public void NewGeneration()
{
if (CurrentGeneration.Count <= 0)
{
return;
}
newGeneration = new List <Specimen>();
oldGeneration = new List <Specimen>();
List <Specimen> bestOfTheBest = new List <Specimen>();
allGenerations.Add(CurrentGeneration);
for (int i = 0; i < CurrentGeneration.Count; i++)
{
for (int j = 0; j < CurrentGeneration.Count; j++)
{
if (i == j)
{
j++;
}
if (j == CurrentGeneration.Count)
{
break;
}
var firstParent = CurrentGeneration[i];
var secondParent = CurrentGeneration[j];
var child = firstParent.CrossoverWith(secondParent);
if (RandomForGA.Generator.NextDouble() < Parameters.MutationRate)
{
child.Mutate(Parameters.MutationAmplitude);
}
newGeneration.Add(child);
}
}
for (int i = 0; i < CurrentGeneration.Count; i++)
{
oldGeneration.Add(CurrentGeneration[i]);
}
CurrentGeneration.Clear();
for (int i = 0; i < oldGeneration.Count; i++)
{
CurrentGeneration.Add(oldGeneration[i]);
}
for (int i = 0; i < newGeneration.Count; i++)
{
CurrentGeneration.Add(newGeneration[i]);
}
CalculateFitness();
CurrentGeneration.Sort((a, b) => population.FittingFunction(a).CompareTo(population.FittingFunction(b)));
for (int i = 0; i < Parameters.PopulationSize; i++)
{
bestOfTheBest.Add(CurrentGeneration[i]);
}
CurrentGeneration = bestOfTheBest;
GenerationNum++;
}