private void ChooseRecombinationStrategy()
{
if (EvolutionaryAlgorithmConstants.IS_USING_RANDOM_START_END_CITY == false)
{
recombination = new Recombination();
}
else
{
recombination = new RecombinationVariableStartEnd();
}
}
public Individual<T>[] CreateNextGeneration(Individual<T>[] originalPopulation, ISelectionStrategy<T> selection,
IRecombinationStrategy<T> recombination, IMutationStrategy<T> mutation)
{
Array.Sort(originalPopulation); // sorting may not always be mandatory (e.g. 1-3 elites, selection does not sort)
int offspringsCount = populationSize - elitesCount;
// TODO: Redundant copying. A linked list would be better.
Individual<T>[] offsprings = recombination.Apply(selection, originalPopulation, offspringsCount);
mutation.Apply(offsprings);
Individual<T>[] nextPopulation = new Individual<T>[populationSize];
Array.Copy(originalPopulation, nextPopulation, elitesCount);
Array.Copy(offsprings, 0, nextPopulation, elitesCount, offsprings.Length);
return nextPopulation;
}
public Individual<T>[] CreateNextGeneration(Individual<T>[] originalPopulation, ISelectionStrategy<T> selection,
IRecombinationStrategy<T> recombination, IMutationStrategy<T> mutation)
{
Array.Sort(originalPopulation);
// Selection and rcombination: Only the elites and the rest of survivors will have a chance to reproduce
Individual<T>[] selectionPool = new Individual<T>[elitesCount + survivorsCount];
Array.Copy(originalPopulation, selectionPool, selectionPool.Length);
// TODO: Redundant copying. A linked list would be better.
Individual<T>[] offsprings = recombination.Apply(selection, selectionPool, offspringsCount);
// Mutation will be applied to the survivors and their offsprings but not on the elites
Individual<T>[] mutants = new Individual<T>[survivorsCount + offsprings.Length];
Array.Copy(originalPopulation, elitesCount, mutants, 0, survivorsCount);
Array.Copy(offsprings, 0, mutants, survivorsCount, offspringsCount);
mutation.Apply(mutants);
// The next population will contain the elites, the mutated survivors and the mutated offsprings
Individual<T>[] nextPopulation = new Individual<T>[originalPopulation.Length];
Array.Copy(originalPopulation, nextPopulation, elitesCount);
Array.Copy(mutants, 0, nextPopulation, elitesCount, survivorsCount + offspringsCount);
return nextPopulation;
}
private GeneticAlgorithm(int continuousVariablesCount, int integerVariablesCount, IDesignFactory designFactory,
IOptimizationLogger logger, IConvergenceCriterion convergenceCriterion, IInitializer <double> initializer,
IEncoding <T> encoding, int populationSize, IPopulationStrategy <T> populationStrategy,
ISelectionStrategy <T> selection, IRecombinationStrategy <T> recombination, IMutationStrategy <T> mutation)
{
this.continuousVariablesCount = continuousVariablesCount;
this.integerVariablesCount = integerVariablesCount;
this.designFactory = designFactory;
this.logger = logger;
this.convergenceCriterion = convergenceCriterion;
this.initializer = initializer;
this.encoding = encoding;
this.populationSize = populationSize;
this.populationStrategy = populationStrategy;
this.selection = selection;
this.recombination = recombination;
this.mutation = mutation;
this.CurrentIteration = -1; // Initialization phase is not counted towards iterations
this.BestPosition = null;
this.BestFitness = double.MaxValue;
}
public Individual <T>[] CreateNextGeneration(Individual <T>[] originalPopulation, ISelectionStrategy <T> selection,
IRecombinationStrategy <T> recombination, IMutationStrategy <T> mutation)
{
throw new NotImplementedException();
}
