public void NewGeneration()
{
if (!Population.Any())
{
return;
}
CalculateFitness();
var newPopulation = new List <Dna <T> >();
for (int i = 0; i < Population.Count; i++)
{
Dna <T> parent1 = ChooseParent();
Dna <T> parent2 = ChooseParent();
Dna <T> child = parent1.Crossover(parent2);
child.Mutate(MutationRate);
newPopulation.Add(child);
}
Population = newPopulation;
Generation++;
}
public Dna <T> Crossover(Dna <T> otherParent)
{
var child = new Dna <T>(Genes.Length, _getRandomGene, _fitnessFunction, false);
for (int i = 0; i < Genes.Length; i++)
{
child.Genes[i] = rnd.NextDouble() < 0.5 ? Genes[i] : otherParent.Genes[i];
}
return(child);
}
private void CalculateFitness()
{
_fitnessSum = 0;
Dna <T> best = Population[0];
Population.ForEach(p =>
{
_fitnessSum += p.CalculateFitness(Population.IndexOf(p));
best = best.Fitness < p.Fitness ? p : best;
});
BestFitness = best.Fitness;
best.Genes.CopyTo(BestGenes, 0);
}