public static void TestThatChildChanged(this ICrossoverManager crossoverManager)
{
var elements = new List <string>()
{
"A", "B", "C", "D", "E", "F", "G", "H", "I", "J"
};
var generator = new AllElementsVectorChromosomePopulationGenerator <string>(elements, null, null);
// Since there's a certain chance that this test will fail, I want to run it twice
var passed = false;
for (int i = 0; i < 2; i++)
{
var parentChromosomes = generator.GeneratePopulation(2);
var child = (VectorChromosome <string>)crossoverManager.Crossover(parentChromosomes.ElementAt(0),
parentChromosomes.ElementAt(1));
try
{
((VectorChromosome <string>)parentChromosomes.ElementAt(0)).AssertAreNotTheSame(child);
((VectorChromosome <string>)parentChromosomes.ElementAt(1)).AssertAreNotTheSame(child);
passed = true;
}
catch
{
// Do nothing
}
}
Assert.IsTrue(passed);
}
private void TestCycleCrossover(string[] parent1, string[] parent2, string[] expectedChild)
{
var chromosome1 = new VectorChromosome <string>(parent1, null, null);
var chromosome2 = new VectorChromosome <string>(parent2, null, null);
var child = (VectorChromosome <string>)crossoverManager.Crossover(chromosome1, chromosome2);
child.AssertAreTheSame(expectedChild);
}
public static void TestThatAllElementsInEachVector(this ICrossoverManager crossoverManager, int testRuns)
{
var elements = new List <string>()
{
"A", "B", "C", "D", "E", "F", "G", "H", "I", "J"
};
var generator = new AllElementsVectorChromosomePopulationGenerator <string>(elements, null, null);
for (int i = 0; i < testRuns; i++)
{
var parentChromosomes = generator.GeneratePopulation(2);
var child = (VectorChromosome <string>)crossoverManager.Crossover(parentChromosomes.ElementAt(0), parentChromosomes.ElementAt(1));
child.AssertContainSameElements(elements);
}
}
public IChromosome[] GenerateChildren(Population population, int number, int generation, IEnvironment environment)
{
if (number < 1)
{
throw new InternalSearchException("Code 1003 (requested 0 children)");
}
selectionStrategy.SetPopulation(population, number * 2);
var mutationProbability = mutationManager.MutationProbability(population, environment, generation);
CheckMuationProbability(mutationProbability);
var children = new ConcurrentBag <IChromosome>();
var tasks = new Task[number];
for (int i = 0; i < number; i++)
{
tasks[i] = Task.Run(() =>
{
var parent1 = AssertNotNull(selectionStrategy.SelectChromosome());
var parent2 = AssertNotNull(selectionStrategy.SelectChromosome());
var child = crossoverManager.Crossover(parent1, parent2);
if (ProbabilityUtils.P(mutationProbability))
{
child.Mutate();
}
children.Add(child);
});
}
foreach (var task in tasks)
{
task.Wait();
}
return(children.ToArray());
}
