/// <summary>
/// Perform one generation.
/// </summary>
public virtual void Iteration()
{
int countToMate = (int)(Population.Genomes.Count * PercentToMate);
int offspringCount = countToMate * 2;
int offspringIndex = Population.Genomes.Count - offspringCount;
int matingPopulationSize = (int)(Population.Genomes.Count * MatingPopulation);
TaskGroup group = EngineConcurrency.Instance
.CreateTaskGroup();
// mate and form the next generation
for (int i = 0; i < countToMate; i++)
{
IGenome mother = Population.Genomes[i];
int fatherInt = (int)(ThreadSafeRandom.NextDouble() * matingPopulationSize);
IGenome father = Population.Genomes[fatherInt];
IGenome child1 = Population.Genomes[offspringIndex];
IGenome child2 = Population.Genomes[
offspringIndex + 1];
MateWorker worker = new MateWorker(mother, father, child1,
child2);
EngineConcurrency.Instance.ProcessTask(worker, group);
offspringIndex += 2;
}
group.WaitForComplete();
// sort the next generation
Population.Sort();
}
/// <summary>
/// Perform one generation.
/// </summary>
public virtual void Iteration(GATracker gaTracker)
{
int countToMate = (int)(Population.Genomes.Count * PercentToMate);
int matingPopulationSize = (int)(Population.Genomes.Count * MatingPopulation);
//The only individuals we want to preserve is the mating population.
//i.e. everything but the mating population gets replaced.
int newOffspringCount = Population.Genomes.Count - matingPopulationSize;
int newOffspringIndex = Population.Genomes.Count - newOffspringCount;
int offspringCount = countToMate * 2;
//int offspringIndex = Population.Genomes.Count - offspringCount;
//TaskGroup group = EngineConcurrency.Instance.CreateTaskGroup();
// mate and form the next generation
//20 < 80
while (newOffspringIndex < newOffspringCount + matingPopulationSize)
{
for (int i = 0; i < countToMate; i++)
{
IGenome mother = Population.Genomes[i];
int fatherInt = (int)(ThreadSafeRandom.NextDouble() * matingPopulationSize);
IGenome father = Population.Genomes[fatherInt];
IGenome child1 = Population.Genomes[newOffspringIndex];
IGenome child2 = Population.Genomes[newOffspringIndex + 1];
GATracker.MatedElement matedElement = new GATracker.MatedElement(i, fatherInt, newOffspringIndex, newOffspringIndex + 1);
MateWorker worker = new MateWorker(mother, father, child1, child2, matedElement);
//EngineConcurrency.Instance.ProcessTask(worker, group);
worker.Run();
//Add the matedElement to the GATracker
gaTracker.AddMatedElement(matedElement);
newOffspringIndex += 2;
}
}
//group.WaitForComplete();
// sort the next generation
Population.Sort();
}
/// <summary>
/// Perform one generation.
/// </summary>
public virtual void Iteration()
{
int countToMate = (int)(Population.Genomes.Count * PercentToMate);
int offspringCount = countToMate * 2;
int offspringIndex = Population.Genomes.Count - offspringCount;
int matingPopulationSize = (int)(Population.Genomes.Count * MatingPopulation);
TaskGroup group = EngineConcurrency.Instance
.CreateTaskGroup();
// mate and form the next generation
for (int i = 0; i < countToMate; i++)
{
IGenome mother = Population.Genomes[i];
int fatherInt = (int)(ThreadSafeRandom.NextDouble() * matingPopulationSize);
IGenome father = Population.Genomes[fatherInt];
IGenome child1 = Population.Genomes[offspringIndex];
IGenome child2 = Population.Genomes[
offspringIndex + 1];
MateWorker worker = new MateWorker(mother, father, child1,
child2);
EngineConcurrency.Instance.ProcessTask(worker, group);
offspringIndex += 2;
}
group.WaitForComplete();
// sort the next generation
Population.Sort();
}
