/// <summary>
/// Main postcript function to store best results
/// </summary>
private void workerProgressChanged(object sender, ProgressChangedEventArgs e)
{
try
{
IChromosome bestChromosome = GA.Population.BestChromosome;
//BASIC
GADataSet ds = GARow.Table.DataSet as GADataSet;
GADataSet.SolutionsRow currentSolution;
currentSolution = ds.Solutions.NewSolutionsRow();
currentSolution.Initialize(bestChromosome.GetGenes());
currentSolution.ProblemID = PROBLEMID;
//this is the most important function to override, does the fitness calc
FillBasic(ref currentSolution);
GeneticAlgorithm ga = GA;
//fill GA data to row
GARow.Update(ref ga); //report GA stuff
//define filter function by genotype
Func <GADataSet.SolutionsRow, bool> funcion;
funcion = Aid.FilterByGenotype(ref hashListOfGenotypes, ref listOfSolutions);
//execute filter function by genotype
funcion(currentSolution);
//the listOfSolutions contains the list of rows that need to be added
//these rows are flagged ShouldDelete = false
//REPONER ESTO
if (!currentSolution.ShouldDelete)
{
ds.Solutions.AddSolutionsRow(currentSolution);
GARow.FillGADataToSolution(ref currentSolution);
}
//callBack MEthod to Form or User Control
CallBack.Invoke();
}
catch (Exception ex)
{
throw ex;
}
}
/// <summary>
/// Configure the Genetic Algorithm
/// </summary>
public virtual void RunConfiguration()
{
// Initialize(); //IMPORTANT
// crossover = new CycleCrossover();
IChromosome adam = CreateChromosome();
IPopulation population = new Population(probabilities.minPop, probabilities.maxPop, adam);
population.GenerationStrategy = new PerformanceGenerationStrategy();
//population.GenerationStrategy = new TrackingGenerationStrategy();
IFitness fitness = CreateFitness();
GeneticAlgorithm ga;
ga = new GeneticAlgorithm(population, fitness, config.Selection, config.Crossover, config.Mutation);
ga.Termination = config.Termination;
if (config.Reinsertion != null)
{
ga.Reinsertion = config.Reinsertion;
}
// ga.Termination = new GenerationNumberTermination(probabilities.maxPop);
ga.MutationProbability = probabilities.mutationProb;
ga.CrossoverProbability = probabilities.crossProb;
// ga.TaskExecutor = null;
ga.TaskExecutor = new SmartThreadPoolTaskExecutor()
{
MinThreads = 10,
MaxThreads = 70
};
GARow.Initialize(ref ga); //initialize
GARow.ConfigTypes(ref config); // types ids
GARow.ConfigTypesNames(ref ga); // types names, change with ids only
GA = ga;
}
