private List <PopulationMember> addCrossoverMembers(List <PopulationMember> newPop, int numberToAdd)
{
//Console.WriteLine ("Beginning Crossover");
// The fittest members have are more likely to be crossed (likelihood is proportional to their fitness)
List <int> probabilityArray = new List <int> ();
//Console.WriteLine ("Caluclating Probability Array...");
for (int x = 0; x < newPop.Count; x++)
{
for (int i = 0; i < newPop[x].lastFitness; i++)
{
probabilityArray.Add(x);
}
}
for (int i = 0; i < numberToAdd; i++)
{
PopulationMember[] parents = new PopulationMember[Configuration.CROSSOVER_PARENT_COUNT];
for (int x = 0; x < parents.Length; x++)
{
parents [x] = newPop[probabilityArray [generator.next(0, probabilityArray.Count)]];
}
//Console.WriteLine ("{4}/{5}: Crossing {0} (fitness {1}) and {2} (fitness {3})", first, newPop[first].lastFitness, second, newPop[second].lastFitness, i, numberToAdd);
// Mutate crossover members
PopulationMember newMember = crosser.crossover(parents);
newMember = mutator.mutate(newMember);
// With a certain probability, the crossover will be dismissed and a brand new population member introduced
if (generator.next(0, Configuration.NEW_DURING_MUTATION_INVERSE) == 0)
{
PopulationMember p = new PopulationMember();
while (p.calculateFitness() < 1)
{
p = new PopulationMember();
}
newPop.Add(p);
}
else
{
newPop.Add(newMember);
}
//newPop.Add(crosser.crossover (newPop[first], newPop[second]));
}
return(newPop);
}
