public void UniformSelectionOperator_Select()
{
MockGeneticAlgorithm algorithm = new MockGeneticAlgorithm
{
FitnessEvaluator = new MockFitnessEvaluator(),
GeneticEntitySeed = new MockEntity(),
PopulationSeed = new SimplePopulation(),
SelectionOperator = new UniformSelectionOperator
{
SelectionBasedOnFitnessType = FitnessType.Scaled
}
};
UniformSelectionOperator op = new UniformSelectionOperator();
op.Initialize(algorithm);
SimplePopulation population = new SimplePopulation();
population.Initialize(algorithm);
for (int i = 0; i < 4; i++)
{
MockEntity entity = new MockEntity();
entity.Initialize(algorithm);
population.Entities.Add(entity);
}
TestRandomUtil randomUtil = new TestRandomUtil();
RandomNumberService.Instance = randomUtil;
randomUtil.Value = 3;
IList <GeneticEntity> selectedEntities = op.SelectEntities(1, population);
Assert.Same(population.Entities[randomUtil.Value], selectedEntities[0]);
randomUtil.Value = 2;
selectedEntities = op.SelectEntities(1, population);
Assert.Same(population.Entities[randomUtil.Value], selectedEntities[0]);
randomUtil.Value = 1;
selectedEntities = op.SelectEntities(1, population);
Assert.Same(population.Entities[randomUtil.Value], selectedEntities[0]);
randomUtil.Value = 0;
selectedEntities = op.SelectEntities(1, population);
Assert.Same(population.Entities[randomUtil.Value], selectedEntities[0]);
}
public void RouletteWheelSampler_GetEntity_NoSizes()
{
MockGeneticAlgorithm algorithm = new MockGeneticAlgorithm
{
GeneticEntitySeed = new MockEntity(),
SelectionOperator = new MockSelectionOperator(),
FitnessEvaluator = new MockFitnessEvaluator(),
PopulationSeed = new MockPopulation()
};
List <WheelSlice> slices = new List <WheelSlice>();
MockEntity entity1 = new MockEntity();
entity1.Initialize(algorithm);
MockEntity entity2 = new MockEntity();
entity2.Initialize(algorithm);
MockEntity entity3 = new MockEntity();
entity3.Initialize(algorithm);
MockEntity entity4 = new MockEntity();
entity4.Initialize(algorithm);
slices.Add(new WheelSlice(entity1, 0));
slices.Add(new WheelSlice(entity2, 0));
slices.Add(new WheelSlice(entity3, 0));
slices.Add(new WheelSlice(entity4, 0));
TestRandomUtil randomUtil = new TestRandomUtil();
RandomNumberService.Instance = randomUtil;
randomUtil.RandomValue = 2;
GeneticEntity sampledEntity = RouletteWheelSampler.GetEntity(slices);
Assert.Equal(4, randomUtil.MaxValuePassed);
Assert.Same(entity3, sampledEntity);
}
public void RouletteWheelSampler_GetEntity()
{
MockGeneticAlgorithm algorithm = new MockGeneticAlgorithm
{
GeneticEntitySeed = new MockEntity(),
SelectionOperator = new MockSelectionOperator(),
FitnessEvaluator = new MockFitnessEvaluator(),
PopulationSeed = new MockPopulation()
};
List <WheelSlice> slices = new List <WheelSlice>();
MockEntity entity1 = new MockEntity();
entity1.Initialize(algorithm);
MockEntity entity2 = new MockEntity();
entity2.Initialize(algorithm);
MockEntity entity3 = new MockEntity();
entity3.Initialize(algorithm);
MockEntity entity4 = new MockEntity();
entity4.Initialize(algorithm);
slices.Add(new WheelSlice(entity1, 4));
slices.Add(new WheelSlice(entity2, 2));
slices.Add(new WheelSlice(entity3, 1));
slices.Add(new WheelSlice(entity4, 3));
TestRandomUtil randomUtil = new TestRandomUtil();
RandomNumberService.Instance = randomUtil;
randomUtil.Ratio = 0;
GeneticEntity sampledEntity = RouletteWheelSampler.GetEntity(slices);
Assert.Same(entity1, sampledEntity);
randomUtil.Ratio = .39999;
sampledEntity = RouletteWheelSampler.GetEntity(slices);
Assert.Same(entity1, sampledEntity);
randomUtil.Ratio = .4;
sampledEntity = RouletteWheelSampler.GetEntity(slices);
Assert.Same(entity2, sampledEntity);
randomUtil.Ratio = .59999;
sampledEntity = RouletteWheelSampler.GetEntity(slices);
Assert.Same(entity2, sampledEntity);
randomUtil.Ratio = .6;
sampledEntity = RouletteWheelSampler.GetEntity(slices);
Assert.Same(entity3, sampledEntity);
randomUtil.Ratio = .69999;
sampledEntity = RouletteWheelSampler.GetEntity(slices);
