private void CrossOverParents(
CandidateSolution <T, S> parent1, CandidateSolution <T, S> parent2,
out CandidateSolution <T, S> child1, out CandidateSolution <T, S> child2)
{
// are we crossing over, or just copying a parent directly?
child1 = parent1.Clone();
child2 = parent2.Clone();
// Do we use exact copies of parents, or crossover?
if (Randomizer.GetDoubleFromZeroToOne() < CrossoverRate)
{
NodeBaseType <T, S> randomC1node, randomC2node;
// pick a random node from both parents and clone the tree below it.
// We don't want root nodes, since that's not really crossover, so we disallow those
do
{
randomC1node = child1.SelectRandomNode();
} while (randomC1node == child1.Root);
do
{
randomC2node = child2.SelectRandomNode();
} while (randomC2node == child2.Root);
// make copies of them
var newChild1 = randomC1node.Clone(null);
var newChild2 = randomC2node.Clone(null);
// create new children by swapping subtrees
CandidateSolution <T, S> .SwapSubtrees(randomC1node, randomC2node, newChild1, newChild2);
// and reset the pointers to the candidate
child1.Root.SetCandidateRef(child1);
child2.Root.SetCandidateRef(child2);
}
}
private CandidateSolution <T, S> RouletteSelectParent()
{
// using Roulette Wheel Selection, we grab a possibility proportionate to it's fitness compared to
// the total fitnesses of all possibilities
double randomValue = Randomizer.GetDoubleFromZeroToOne() * totalFitness;
for (int i = 0; i < PopulationSize; i++)
{
randomValue -= currentGeneration[i].Fitness;
if (randomValue <= 0)
{
return(currentGeneration[i]);
}
}
return(currentGeneration[PopulationSize - 1]);
}