protected override void NextIteration()
{
int populationSize = Population.Count;
int n = (int)Math.Sqrt(populationSize);
int m = populationSize / n;
int rem = populationSize - n * m;
var newGeneration = new List <Individual>(populationSize);
int indexOfBest = 0;
double maxProba = 0;
double currentProba = 0;
for (int i = 0; i < populationSize - rem; i++)
{
var neighbours = FindNeighbours(i, n, m);
indexOfBest = 0;
maxProba = 0;
for (int j = 0; j < 4; j++)
{
currentProba = neighbours[j].Fitness * (RandomGenerator.NextDouble() * 0.5 + 0.5);
if (currentProba > maxProba)
{
indexOfBest = j;
maxProba = currentProba;
}
}
var children = neighbours[indexOfBest].Crossover(Population[i], RandomGenerator);
newGeneration.Add(children.Max());
}
for (int i = populationSize - rem; i < populationSize; i++)
{
newGeneration.Add(Population[i]);
}
if (newGeneration.Count < populationSize)
{
newGeneration.Add(Population[RandomGenerator.Next(populationSize)].Mutate(RandomGenerator));
}
for (int i = 0; i < newGeneration.Count; i++)
{
if (RandomGenerator.NextDouble() < MutationProbability)
{
newGeneration[i] = newGeneration[i].Mutate(RandomGenerator);
}
}
Population = newGeneration;
foreach (Individual individual in Population)
{
if (BestIndividual == null || BestIndividual.CompareTo(individual) < 0)
{
BestIndividual = individual;
}
}
}
public void ToNextGeneration()
{
m_currentGeneration++;
// (1,1) , always use children
if (!Configuration.s_isParentCandidate)
{
for (int index = 0; index < m_populationSize; index++)
{
double originalFitness = m_population[index].GetFitness();
m_population[index].Mutate();
double mutatedFitness = m_population[index].GetFitness();
}
}
else // (1+1)
{
for (int index = 0; index < m_populationSize; index++)
{
Chromesome parent = m_population[index];
Chromesome child = new Chromesome(parent);
// mutate the child
child.Mutate();
// in this case, parent wins
if (parent.GetFitness() < child.GetFitness())
{
m_population[index] = parent;
}
else // in this case, child (after mutation) wins
{
m_population[index] = child;
}
}
}
// set up for successful mutation
double originalBestFitness = BestIndividual.GetFitness();
// Update world status
UpdateBestIndividual();
double mutatedBestFitness = BestIndividual.GetFitness();
if (mutatedBestFitness < originalBestFitness)
{
m_successfulMutationCount++;
}
}
protected override void NextIteration()
{
int populationSize = Population.Count;
var newGeneration = new List <Individual>(populationSize);
int eliteSize = (int)(ElitePart * GenerationSize);
// add elite individuals to new generation
newGeneration.AddRange(Population.Take(eliteSize));
for (int i = 0; i < (populationSize - eliteSize) / 2; i++)
{
Individual a1, a2;
a1 = Population[RandomGenerator.Next(populationSize)];
a2 = Population[RandomGenerator.Next(populationSize)];
var children = a1.Crossover(a2, RandomGenerator);
newGeneration.AddRange(children);
}
if (newGeneration.Count < populationSize)
{
newGeneration.Add(Population[RandomGenerator.Next(populationSize)].Mutate(RandomGenerator));
}
for (int i = 0; i < newGeneration.Count; i++)
{
if (RandomGenerator.NextDouble() < MutationProbability)
{
newGeneration[i] = newGeneration[i].Mutate(RandomGenerator);
}
}
newGeneration.Sort();
newGeneration.Reverse();
Population = newGeneration;
if (BestIndividual == null || BestIndividual.CompareTo(Population[0]) < 0)
{
BestIndividual = Population[0];
}
}
