public MyDNA <T> Crossover(MyDNA <T> otherParent)
{
MyDNA <T> child = new MyDNA <T>(Genes.Length, random, getRandomGene, fitnessFunction, shouldInitGenes: false);
for (int i = 0; i < Genes.Length; i++)
{
child.Genes[i] = random.NextDouble() < 0.5 ? Genes[i] : otherParent.Genes[i];
}
return(child);
}
public int CompareDNA(MyDNA <T> a, MyDNA <T> b)
{
if (a.Fitness > b.Fitness)
{
return(-1);
}
else if (a.Fitness < b.Fitness)
{
return(1);
}
else
{
return(0);
}
}
public void CalculateFitness()
{
fitnessSum = 0;
MyDNA <T> best = Population[0];
for (int i = 0; i < Population.Count; i++)
{
fitnessSum += Population[i].CalculateFitness(i);
if (Population[i].Fitness > best.Fitness)
{
best = Population[i];
}
}
BestFitness = best.Fitness;
best.Genes.CopyTo(BestGenes, 0);
}
public void NewGeneration()
{
if (Population.Count <= 0)
{
return;
}
CalculateFitness();
Population.Sort(CompareDNA);
newPopulation.Clear();
for (int i = 0; i < Population.Count; i++)
{
if (i < Elitism)
{
newPopulation.Add(Population[i]);
}
else
{
MyDNA <T> parent1 = ChooseParent();
MyDNA <T> parent2 = ChooseParent();
MyDNA <T> child = parent1.Crossover(parent2);
child.Mutate(MutationRate);
newPopulation.Add(child);
}
}
List <MyDNA <T> > tempList = Population;
Population = newPopulation;
newPopulation = tempList;
Generation++;
}