("mutation", mutation); algorithm.addOperator("selection", selection); long initTime = System.currentTimeMillis(); SolutionSet population = algorithm.execute(); long estimatedTime = System.currentTimeMillis() - initTime; // Result messages logger_.info("Total execution time: " + estimatedTime + "ms"); logger_.info("Variables values have been writen to file VAR"); population.printVariablesToFile("VAR"); logger_.info("Objectives values have been writen to file FUN"); population.printObjectivesToFile("FUN"); if (indicators != null) { logger_.info("Quality indicators"); logger_.info("Hypervolume: " + indicators.getHypervolume(population)); logger_.info("GD : " + indicators.getGD(population)); logger_.info("IGD : " + indicators.getIGD(population)); logger_.info("Spread : " + indicators.getSpread(population)); logger_.info("Epsilon : " + indicators.getEpsilon(population)); int evaluations = ((Integer) algorithm.getOutputParameter("evaluations")).intValue(); logger_.info("Speed : " + evaluations + " evaluations"); } // if } // main