public void GivenADifferentialEvolutionAlgorithm_WhenTheAlgorithmIsRun_ItShouldResultInAPopulationWithAtLeastOneIndividual()
{
Mock <IFitnessEvaluationStrategy> fitnessEvaluationMock = new Mock <IFitnessEvaluationStrategy>();
IFitnessEvaluationStrategy fitnessEvaluationStrategy = fitnessEvaluationMock.Object;
Mock <ICrossoverStrategy> crossoverMock = new Mock <ICrossoverStrategy>();
crossoverMock.Setup(x => x.Cross(It.IsAny <Individual>(), It.IsAny <Individual>()))
.Returns(new Individual(fitnessEvaluationStrategy, new Configuration()));
ICrossoverStrategy crossoverStrategy = crossoverMock.Object;
Mock <IMutationStrategy> mutationMock = new Mock <IMutationStrategy>();
IMutationStrategy mutationStrategy = mutationMock.Object;
Mock <ISelectionStrategy> selectionMock = new Mock <ISelectionStrategy>();
selectionMock.Setup(x => x.Select(It.IsAny <List <Individual> >()))
.Returns(new Individual(fitnessEvaluationStrategy, new Configuration()));
ISelectionStrategy selectionStrategy = selectionMock.Object;
DifferentialEvolution differentialEvolution = new DifferentialEvolution(mutationStrategy,
crossoverStrategy,
selectionStrategy,
selectionStrategy,
fitnessEvaluationStrategy,
new Configuration());
differentialEvolution.Run();
Assert.IsTrue(differentialEvolution.population.Count > 0);
}
public void GivenFiveIterationsAndThreeIndividuals_WhenTheAlgorithmIsRun_ItShouldCallTheCrossoverStrategyFifteenTimes()
{
Mock <IFitnessEvaluationStrategy> fitnessEvaluationMock = new Mock <IFitnessEvaluationStrategy>();
IFitnessEvaluationStrategy fitnessEvaluationStrategy = fitnessEvaluationMock.Object;
Mock <ICrossoverStrategy> crossoverMock = new Mock <ICrossoverStrategy>();
crossoverMock.Setup(x => x.Cross(It.IsAny <Individual>(), It.IsAny <Individual>()))
.Returns(new Individual(fitnessEvaluationStrategy, new Configuration()));
ICrossoverStrategy crossoverStrategy = crossoverMock.Object;
Mock <IMutationStrategy> mutationMock = new Mock <IMutationStrategy>();
IMutationStrategy mutationStrategy = mutationMock.Object;
Mock <ISelectionStrategy> selectionMock = new Mock <ISelectionStrategy>();
selectionMock.Setup(x => x.Select(It.IsAny <List <Individual> >()))
.Returns(new Individual(fitnessEvaluationStrategy, new Configuration()));
ISelectionStrategy selectionStrategy = selectionMock.Object;
DifferentialEvolution differentialEvolution = new DifferentialEvolution(mutationStrategy,
crossoverStrategy,
selectionStrategy,
selectionStrategy,
fitnessEvaluationStrategy,
new Configuration());
differentialEvolution.Run();
crossoverMock.Verify(c => c.Cross(It.IsAny <Individual>(), It.IsAny <Individual>()), Times.Exactly(15));
}
static void Main(string[] args)
{
IConfiguration configuration = new Configuration();
IMutationStrategy trialVectorMutationStrategy = new TrialIndividualMutationStrategy(configuration);
ICrossoverStrategy crossoverStrategy = new BinomialCrossoverStrategy(configuration);
ISelectionStrategy generationSelectionStrategy = new MinimisationElitistSelectionStrategy();
ISelectionStrategy differenceVectorSelectionStrategy = new RandomSelectionStrategy();
IFitnessEvaluationStrategy fitnessEvaluationStrategy = new RastriginFitnessEvaluationStrategy();
DifferentialEvolution differentialEvolution = new DifferentialEvolution(
trialVectorMutationStrategy,
crossoverStrategy,
generationSelectionStrategy,
differenceVectorSelectionStrategy,
fitnessEvaluationStrategy,
configuration
);
differentialEvolution.Run();
var population = differentialEvolution.population;
foreach (Individual individual in population)
{
foreach (double dimension in individual.Position)
{
Console.Write(Math.Round(dimension) + ", ");
}
Console.WriteLine();
}
Console.Read();
}
