private static void gasolver_CrossoverSelected(CrossoverEventArgs args)
{
if (_createDiagLogs)
{
using (var sw = new StreamWriter(_crossoverlogFilename, true)) {
sw.WriteLine(args.MovesParent1);
sw.WriteLine(args.MovesParent2);
sw.WriteLine("----------------------------------------------------------------------------------------------------");
sw.Flush();
sw.Close();
}
}
}
private void PerformCrossover(IRandomizer randomizer)
{
var x = new ChromosomeSelector(_currentGeneration);
var parent1 = x.Get(randomizer);
var parent2 = x.Get(randomizer);
MoveList child1;
MoveList child2;
if (parent1.CompareTo(parent2) == 0)
{
child1 = Perform2ROG(randomizer);
child2 = Perform2ROG(randomizer);
_currentGeneration.Add(child1);
_currentGeneration.Add(child2);
}
else
{
if (CrossoverSelected != null)
{
var coEventArgs = new CrossoverEventArgs {
MovesParent1 = parent1.ToString(),
MovesParent2 = parent2.ToString()
};
CrossoverSelected(coEventArgs);
}
//Get crossover strategy
var strategy = CrossoverFactory.GetCrossoverStrategy(randomizer);
//Do crossover
var children = strategy.DoCrossover(parent1, parent2);
child1 = children.Item1;
child2 = children.Item2;
CheckAndAddValidChild(child1, true, false);
CheckAndAddValidChild(child2, true, false);
}
}
/// <summary>
/// Main process loop for performing a crossover on a population.
/// </summary>
protected void Process()
{
int maxLoop = 100;
int eliteCount = 0;
//reset the number of evaluations
_evaluations = 0;
//now that we know how many children we are to be creating, in the case of 'Delete Last'
//we copy the current generation across and add new children where they are greater than
//the worst solution.
if (_replacementMethodS == ReplacementMethod.DeleteLast)
{
//copy everything accross including the elites
NewPopulation.Solutions.Clear();
NewPopulation.Solutions.AddRange(CurrentPopulation.Solutions);
}
else
{
//just copy the elites, this will take all elites
//TODO: Sort out what we do if we overfill the population with elites
var elites = CurrentPopulation.GetElites();
eliteCount = elites.Count();
if (elites != null && eliteCount > 0)
{
NewPopulation.Solutions.AddRange(elites);
}
}
_currentPopulationSize = CurrentPopulation.Solutions.Count;
_numberOfChildrenToGenerate =
_currentPopulationSize - eliteCount;
while (_numberOfChildrenToGenerate > 0)
{
//emergency exit
if (maxLoop <= 0)
{
throw new ChromosomeException("Unable to create a suitable child. If duplicates have been disallowed then consider increasing the chromosome length or increasing the number of elites.");
}
//these will hold the children
Chromosome c1 = null;
Chromosome c2 = null;
//select some parents
var parents = CurrentPopulation.SelectParents();
var p1 = parents[0];
var p2 = parents[1];
//crossover
var crossoverData = CreateCrossoverData(p1.Genes.Count, CrossoverType);
var crossoverResult = PerformCrossover(p1, p2, CrossoverProbability, CrossoverType, crossoverData, out c1, out c2);
//pass the children out to derived classes
//(e.g. CrossoverMutate class uses this to perform mutation)
if (OnCrossoverComplete != null)
{
var eventArgs = new CrossoverEventArgs(crossoverResult);
OnCrossoverComplete(this, eventArgs);
}
if (AddChild(c1))
{
_numberOfChildrenToGenerate--;
}
else
{
//unable to create child
maxLoop--;
}
//see if we can add the secomd
if (_numberOfChildrenToGenerate > 0)
{
if (AddChild(c2))
{
_numberOfChildrenToGenerate--;
}
else
{
//unable to create child
maxLoop--;
}
}
}
}
