public IntDNA MutateBestOnly(IntDNA father)
{
var child = father.Fitness > Fitness ? father : this;
//child.Mutate();
child.GoodMutation();
return(child);
}
public IntDNA CrossOverTilde(IntDNA father)
{
//return (new DNA(father.Gene ^ Gene));
var child = new IntDNA(father.Gene ^ Gene);
child.Mutate();
return(child);
}
public static IntDNA[] DnaInitialize(int size = 20)
{
//var rng = new Random();
var dnalist = new IntDNA[size];
for (var i = 0; i < size; i++)
{
dnalist[i] = new IntDNA(Rng.Next(0, 65536));
}
return(dnalist);
}
internal IntDNA CrossOverAnd(IntDNA father)
{
//var sumfitness = father.Fitness + Fitness;
//var fatherfitness = father.Fitness / sumfitness;
//var motherfitness =
//return(new DNA(father.Gene & Gene));
var child = new IntDNA(father.Gene & Gene);
child.Mutate();
return(child);
}
public static void IntDna()
{
var bestgene = 0;
var bestfitness = 0;
var bestgeneration = 0;
const int size = 100;
const int generations = 2000000;
var dnaarray = IntDNA.DnaInitialize(size);
for (var generation = 0; generation < generations; generation++)
{
//foreach (var dna in dnaarray)
var generation1 = generation;
Parallel.ForEach(dnaarray, dna =>
{
dna.CalculateFitness();
if (bestfitness >= dna.Fitness)
{
return;
}
bestfitness = dna.Fitness;
bestgene = dna.Gene;
bestgeneration = generation1;
Console.WriteLine("Fitness: " + bestfitness + " gene: " + bestgene + " generation: " +
bestgeneration);
});
var sorteddnalist = dnaarray.OrderByDescending(dna => dna.Fitness).ToList();
for (var i = 0; i < sorteddnalist.Count - 1; i += 2)
{
dnaarray[i] = sorteddnalist[i].MutateBestOnly(sorteddnalist[i + 1]);
}
//Console.WriteLine(generation);
}
Console.WriteLine("Fitness: " + bestfitness + " gene: " + bestgene + " generation: " + bestgeneration);
Console.WriteLine("Fitness: " + Convert.ToString(bestfitness, 2) +
" gene: " + Convert.ToString(bestgene, 2) +
" generation: " + Convert.ToString(bestgeneration, 2));
}
