public GA(AlgorithmParameters algorithmParameters, EvaluatedFunction evaluatedFunction)
{
this.algorithmParameters = algorithmParameters;
this.evaluatedFunction = evaluatedFunction;
this.Chromosomes = new BitArray[algorithmParameters.Generations, 2, algorithmParameters.Population];
this.ChromosomeValues = new double[algorithmParameters.Generations, 3, algorithmParameters.Population];
this.BestValues = new double[algorithmParameters.Generations];
this.MeanValues = new double[algorithmParameters.Generations];
this.MedianValues = new double[algorithmParameters.Generations];
this.random = new Random();
// generate first population
for (int individualIndex = 0; individualIndex < algorithmParameters.Population; individualIndex++)
{
int x = generateRandomValue();
int y = generateRandomValue();
System.Diagnostics.Debug.WriteLine("X: " + x.ToString());
System.Diagnostics.Debug.WriteLine("Y: " + y.ToString());
BitArray x_genome = int2Binary(x, this.algorithmParameters.Precision);
BitArray y_genome = int2Binary(y, this.algorithmParameters.Precision);
this.Chromosomes[0, 0, individualIndex] = x_genome;
this.Chromosomes[0, 1, individualIndex] = y_genome;
}
}
private void AddParameters(object sender, RoutedEventArgs e)
{
DlgAddParameters dlg = new DlgAddParameters();
AlgorithmParameters algorithmParameters;
if (dlg.ShowDialog() == true)
{
double crossoverProbability = (double)dlg.crossoverProbability.Value;
double mutationProbability = (double)dlg.mutationProbability.Value;
int population = (int)dlg.individualsNumber.Value;
int generationsNumber = (int)dlg.generationsNumber.Value;
int precision = (int)dlg.precision.Value;
bool isMaximumSearching = (bool)dlg.maximumSearch.IsChecked;
algorithmParameters = new AlgorithmParameters(crossoverProbability, mutationProbability, population, generationsNumber, precision, isMaximumSearching);
algorithmParametersList.Add(algorithmParameters);
ICollectionView AlgParams = CollectionViewSource.GetDefaultView(AlgorithmGrid.ItemsSource);
if (AlgParams != null && AlgParams.CanGroup == true)
{
AlgParams.GroupDescriptions.Clear();
}
AlgorithmGrid.Items.Refresh();
}
}
private void Edit_Algorithm(object sender, RoutedEventArgs e)
{
DlgAddParameters dlg = new DlgAddParameters();
AlgorithmParameters algorithmParameters = AlgorithmGrid.SelectedItem as AlgorithmParameters;
int indexOfAlgorithm = algorithmParametersList.IndexOf(algorithmParameters);
dlg.crossoverProbability.Value = algorithmParameters.CrossoverProbability;
dlg.mutationProbability.Value = algorithmParameters.MutationProbability;
dlg.individualsNumber.Value = algorithmParameters.Population;
dlg.generationsNumber.Value = algorithmParameters.Generations;
dlg.precision.Value = algorithmParameters.Precision;
dlg.maximumSearch.IsChecked = algorithmParameters.isMaxSearching;
if (dlg.ShowDialog() == true)
{
algorithmParameters.CrossoverProbability = (double)dlg.crossoverProbability.Value;
algorithmParameters.MutationProbability = (double)dlg.mutationProbability.Value;
algorithmParameters.Population = (int)dlg.individualsNumber.Value;
algorithmParameters.Generations = (int)dlg.generationsNumber.Value;
algorithmParameters.Precision = (int)dlg.precision.Value;
algorithmParameters.isMaxSearching = (bool)dlg.maximumSearch.IsChecked;
algorithmParametersList[indexOfAlgorithm] = algorithmParameters;
AlgorithmGrid.Items.Refresh();
}
}
private void FilterParameters(object sender, RoutedEventArgs e)
{
DlgFilterParameters dlg = new DlgFilterParameters();
if (dlg.ShowDialog() == true)
{
ListCollectionView collectionView = new ListCollectionView(algorithmParametersList);
collectionView.Filter = (o) =>
{
AlgorithmParameters algorithmParameters = o as AlgorithmParameters;
if (dlg.greaterCrossover.IsChecked != null)
{
if ((bool)dlg.greaterCrossover.IsChecked)
{
if (algorithmParameters.CrossoverProbability <= dlg.crossoverProbability.Value)
{
return(false);
}
}
}
if (dlg.lesserCrossover.IsChecked != null)
{
if ((bool)dlg.lesserCrossover.IsChecked)
{
if (algorithmParameters.CrossoverProbability >= dlg.crossoverProbability.Value)
{
return(false);
}
}
}
if (dlg.greaterMutation.IsChecked != null)
{
if ((bool)dlg.greaterMutation.IsChecked)
{
if (algorithmParameters.MutationProbability <= dlg.mutationProbability.Value)
{
return(false);
}
}
}
if (dlg.lesserMutation.IsChecked != null)
{
if ((bool)dlg.lesserMutation.IsChecked)
{
if (algorithmParameters.MutationProbability >= dlg.mutationProbability.Value)
{
return(false);
}
}
}
if (dlg.greaterPrecision.IsChecked != null)
{
if ((bool)dlg.greaterPrecision.IsChecked)
{
if (algorithmParameters.Precision <= dlg.precision.Value)
{
return(false);
}
}
}
if (dlg.lesserPrecision.IsChecked != null)
{
if ((bool)dlg.lesserPrecision.IsChecked)
{
if (algorithmParameters.Precision >= dlg.precision.Value)
{
return(false);
}
}
}
if (dlg.greaterPopulation.IsChecked != null)
{
if ((bool)dlg.greaterPopulation.IsChecked)
{
if (algorithmParameters.Population <= dlg.individualsNumber.Value)
{
return(false);
}
}
}
if (dlg.lesserPopulation.IsChecked != null)
{
if ((bool)dlg.lesserPopulation.IsChecked)
{
if (algorithmParameters.Population >= dlg.individualsNumber.Value)
{
return(false);
}
}
}
if (dlg.greaterGeneration.IsChecked != null)
{
if ((bool)dlg.greaterGeneration.IsChecked)
{
if (algorithmParameters.Generations <= dlg.generationsNumber.Value)
{
return(false);
}
}
}
if (dlg.lesserGeneration.IsChecked != null)
{
if ((bool)dlg.lesserGeneration.IsChecked)
{
if (algorithmParameters.Generations >= dlg.generationsNumber.Value)
{
return(false);
}
}
}
if (dlg.minimumSearch.IsChecked != null)
{
if ((bool)dlg.minimumSearch.IsChecked)
{
if (algorithmParameters.isMaxSearching)
{
return(false);
}
}
}
if (dlg.maximumSearch.IsChecked != null)
{
if ((bool)dlg.maximumSearch.IsChecked)
{
if (!algorithmParameters.isMaxSearching)
{
return(false);
}
}
}
return(true);
};
AlgorithmGrid.ItemsSource = collectionView;
}
}
