public void Mate(int N_bests = 5)
{
List <Individual> to_mate = new List <Individual>(fixed_amount);
for (int i = 0; i < N_bests; i++)
{
to_mate.Add(individuals[i]);
}
for (int i = 0; i < fixed_amount - N_bests; i++)
{
int first_competitor = _src.random_generator.Next(N_bests + 1, fixed_amount),
second_competitor = _src.random_generator.Next(N_bests + 1, fixed_amount);
Individual winner = individuals[first_competitor].Value < individuals[second_competitor].Value ? individuals[second_competitor] : individuals[first_competitor];
to_mate.Add(winner);
}
for (int i = 0; i < to_mate.Count; i++)
{
Individual parrent1 = to_mate[i],
parrent2 = to_mate[_src.random_generator.Next(0, to_mate.Count)];
Individual offspring = OX_crossover(parrent1, parrent2);
double mutationRate = Individual.Common(parrent1, parrent2);
if (mutationRate > 0.1)
{
if (mutationRate > 0.6)
{
if (_src.random_generator.Next(0, 100) > 70)
{
int start = _src.random_generator.Next(2, offspring.Chromos.Count - 2);
int count = _src.random_generator.Next(1, Convert.ToInt32((offspring.Chromos.Count - 1 - start) * (mutationRate)));
offspring.ReverseMutation(start, count);
}
if (_src.random_generator.Next(0, 100) < mutationRate * 100)
{
for (int j = 0; j < Convert.ToInt32(mutationRate * 3.3); j++)
{
int value = _src.random_generator.Next(1, _src.numberOfVertices);
int position = _src.random_generator.Next(1, _src.numberOfVertices);
offspring.InsertMutation(position, value);
}
}
}
else
{
offspring.SwapMutation(_src.random_generator.Next(2, offspring.Chromos.Count - 2), _src.random_generator.Next(2, offspring.Chromos.Count - 2));
}
}
individuals.Add(offspring);
}
Sort_invididuals();
}