public void createOffspring(Random rng, Function f, CrossOver cs)
{
scramble();
int popSize = pop.Count;
for (int i = 0; i < popSize; i = i + 2)
{
GenoType p1 = pop[i];
GenoType p2 = pop[i + 1];
Tuple <BitArray, BitArray> childrenTuple = cs.Cut(p1.Bits, p2.Bits, rng);
GenoType c1 = new GenoType(rng, childrenTuple.Item1);
GenoType c2 = new GenoType(rng, childrenTuple.Item2);
//Console.WriteLine("---------------------------------------");
//Console.WriteLine("parent1: {0}", p1.print());
//Console.WriteLine("parent2: {0}", p2.print());
//Console.WriteLine("child1: {0}", c1.print());
//Console.WriteLine("child2: {0}", c2.print());
//Console.ReadLine();
//aan dezelfde lijst toevoegen # gevaarlijk zeg jeez
pop.Add(c1);
pop.Add(c2);
}
//yolo hackaton ez
pop = pop.OrderByDescending(x => f.Evaluate(x.Bits)).Take(popSize).ToList();
////dit is voor mijzelf dit is inefficient
//double weightPopulation = 0;
//pop.ForEach(x => weightPopulation += f.Evaluate(x.Bits));
//Console.WriteLine(weightPopulation);
}
List <GenoType> initPop(int n)
{
List <GenoType> pop = new List <GenoType>();
for (int i = 0; i < n; i++)
{
GenoType geno = new GenoType(rng);
pop.Add(geno);
}
return(pop);
}
private bool sameGeno(GenoType genoType1, GenoType genoType2)
{
bool equal = true;
int i = 0;
while (equal && i < genoType1.Bits.Count)
{
equal = genoType1.Bits[i] == genoType2.Bits[i];
i++;
}
return(equal);
}