Assert.Same(entity3, sampledEntity);
randomUtil.Ratio = .7;
sampledEntity = RouletteWheelSampler.GetEntity(slices);
Assert.Same(entity4, sampledEntity);
randomUtil.Ratio = 1;
sampledEntity = RouletteWheelSampler.GetEntity(slices);
Assert.Same(entity4, sampledEntity);
}
public void RankSelectionOperator_Select()
{
GeneticAlgorithm algorithm = GetAlgorithm();
RankSelectionOperator op = new RankSelectionOperator();
op.Initialize(algorithm);
SimplePopulation population = new SimplePopulation();
population.Initialize(algorithm);
MockEntity entity1 = new MockEntity();
entity1.Initialize(algorithm);
MockEntity entity2 = new MockEntity();
entity2.Initialize(algorithm);
MockEntity entity3 = new MockEntity();
entity3.Initialize(algorithm);
MockEntity entity4 = new MockEntity();
entity4.Initialize(algorithm);
entity1.ScaledFitnessValue = 0;
entity2.ScaledFitnessValue = 50;
entity3.ScaledFitnessValue = 23;
entity4.ScaledFitnessValue = 25;
population.Entities.Add(entity1);
population.Entities.Add(entity2);
population.Entities.Add(entity3);
population.Entities.Add(entity4);
TestRandomUtil randomUtil = new TestRandomUtil();
RandomNumberService.Instance = randomUtil;
randomUtil.Ratio = 0;
IList <GeneticEntity> selectedEntities = op.SelectEntities(1, population).ToList();
Assert.Same(entity1, selectedEntities[0]);
randomUtil.Ratio = .099999;
selectedEntities = op.SelectEntities(1, population);
Assert.Same(entity1, selectedEntities[0]);
randomUtil.Ratio = .1;
selectedEntities = op.SelectEntities(1, population);
Assert.Same(entity3, selectedEntities[0]);
randomUtil.Ratio = .299999;
selectedEntities = op.SelectEntities(1, population);
Assert.Same(entity3, selectedEntities[0]);
randomUtil.Ratio = .3;
selectedEntities = op.SelectEntities(1, population);
Assert.Same(entity4, selectedEntities[0]);
randomUtil.Ratio = .599999;
selectedEntities = op.SelectEntities(1, population);
Assert.Same(entity4, selectedEntities[0]);
randomUtil.Ratio = .6;
selectedEntities = op.SelectEntities(1, population);
Assert.Same(entity2, selectedEntities[0]);
randomUtil.Ratio = 1;
selectedEntities = op.SelectEntities(1, population);
Assert.Same(entity2, selectedEntities[0]);
}
public void SinglePointCrossoverOperator_GenerateCrossover_DifferentLength()
{
MockGeneticAlgorithm algorithm = new MockGeneticAlgorithm
{
PopulationSeed = new MockPopulation(),
SelectionOperator = new MockSelectionOperator(),
FitnessEvaluator = new MockFitnessEvaluator(),
CrossoverOperator = new SinglePointCrossoverOperator
{
CrossoverRate = 1
},
GeneticEntitySeed = new BinaryStringEntity
{
MinimumStartingLength = 4,
MaximumStartingLength = 4
}
};
algorithm.GeneticEntitySeed.Initialize(algorithm);
SinglePointCrossoverOperator op = new SinglePointCrossoverOperator {
CrossoverRate = 1
};
op.Initialize(algorithm);
BinaryStringEntity entity1 = (BinaryStringEntity)algorithm.GeneticEntitySeed.CreateNewAndInitialize();
entity1.Length = 5;
entity1[0] = true;
entity1[1] = false;
entity1[2] = false;
entity1[3] = true;
entity1[4] = true;
BinaryStringEntity entity2 = (BinaryStringEntity)algorithm.GeneticEntitySeed.CreateNewAndInitialize();
entity2.Initialize(algorithm);
entity2[0] = true;
entity2[1] = true;
entity2[2] = false;
entity2[3] = false;
TestRandomUtil randomUtil = new TestRandomUtil();
RandomNumberService.Instance = randomUtil;
randomUtil.RandomVal = 1;
IList <GeneticEntity> result = op.Crossover(new GeneticEntity[] { entity1, entity2 }).ToList();
BinaryStringEntity resultEntity1 = (BinaryStringEntity)result[0];
BinaryStringEntity resultEntity2 = (BinaryStringEntity)result[1];
Assert.Equal("1100", resultEntity1.Representation);
Assert.Equal("10011", resultEntity2.Representation);
randomUtil.RandomVal = 3;
result = op.Crossover(new GeneticEntity[] { entity1, entity2 }).ToList();
resultEntity1 = (BinaryStringEntity)result[0];
resultEntity2 = (BinaryStringEntity)result[1];
Assert.Equal("1000", resultEntity1.Representation);
Assert.Equal("11011", resultEntity2.Representation);
}
