//public static Individual recombine(Individual parent1, Individual parent2)
//{
// //vermeiden, dass niedrigstes oder höchstes Gen gewählt wird, weil sonst Klon eines Elternteils entsteht
// int selectedGenPosition = GlobalSettings.random.Next(GlobalSettings.NumberOfGenes-1) + 1;
// Individual child = new Individual();
// if (selectedGenPosition > 0)
// {
// child.gens.RemoveRange(0, selectedGenPosition);
// child.gens.InsertRange(0, parent1.gens.GetRange(0, selectedGenPosition));
// }
// child.gens[selectedGenPosition].recombine(parent1.gens[selectedGenPosition], parent2.gens[selectedGenPosition]);
// if (selectedGenPosition < parent2.gens.Count - 1 )
// {
// child.gens.RemoveRange(selectedGenPosition + 1, parent2.gens.Count - 1 - selectedGenPosition);
// child.gens.InsertRange(selectedGenPosition + 1, parent2.gens.GetRange(selectedGenPosition + 1, parent2.gens.Count - 1 - selectedGenPosition));
// }
// return child;
//}
public static Individual recombine(Individual parent1, Individual parent2)
{
//vermeiden, dass niedrigstes oder höchstes Gen gewählt wird, weil sonst Klon eines Elternteils entsteht
int selectedGenPosition = GlobalSettings.random.Next(GlobalSettings.NumberOfGenes * BinaryGene.Size - 2) + 1;
int sliceGeneNumber = selectedGenPosition / BinaryGene.Size;
Individual child = new Individual();
child.gens.Clear();
if (sliceGeneNumber > 0)
{
for (int i = 0; i < sliceGeneNumber; i++)
{
child.gens.Add((parent1.gens[i] as BinaryGene).Clone() as BinaryGene);
}
}
child.gens.Add(new BinaryGene(parent1.gens[sliceGeneNumber], parent2.gens[sliceGeneNumber], selectedGenPosition % BinaryGene.Size));
if (sliceGeneNumber < parent2.gens.Count - 1)
{
for (int i = child.gens.Count; i < GlobalSettings.NumberOfGenes; i++)
{
child.gens.Add((parent2.gens[i] as BinaryGene).Clone() as BinaryGene);
}
}
return child;
}
public abstract double calculateFitness(Individual ind);