public void Evolve_ManyGenerations_Fast()
{
var selection = new EliteSelection();
var crossover = new UniformCrossover();
var mutation = new UniformMutation(true);
var chromosome = new AutoConfigChromosome();
var targetChromosome = new TspChromosome(10);
var targetFitness = new TspFitness(10, 0, 100, 0, 100);
var fitness = new AutoConfigFitness(targetFitness, targetChromosome);
fitness.PopulationMinSize = 20;
fitness.PopulationMaxSize = 20;
fitness.Termination = new TimeEvolvingTermination(TimeSpan.FromSeconds(5));
var population = new Population(10, 10, chromosome);
var ga = new GeneticAlgorithm(population, fitness, selection, crossover, mutation);
ga.TaskExecutor = new SmartThreadPoolTaskExecutor()
{
MinThreads = 10,
MaxThreads = 20
};
ga.Termination = new GenerationNumberTermination(2);
ga.Start();
Assert.NotNull(ga.BestChromosome);
}
public void Evolve_ManyGenerations_Fast()
{
var selection = new EliteSelection();
var crossover = new UniformCrossover();
var mutation = new UniformMutation(true);
var chromosome = new AutoConfigChromosome();
var targetChromosome = new TspChromosome(10);
var targetFitness = new TspFitness(10, 0, 100, 0, 100);
var fitness = new AutoConfigFitness(targetFitness, targetChromosome);
fitness.PopulationMinSize = 20;
fitness.PopulationMaxSize = 20;
fitness.Termination = new TimeEvolvingTermination(TimeSpan.FromSeconds(5));
var population = new Population(10, 10, chromosome);
var ga = new GeneticAlgorithm(population, fitness, selection, crossover, mutation);
ga.TaskExecutor = new SmartThreadPoolTaskExecutor()
{
MinThreads = 10,
MaxThreads = 20
};
ga.Termination = new GenerationNumberTermination(2);
ga.Start();
Assert.NotNull(ga.BestChromosome);
}
public void GenerateGene_InvalidIndex_Exception()
{
var target = new AutoConfigChromosome();
var actual = Assert.Catch(() => target.GenerateGene(9));
Assert.AreEqual("Invalid AutoConfigChromosome gene index.", actual.Message);
}
public void Evaluate_StartFailed_ZeroFitness()
{
var chromosome = new AutoConfigChromosome();
var targetChromosome = Substitute.For <IChromosome>();
targetChromosome.CreateNew().Returns(x => throw new Exception("TEST"));
var targetFitness = new TspFitness(10, 0, 100, 0, 100);
var target = new AutoConfigFitness(targetFitness, targetChromosome);
var actual = target.Evaluate(chromosome);
Assert.AreEqual(0, actual);
}
public void Evaluate_StartOk_Fitness()
{
var chromosome = new AutoConfigChromosome();
var targetChromosome = new TspChromosome(10);
var targetFitness = new TspFitness(10, 0, 100, 0, 100);
var target = new AutoConfigFitness(targetFitness, targetChromosome);
target.PopulationMinSize = 20;
target.PopulationMaxSize = 20;
target.Termination = new FitnessThresholdTermination(0.1f);
var actual = target.Evaluate(chromosome);
Assert.AreNotEqual(0, actual);
}
