public void TravellingSalesmanTest()
{
int populationSize = 100;
IRandom rand = new Rand();
this.geneLength = 6;
this.cityInfo = this.BuildCityInfo();
Population candidates = RandomPopulationGenerator.GeneratePopulation(rand, populationSize, 1, geneLength, this.cityInfo.Count, this.cityInfo.Count, new List<Chromosome>(), new List<Chromosome>(), CorrectEncoding);
GeneticAlgorithm ga = new GeneticAlgorithm(rand, candidates, CalculateFitness);
ga.encodingCorrector = CorrectEncoding;
IOrganism solution = ga.FindSolution();
string path = WritePath(solution);
double totalDistance = 1 / CalculateFitness(solution);
Assert.IsTrue(totalDistance <= 25000);
}
public void RouletteWheelSelectorStochasticAcceptanceTest4()
{
IRandom rand = new Rand();
this.TestSelector(new RouletteWheelSelectorStochasticAcceptance(rand), 2, Enumerable.Range(0, 100).Select(i => i / 100.0).ToArray());
}
public void RouletteWheelSelectorStochasticAcceptanceTest1()
{
IRandom rand = new Rand();
this.TestSelector(new RouletteWheelSelectorStochasticAcceptance(rand), 5, 10, 20, 30, 40);
}
public void RouletteWheelSelectorStochasticAcceptanceTest2()
{
IRandom rand = new Rand();
this.TestSelector(new RouletteWheelSelectorStochasticAcceptance(rand), 5, 0.1, 0.2, 0.3, 0.4);
}
public void RouletteWheelSelectionTest2()
{
IRandom rand = new Rand();
this.TestSelector(new RouletteWheelSelector(rand), 5, 0.1, 0.2, 0.3, 0.4);
}
public void RouletteWheelSelectionTest3()
{
IRandom rand = new Rand();
this.TestSelector(new RouletteWheelSelector(rand), 2, Enumerable.Range(0, 100).Select(i => Convert.ToDouble(i)).ToArray());
}
public void LinearRankSelectorTest1()
{
IRandom rand = new Rand();
this.TestSelector(new LinearRankingSelector(rand), 5, 2, 16000, 33000, 50000);
}
public void RouletteWheelSelectionTest1()
{
IRandom rand = new Rand();
this.TestSelector(new RouletteWheelSelector(rand), 5, 10, 20, 30, 40);
}
public void ExponentialRankSelectorTest1()
{
IRandom rand = new Rand();
this.TestSelector(new ExponentialRankingSelector(rand), 5, 10000, 10001, 10002, 10003);
}
public void StochasticUniversalSamplingTest4()
{
IRandom rand = new Rand();
this.TestSelector(new StochasticUniversalSampling(rand), 2, Enumerable.Range(0, 100).Select(i => i / 100.0).ToArray());
}
public void StochasticUniversalSamplingTest2()
{
IRandom rand = new Rand();
this.TestSelector(new StochasticUniversalSampling(rand), 5, 0.1, 0.2, 0.3, 0.4);
}
public void StochasticUniversalSamplingTest1()
{
IRandom rand = new Rand();
this.TestSelector(new StochasticUniversalSampling(rand), 5, 10, 20, 30, 40);
}
public void MutatorTest4()
{
Organism organism = new Organism();
organism.Chromosomes.Add(new Chromosome(1, "10"));
int runCount = 100000;
double mutationProbability = 0;
MutationCounter mutator = new MutationCounter();
IRandom rand = new Rand();
Mutator mutationManager = new Mutator(rand, mutationProbability);
mutationManager.AddMutator(mutator);
for (int i = 0; i <= runCount - 1; i++) {
mutationManager.Mutate(organism);
}
Assert.AreEqual(0, mutator.MutationCount);
Assert.AreEqual("10", organism.Chromosomes[0].ToString());
}