/// <summary>
/// Constructor for DE.
/// </summary>
/// <param name="fitness">Fitness func.</param>
/// <param name="population">Init pop</param>
public DifferentialEvolution(IFitness fitness, IPopulation population) : base(fitness, population)
{
this.XoverProbability = 0.01;
this.F = 0.5;
termination = new TerminationMaxNumberGeneration();
termination.InitializeTerminationCondition(15_000);
}
/// <summary>
/// Evolutionary strategy
/// </summary>
/// <param name="fitness">fit. func.</param>
/// <param name="population">init pop</param>
public ES_μ_λ(IFitness fitness, IPopulation population) : base(fitness, population)
{
xover = new XoverUniform();
elite = new EliteByFitness(0.1);
selection = new SelectionTournament();
termination = new TerminationMaxNumberGeneration();
termination.InitializeTerminationCondition(15_000);
mutationProbability = 0.01f;
xoverProbability = 0.5f;
}
public EVACMA_ES(IFitness fitness, IPopulation population) : base(fitness, population)
{
termination = new TerminationMaxNumberGeneration();
termination.InitializeTerminationCondition(2_00);
// initialInd = population.CreateIndividual();
}
