/// <summary>
/// Create a population of a set number of genes, with a crossover type, and the ideal path ends
/// </summary>
/// <param name="numberOfGenomes"></param>
/// <param name="crossOver"></param>
/// <param name="originPosition"></param>
/// <param name="destinationPosition"></param>
public Population(int numberOfGenomes, CrossOver crossOver, Coordinate originPosition, Coordinate destinationPosition, float mutationStrength)
{
NumberOfGenomes = numberOfGenomes;
CrossOver = crossOver;
OriginPosition = originPosition;
DestinationPosition = destinationPosition;
MutationStrength = (int)(mutationStrength * 100);
for (int i = 0; i < NumberOfGenomes; i++)
{
Genomes.Add(new Genome(OriginPosition));
}
}
/// <summary>
/// Crossover all pairs of genomes
/// </summary>
/// <param name="parentGenomes"></param>
/// <returns></returns>
private List <Genome> GetCrossOverGenomes(List <Genome> parentGenomes, int requiredChildren)
{
List <Genome> offspring = new List <Genome>();
while (offspring.Count < requiredChildren)
{
Genome parent1 = parentGenomes[StaticUtils.Random.Next(parentGenomes.Count - 1)];
Genome parent2 = parentGenomes[StaticUtils.Random.Next(parentGenomes.Count - 1)];
offspring.Add(CrossOver.CrossOverGenomes(parent1, parent2, OriginPosition));
}
return(offspring);
}
/// <summary>
/// Create new algorithm instance and initial population
/// </summary>
/// <param name="numberOfGenomes"></param>
/// <param name="iterationsPerGeneration"></param>
/// <param name="originPosition"></param>
/// <param name="destinationPosition"></param>
public GeneticAlgorithm(int numberOfGenomes, int iterationsPerGeneration, Coordinate originPosition, Coordinate destinationPosition, float mutationStrength, CrossOver.CrossOverType crossOverType) //fitness threshold? percentage of fit individuals?
{
NumberOfGenomes = numberOfGenomes;
OriginPosition = originPosition;
InitialDestinationPosition = new Coordinate(destinationPosition);
DestinationPosition = destinationPosition;
MutationStrength = mutationStrength;
IterationsPerGeneration = iterationsPerGeneration;
CrossOver = CrossOver.GetCrossOver(crossOverType);
BeginNewPopulation();
//add mutation strength?
}
