/// <summary>
/// Recombine the genotypes in intermediate population, producing a new population. The recombination
/// between two genotypes is made by <see cref="CompleteCrossover"/>. At the end a new population of
/// size newPopulationSize is created. A number of genotypes, given by the parameter survivalGenotype
/// are directly passed to the new generation. <br/><br/>
/// Note, the intermediatePopulation and the current population have to be ordered in descending order by fitness.
/// </summary>
/// <param name="intermediatePopulation">The intermediate population</param>
/// <param name="newPopulationSize">The size of the new population</param>
/// <param name="survivalGenotype">The number of genotypes to be passed directly in the
/// next generation</param>
/// <returns></returns>
private List <Genotype> Recombination(List <Genotype> intermediatePopulation, int newPopulationSize, int survivalGenotype)
{
if (intermediatePopulation.Count < 2)
{
throw new ArgumentException("The intermediate population has to be at least of size 2");
}
List <Genotype> newPopulation = new List <Genotype>();
for (int i = 0; i < survivalGenotype; i++)
{
newPopulation.Add(this._currentPopulation[i]);
}
while (newPopulation.Count < newPopulationSize)
{
int randomIndex1 = randomizer.Next(0, intermediatePopulation.Count), randomIndex2;
do
{
randomIndex2 = randomizer.Next(0, intermediatePopulation.Count);
} while (randomIndex1 == randomIndex2);
Genotype offspring1, offspring2;
GeneticAlgorithm.CompleteCrossover(intermediatePopulation[randomIndex1], intermediatePopulation[randomIndex2], out offspring1, out offspring2);
newPopulation.Add(offspring1);
if (newPopulation.Count < newPopulationSize)
{
newPopulation.Add(offspring2);
}
}
return(newPopulation);
}
private List <Genotype> RandomRecombination(List <Genotype> intermediatePopulation, uint newPopulationSize)
{
if (intermediatePopulation.Count < 2)
{
throw new System.ArgumentException("The intermediate population has to be at least of size 2 for this operator.");
}
List <Genotype> newPopulation = new List <Genotype>();
newPopulation.Add(intermediatePopulation[0]);
newPopulation.Add(intermediatePopulation[1]);
while (newPopulation.Count < newPopulationSize)
{
int randomIndex1 = randomizer.Next(0, intermediatePopulation.Count), randomIndex2;
do
{
randomIndex2 = randomizer.Next(0, intermediatePopulation.Count);
} while (randomIndex2 == randomIndex1);
Genotype offspring1, offspring2;
GeneticAlgorithm.CompleteCrossover(intermediatePopulation[randomIndex1], intermediatePopulation[randomIndex2],
GeneticAlgorithm.DefCrossSwapProb, out offspring1, out offspring2);
newPopulation.Add(offspring1);
if (newPopulation.Count < newPopulationSize)
{
newPopulation.Add(offspring2);
}
}
return(newPopulation);
}
// Recombination operator for the genetic algorithm, recombining random genotypes of the intermediate population
private List <Genotype> RandomRecombination(List <Genotype> intermediatePopulation, uint newPopulationSize)
{
//Check arguments
if (intermediatePopulation.Count < 2)
{
throw new System.ArgumentException("The intermediate population has to be at least of size 2 for this operator.");
}
List <Genotype> newPopulation = new List <Genotype>();
//Always add atlist best two (unmodified)
for (int i = 0; i < GameData.instance.BreadAmountToSaveFromSelection; i++)
{
newPopulation.Add(intermediatePopulation[i]);
}
while (newPopulation.Count < newPopulationSize)
{
//Get two random indices that are not the same
int randomIndex1 = randomizer.Next(0, intermediatePopulation.Count), randomIndex2;
do
{
randomIndex2 = randomizer.Next(0, intermediatePopulation.Count);
} while (randomIndex2 == randomIndex1);
Genotype offspring1, offspring2;
GeneticAlgorithm.CompleteCrossover(intermediatePopulation[randomIndex1], intermediatePopulation[randomIndex2],
GameData.instance.SwapProb, out offspring1, out offspring2);
newPopulation.Add(offspring1);
if (newPopulation.Count < newPopulationSize)
{
newPopulation.Add(offspring2);
}
}
return(newPopulation);
}
// Recombination operator for the genetic algorithm, recombining random genotypes of the intermediate population
private List <Genotype> RandomRecombination(List <Genotype> intermediatePopulation, uint newPopulationSize)
{
//Check arguments
if (intermediatePopulation.Count < 2)
{
throw new System.ArgumentException("The intermediate population has to be at least of size 2 for this operator.");
}
List <Genotype> newPopulation = new List <Genotype>();
//Always add best two (unmodified)
newPopulation.Add(intermediatePopulation[0]);
newPopulation.Add(intermediatePopulation[1]);
while (newPopulation.Count < newPopulationSize)
{
//Get two random indices that are not the same
int randomIndex1 = randomizer.Next(0, intermediatePopulation.Count), randomIndex2;
do
{
randomIndex2 = randomizer.Next(0, intermediatePopulation.Count);
} while (randomIndex2 == randomIndex1);
Genotype offspring1, offspring2;
GeneticAlgorithm.CompleteCrossover(intermediatePopulation[randomIndex1], intermediatePopulation[randomIndex2],
GameStateManager.Instance.appSettings.defCrossSwapProb, out offspring1, out offspring2);
newPopulation.Add(offspring1);
if (newPopulation.Count < newPopulationSize)
{
newPopulation.Add(offspring2);
}
}
return(newPopulation);
}
