public override void CopyGeneInfo(Genome dest)
{
MastermindGenome theGene = (MastermindGenome)dest;
theGene.Length = Length;
theGene.TheMin = TheMin;
theGene.TheMax = TheMax;
}
public MasterMindPopulation(int numberOfGenomes)
{
Genomes.Clear();
for (int i = 0; i < numberOfGenomes; i++)
{
MastermindGenome aGenome = new MastermindGenome(kLength, 1, 9);
aGenome.SetCrossoverPoint(kCrossover);
aGenome.CalculateFitness();
Genomes.Add(aGenome);
}
}
public override Genome Crossover(Genome g)
{
MastermindGenome aGene1 = new MastermindGenome();
MastermindGenome aGene2 = new MastermindGenome();
g.CopyGeneInfo(aGene1);
g.CopyGeneInfo(aGene2);
MastermindGenome CrossingGene = (MastermindGenome)g;
for (int i = 0; i < CrossoverPoint; i++)
{
aGene1.TheArray.Add(CrossingGene.TheArray[i]);
aGene2.TheArray.Add(TheArray[i]);
}
for (int j = CrossoverPoint; j < Length; j++)
{
aGene1.TheArray.Add(TheArray[j]);
aGene2.TheArray.Add(CrossingGene.TheArray[j]);
}
// 50/50 chance of returning gene1 or gene2
MastermindGenome aGene = null;
if (TheSeed.Next(2) == 1)
{
aGene = aGene1;
}
else
{
aGene = aGene2;
}
return(aGene);
}
public void DoCrossover(ArrayList genes)
{
ArrayList GeneMoms = new ArrayList();
ArrayList GeneDads = new ArrayList();
for (int i = 0; i < genes.Count; i++)
{
// randomly pick the moms and dad's
if (MastermindGenome.TheSeed.Next(100) % 2 > 0)
{
GeneMoms.Add(genes[i]);
}
else
{
GeneDads.Add(genes[i]);
}
}
// now make them equal
if (GeneMoms.Count > GeneDads.Count)
{
while (GeneMoms.Count > GeneDads.Count)
{
GeneDads.Add(GeneMoms[GeneMoms.Count - 1]);
GeneMoms.RemoveAt(GeneMoms.Count - 1);
}
if (GeneDads.Count > GeneMoms.Count)
{
GeneDads.RemoveAt(GeneDads.Count - 1); // make sure they are equal
}
}
else
{
while (GeneDads.Count > GeneMoms.Count)
{
GeneMoms.Add(GeneDads[GeneDads.Count - 1]);
GeneDads.RemoveAt(GeneDads.Count - 1);
}
if (GeneMoms.Count > GeneDads.Count)
{
GeneMoms.RemoveAt(GeneMoms.Count - 1); // make sure they are equal
}
}
// now cross them over and add them according to fitness
for (int i = 0; i < GeneDads.Count; i++)
{
// pick best 2 from parent and children
MastermindGenome babyGene1 = (MastermindGenome)((MastermindGenome)GeneDads[i]).Crossover((MastermindGenome)GeneMoms[i]);
MastermindGenome babyGene2 = (MastermindGenome)((MastermindGenome)GeneMoms[i]).Crossover((MastermindGenome)GeneDads[i]);
GenomeFamily.Clear();
GenomeFamily.Add(GeneDads[i]);
GenomeFamily.Add(GeneMoms[i]);
GenomeFamily.Add(babyGene1);
GenomeFamily.Add(babyGene2);
CalculateFitnessForAll(GenomeFamily);
GenomeFamily.Sort();
if (Best2 == true)
{
// if Best2 is true, add top fitness genes
GenomeResults.Add(GenomeFamily[0]);
GenomeResults.Add(GenomeFamily[1]);
}
else
{
GenomeResults.Add(babyGene1);
GenomeResults.Add(babyGene2);
}
}
}
