override public Algorithm configure()
{
Algorithm algorithm;
Crossover crossover;
Mutation mutation;
Selection selection;
Dictionary<string, object> parameters;
algorithm = new NSGAII(problem_);
// Algorithm parameters
algorithm.inputParameters_.Add("populationSize", populationSize_);
algorithm.inputParameters_.Add("maxEvaluations", maxEvaluations_);
// Crossover
parameters = new Dictionary<string, object>();
parameters.Add("probability", 0.9);
parameters.Add("distributionIndex", 20.0);
crossover = CrossoverFactory.getCrossoverOperator("SBXCrossover", parameters);
// Mutation
parameters = new Dictionary<string, object>();
parameters.Add("probability", 0.01);
parameters.Add("distributionIndex", 20.0);
mutation = MutationFactory.getMutationOperator("PolynomialMutation", parameters);
// Selection
parameters = null;
selection = SelectionFactory.getSelectionOperator("BinaryTournament", parameters);
selection.comparator_ = new DominanceAndCrowdingDistanceComparator();
// Add the operators to the algorithm
algorithm.operators.Add("crossover", crossover);
algorithm.operators.Add("mutation", mutation);
algorithm.operators.Add("selection", selection);
return algorithm;
}
override public Algorithm configure()
{
Algorithm algorithm;
Crossover crossover;
Mutation mutation;
Selection selection;
Dictionary <string, object> parameters;
algorithm = new NSGAII(problem_);
// Algorithm parameters
algorithm.inputParameters_.Add("populationSize", populationSize_);
algorithm.inputParameters_.Add("maxEvaluations", maxEvaluations_);
// Crossover
parameters = new Dictionary <string, object>();
parameters.Add("probability", 0.9);
parameters.Add("distributionIndex", 20.0);
crossover = CrossoverFactory.getCrossoverOperator("SBXCrossover", parameters);
// Mutation
parameters = new Dictionary <string, object>();
parameters.Add("probability", 0.01);
parameters.Add("distributionIndex", 20.0);
mutation = MutationFactory.getMutationOperator("PolynomialMutation", parameters);
// Selection
parameters = null;
selection = SelectionFactory.getSelectionOperator("BinaryTournament", parameters);
selection.comparator_ = new DominanceAndCrowdingDistanceComparator();
// Add the operators to the algorithm
algorithm.operators.Add("crossover", crossover);
algorithm.operators.Add("mutation", mutation);
algorithm.operators.Add("selection", selection);
return(algorithm);
}
