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();
}
public void GivenAprobabilityOfZero_WhenIndividualsAreCrossed_ItShouldReturnAnIndividualWithThePositionOfIndividualOne()
{
Individual individual1 = new Individual(null, new Configuration())
{
Position = new double[] { 1.0, 2.0, 3.0 }
};
Individual individual2 = new Individual(null, new Configuration())
{
Position = new double[] { 9.0, 11.0, 11.0 }
};
MockRandom();
BinomialCrossoverStrategy crossoverStrategy = new BinomialCrossoverStrategy(new Configuration(), 0.0);
Individual result = crossoverStrategy.Cross(individual1, individual2);
Assert.IsTrue(individual1.Position.SequenceEqual(result.Position));
}
public void GivenAnTwoIndividuals_WhenTheyAreCombined_ItShouldReturnAnIndividualDifferentFromTheInputs()
{
Individual individual1 = new Individual(null, new Configuration())
{
Position = new double[] { 1.0, 2.0, 3.0 }
};
Individual individual2 = new Individual(null, new Configuration())
{
Position = new double[] { 9.0, 11.0, 11.0 }
};
MockRandom();
BinomialCrossoverStrategy crossoverStrategy = new BinomialCrossoverStrategy(new Configuration());
Individual result = crossoverStrategy.Cross(individual1, individual2);
Assert.IsFalse(individual1.Position.SequenceEqual(result.Position));
Assert.IsFalse(individual2.Position.SequenceEqual(result.Position));
}
public void GivenAnTwoIndividuals_WhenTheyAreCombined_ItShouldReturnAnIndividualWithPartsFromEachIndividual()
{
Individual individual1 = new Individual(null, new Configuration())
{
Position = new double[] { 1.0, 2.0, 3.0 }
};
Individual individual2 = new Individual(null, new Configuration())
{
Position = new double[] { 9.0, 11.0, 11.0 }
};
MockRandom();
BinomialCrossoverStrategy crossoverStrategy = new BinomialCrossoverStrategy(new Configuration());
Individual result = crossoverStrategy.Cross(individual1, individual2);
int totalFromIndividual1 = 0;
int totalFromIndividual2 = 0;
for (int i = 0; i < individual1.Position.Length; i++)
{
if (result.Position[i] == individual1.Position[i])
{
totalFromIndividual1++;
}
else
{
totalFromIndividual2++;
}
}
Assert.IsTrue(totalFromIndividual1 > 0);
Assert.IsTrue(totalFromIndividual2 > 0);
}
