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);
}
static void Main(string[] args)
{
Console.ForegroundColor = ConsoleColor.DarkGreen;
Console.WriteLine("GeneticSharp - ConsoleApp");
Console.ResetColor();
Console.WriteLine("Select the sample:");
Console.WriteLine("1) TSP (Travelling Salesman Problem)");
Console.WriteLine("2) Ghostwriter");
var sampleNumber = Console.ReadLine();
ISampleController sampleController = null;
switch (sampleNumber)
{
case "1":
sampleController = new TspSampleController(20);
break;
case "2":
sampleController = new GhostwriterSampleController();
break;
default:
return;
}
var selection = new EliteSelection();
var crossover = new UniformCrossover();
var mutation = new UniformMutation(true);
var fitness = sampleController.CreateFitness();
var population = new Population(50, 70, sampleController.CreateChromosome());
var ga = new GeneticAlgorithm(population, fitness, selection, crossover, mutation);
ga.MutationProbability = 0.4f;
ga.Termination = new FitnessStagnationTermination(100);
ga.TaskExecutor = new SmartThreadPoolTaskExecutor()
{
MinThreads = 25,
MaxThreads = 50
};
ga.GenerationRan += delegate
{
Console.CursorLeft = 0;
Console.CursorTop = 5;
var bestChromosome = ga.Population.BestChromosome;
Console.WriteLine("Generations: {0}", ga.Population.GenerationsNumber);
Console.WriteLine("Fitness: {0:n4}", bestChromosome.Fitness);
Console.WriteLine("Time: {0}", ga.TimeEvolving);
sampleController.Draw(bestChromosome);
};
try
{
ga.Start();
}
catch (Exception ex)
{
Console.ForegroundColor = ConsoleColor.DarkRed;
Console.WriteLine();
Console.WriteLine("Error: {0}", ex.Message);
Console.ResetColor();
Console.ReadKey();
return;
}
Console.ForegroundColor = ConsoleColor.DarkGreen;
Console.WriteLine();
Console.WriteLine("Evolved.");
Console.ResetColor();
Console.ReadKey();
}
public void Cross_ParentsWithTwoGenesProbabilityDiffPercents_DiffChildren()
{
var chromosome1 = MockRepository.GenerateStub<ChromosomeBase>(4);
chromosome1.ReplaceGenes(0, new Gene[]
{
new Gene(1),
new Gene(2),
new Gene(3),
new Gene(4),
});
chromosome1.Expect(c => c.CreateNew()).Return(MockRepository.GenerateStub<ChromosomeBase>(4));
var chromosome2 = MockRepository.GenerateStub<ChromosomeBase>(4);
chromosome2.ReplaceGenes(0, new Gene[]
{
new Gene(5),
new Gene(6),
new Gene(7),
new Gene(8)
});
chromosome2.Expect(c => c.CreateNew()).Return(MockRepository.GenerateStub<ChromosomeBase>(4));
var parents = new List<IChromosome>() { chromosome1, chromosome2 };
var mock = new MockRepository();
var rnd = mock.StrictMock<IRandomization>();
using (mock.Ordered())
{
rnd.Expect(r => r.GetDouble()).Return(0);
rnd.Expect(r => r.GetDouble()).Return(0.49);
rnd.Expect(r => r.GetDouble()).Return(0.5);
rnd.Expect(r => r.GetDouble()).Return(1);
}
RandomizationProvider.Current = rnd;
// 50%
var target = new UniformCrossover(0.5f);
mock.ReplayAll();
var actual = target.Cross(parents);
Assert.AreEqual(2, actual.Count);
Assert.AreEqual(4, actual[0].Length);
Assert.AreEqual(4, actual[1].Length);
Assert.AreEqual(1, actual[0].GetGene(0).Value);
Assert.AreEqual(2, actual[0].GetGene(1).Value);
Assert.AreEqual(7, actual[0].GetGene(2).Value);
Assert.AreEqual(8, actual[0].GetGene(3).Value);
Assert.AreEqual(5, actual[1].GetGene(0).Value);
Assert.AreEqual(6, actual[1].GetGene(1).Value);
Assert.AreEqual(3, actual[1].GetGene(2).Value);
Assert.AreEqual(4, actual[1].GetGene(3).Value);
// 70%
mock = new MockRepository();
rnd = mock.StrictMock<IRandomization>();
using (mock.Ordered())
{
rnd.Expect(r => r.GetDouble()).Return(0);
rnd.Expect(r => r.GetDouble()).Return(0.49);
rnd.Expect(r => r.GetDouble()).Return(0.5);
rnd.Expect(r => r.GetDouble()).Return(1);
}
RandomizationProvider.Current = rnd;
mock.ReplayAll();
target = new UniformCrossover(0.7f);
actual = target.Cross(parents);
Assert.AreEqual(2, actual.Count);
Assert.AreEqual(4, actual[0].Length);
Assert.AreEqual(4, actual[1].Length);
Assert.AreEqual(1, actual[0].GetGene(0).Value);
Assert.AreEqual(2, actual[0].GetGene(1).Value);
Assert.AreEqual(3, actual[0].GetGene(2).Value);
Assert.AreEqual(8, actual[0].GetGene(3).Value);
Assert.AreEqual(5, actual[1].GetGene(0).Value);
Assert.AreEqual(6, actual[1].GetGene(1).Value);
Assert.AreEqual(7, actual[1].GetGene(2).Value);
Assert.AreEqual(4, actual[1].GetGene(3).Value);
}
