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
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
/**
* @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