private void InitializeEngine()
{
var engineBuidler = new GeneticSearchEngineBuilder(POPULATION_SIZE, GENERATIONS, new CrossoverManager(),
new PopulationGenerator()).SetCustomChromosomeEvaluator(new ChromosomeEvaluator())
.SetEnvironment(new MyEnvironment()).SetMutationProbability(0.01);
searchRunner1.SetEngineBuilder(engineBuidler);
}
public void RequestedChromosomesIsRightWithElite(double elite)
{
var searchEngine =
new GeneticSearchEngineBuilder(POPULATION_SIZE, 50, crossoverManager, populationGenerator)
.SetElitePercentage(elite)
.SetSelectionStrategy(new AssertRequestedChromosomesIsRightSelectionWrapper()).Build();
searchEngine.Next();
}
public void SetEngineBuilder(GeneticSearchEngineBuilder engineBuilder)
{
this.engineBuilder = engineBuilder;
lock (shouldPauseLock)
shouldPause = true;
Thread.Sleep(200); // Give some time for the search to stop
InitializeEngine();
SetButtonsState(EngineState.Puased);
}
public void BasicTest(RunType runType)
{
var searchEngine =
new GeneticSearchEngineBuilder(POPULATION_SIZE, 50, crossoverManager, populationGenerator)
.SetSelectionStrategy(new AssertRequestedChromosomesIsRightSelectionWrapper()).Build();
var result = searchEngine.Run(runType);
Assert.AreEqual(VECTOR_SIZE, result.BestChromosome.Evaluate());
Assert.AreEqual(50, result.Generations, "Wrong number of generations");
}
public void MutationTest(RunType runType)
{
var searchEngine =
new GeneticSearchEngineBuilder(POPULATION_SIZE, 50, crossoverManager, populationGenerator)
.SetSelectionStrategy(new AssertRequestedChromosomesIsRightSelectionWrapper())
.SetMutationProbability(0.1).IncludeAllHistory().Build();
var result = searchEngine.Run(runType);
Assert.IsTrue(VECTOR_SIZE < result.BestChromosome.Evaluate(),
$"best result ({result.BestChromosome.Evaluate()}) should have been greater than {VECTOR_SIZE}. Chromosome is {result.BestChromosome}");
}
public void Banchmark()
{
var crossoverManager = A.Fake <ICrossoverManager>();
A.CallTo(() => crossoverManager.Crossover(A <IChromosome> ._, A <IChromosome> ._))
.ReturnsLazily(delegate(IChromosome c1, IChromosome c2) { Thread.Sleep(SLEEP_TIME); return(c1); });
var engine = new GeneticSearchEngineBuilder(POPULATION_SIZE, MAX_GENERATIONS, crossoverManager,
new SlowPopulationGenerator(SLEEP_TIME)).Build();
var result = engine.Run();
Console.WriteLine("Total time: " + result.SearchTime);
}
private void InitializeEngine()
{
var mutationManager = new IntUniformMutationManager(0, 100);
var evaluator = new BasicEvaluator();
var populationGenerator =
new IntVectorChromosomePopulationGenerator(VECTOR_SIZE, 0, 1, mutationManager, evaluator);
var crossoverManager = new SinglePointCrossoverManager <int>(mutationManager, evaluator);
var engineBuilder =
new GeneticSearchEngineBuilder(POPULATION_SIZE, GENERATION, crossoverManager, populationGenerator)
.SetMutationProbability(MutationInputBox.GetValue).SetElitePercentage(ElitismInputBox.GetValue);
searchRunner1.SetEngineBuilder(engineBuilder);
}
public void NagitiveEvaluation_ThrowException()
{
try
{
var chromosme = A.Fake <IChromosome>();
A.CallTo(() => chromosme.Evaluate()).Returns(-1);
var populationGenerator = A.Fake <IPopulationGenerator>();
A.CallTo(() => populationGenerator.GeneratePopulation(A <int> ._))
.Returns(new[] { chromosme });
var engine = new GeneticSearchEngineBuilder(1, 2, A.Fake <ICrossoverManager>(), populationGenerator)
.Build();
engine.Run();
Assert.Fail("Should have thrown an exception by now");
}
catch (AggregateException e)
{
Assert.AreEqual(typeof(NegativeEvaluationException), e.InnerExceptions.First().GetType());
}
}
public void BedPopulationRenewalPercantage_ThrowException(double percantage)
{
var chromosme = A.Fake <IChromosome>();
A.CallTo(() => chromosme.Evaluate()).Returns(1);
var populationGenerator = A.Fake <IPopulationGenerator>();
A.CallTo(() => populationGenerator.GeneratePopulation(A <int> ._))
.Returns(new[] { chromosme });
var populationRenewalManager = A.Fake <IPopulationRenwalManager>();
A.CallTo(() => populationRenewalManager.ShouldRenew(A <Population> ._, A <IEnvironment> ._, A <int> ._))
.Returns(percantage);
var engine =
new GeneticSearchEngineBuilder(1, 2, A.Fake <ICrossoverManager>(), populationGenerator)
.AddPopulationRenwalManager(populationRenewalManager)
.Build();
engine.Run();
Assert.Fail("Should have thrown an exception by now");
}
static void Main(string[] args)
{
Console.WriteLine("Started!");
IMutationManager <string> mutationManager = new ExchangeMutationManager <string>();
IEvaluator evaluator = new DistanceEvaluator(locations);
ICrossoverManager crossoverManager = new OrderCrossover <string>(mutationManager, evaluator);
IPopulationGenerator populationGenerator =
new AllElementsVectorChromosomePopulationGenerator <string>(cities, mutationManager, evaluator);
GeneticSearchEngine engine =
new GeneticSearchEngineBuilder(POPULATION_SIZE, GENERATIONS, crossoverManager, populationGenerator)
.SetMutationProbability(0.1).SetElitePercentage(0.02).Build();
engine.OnNewGeneration += (Population p, IEnvironment e) => PrintBestChromosome(p);
GeneticSearchResult result = engine.Run();
Console.WriteLine("Finished!");
Console.WriteLine(result.BestChromosome + ": " + distanceCalclator.GetDistance(result.BestChromosome));
Console.ReadLine();
}
