private void SimulateGeneration()
{
tempPopulation.Clear();
int FitToCopy = tourPopulation.Count * TOP_SURVIVORS / 100;
int UnfitToCopy = BOTTOM_SURVIVORS;
int i;
for (i = 0; i < FitToCopy; i++)
{
if (i != 0 && rand.Next(1, 100) <= MUTATION_PROBABILITY)
{
Mutate(tourPopulation[i]);
}
tempPopulation.Add(tourPopulation[i]);
}
for (; i < tourPopulation.Count - UnfitToCopy; i++)
{
Breed(tourPopulation[i]);
tempPopulation.Add(tourPopulation[i]);
}
for (; i < tourPopulation.Count; i++)
{
if (rand.Next(1, 100) <= MUTATION_PROBABILITY * 2)
{
Tour C = new Tour();
C.AddRange(tourPopulation[i].ToArray());
Mutate(C);
tempPopulation.Add(C);
}
}
tourPopulation.Clear();
tourPopulation.AddRange(tempPopulation);
}
private void Crossover(Tour parent1, Tour parent2, Tour child)
{
int unique = 0;
child.Clear();
int index = 0;
int start = rand.Next(0, numberOfCities * 6 / 10);
int len = rand.Next(numberOfCities * 3 / 10, (numberOfCities - 1 - start));
List <int> S;
S = parent1.GetRange(start, len);
int i = 0;
while (index < start)
{
if (!S.Contains(parent2[i]))
{
child.Add(parent2[i]);
index++;
}
else
{
unique++;
}
i++;
}
child.AddRange(S);
index += len;
while (index < parent1.Count())
{
if (!S.Contains(parent2[i]))
{
unique++;
child.Add(parent2[i]);
index++;
}
else
{
unique++;
}
i++;
}
if (unique == numberOfCities - len)
{
Mutate(child);
}
}