public void Reproduction()
{
chromoGens = Crossover.doCrossover(crossoverType, chromoGens, probabilityCrossover, random);
//chromoGens = Mutation.doMutation(1, chromoGens, probabilityMutation, random);
chromoValue = Chromossome.getPopulationValues(chromoGens, rangeMin, rangeMax, granularity, random);
chromoFitness = Chromossome.getPopulationFitness(functionType, optimizationType, chromoValue);
}
private void ConductGeneticAlgorithm()
{
if (isConductingGA)
{
return;
}
isConductingGA = true;
int[,] xVal = new int[4, DataStorage.initialPopCount];
if (generationCtr == 0)
{
for (int i = 0; i < DataStorage.initialPopCount; i++)
{
xVal[0, i] = xVal[1, i] = xVal[2, i] = xVal[3, i] = rnd.Next(DataStorage.lowerBound, DataStorage.UpperBound);
}
}
else
{
xVal = mutatedChromosomes;
}
// Performing selection
int[,] selectedXVal = Selection.DoSelection(xVal, ref mainSelectionTable, ref additionalSelectionTable);
// Performing crossover
int[,] crossOveredValue = Crossover.DoCrossover(selectedXVal, ref crossOverTable);
// Performing mutation
int[] maxima = new int[4];
mutatedChromosomes = Mutation.DoMutation(crossOveredValue, ref mutationTable, ref maxima);
for (int gen = 0; gen < 4; gen++)
{
maximaSaved[generationCtr, gen] = maxima[gen];
}
GenerationTB.Text = (generationCtr + 1).ToString();
MaximaTB.Text = maxima[genIndex].ToString();
for (int gen = 0; gen < 4; gen++)
{
GenVsMaximaChart.Series[DataStorage.selectionSchemes[gen]].Points.AddXY((generationCtr + 1), DataStorage.UpperBound - maximaSaved[generationCtr, gen]);
}
generationCtr++;
isConductingGA = false;
if (generationCtr == DataStorage.generationCount)
{
Form analysis = new Analysis();
analysis.Show();
}
}
private void UpdateTableAndGraphValues()
{
SelectionTypeLB.Text = DataStorage.selectionSchemes[genIndex];
MaximaTB.Text = maximaSaved[generationCtr - 1, genIndex].ToString();
Selection.UpdateTableValue(ref mainSelectionTable, ref additionalSelectionTable);
Crossover.UpdateTableValue(ref crossOverTable);
Mutation.UpdateTableValue(ref mutationTable);
toolTip1.SetToolTip(SelectionTypeLB, DataStorage.selectionToolTip[genIndex]);
}
private void ConductGeneticAlgorithm()
{
string[,] initialPath = new string[4, DataStorage.initialPopCount];
if (generationCtr == 0)
{
for (int i = 0; i < DataStorage.initialPopCount; i++)
{
initialPath[0, i] = initialPath[1, i] = initialPath[2, i] = initialPath[3, i] = Utility.GetRandomPath(DataStorage.cityCount);
}
}
else
{
initialPath = mutatedPath;
}
// Performing selection
string[,] selectedpath = Selection.DoSelection(initialPath, ref mainSelectionTable, ref additionalSelectionTable);
// Performing crossover
string[,] crossOveredValue = Crossover.DoCrossover(selectedpath, ref crossOverTable);
// Performing mutation
int[] minima = new int[4];
string[] minimaPath = new string[4];
mutatedPath = Mutation.DoMutation(crossOveredValue, ref mutationTable, ref minima, ref minimaPath);
for (int gen = 0; gen < 4; gen++)
{
minimaSaved[generationCtr, gen] = minima[gen];
minimaPathSaved[generationCtr, gen] = minimaPath[gen];
}
GenerationTB.Text = (generationCtr + 1).ToString();
MinimaTB.Text = minima[genIndex].ToString();
MinimaPathTB.Text = minimaPath[genIndex].ToString();
for (int gen = 0; gen < 4; gen++)
{
DistanceChart.Series[DataStorage.selectionSchemes[gen]].Points.AddXY((generationCtr + 1), minimaSaved[generationCtr, gen]);
}
generationCtr++;
if (generationCtr == DataStorage.generationCount)
{
Form analysis = new Analysis();
analysis.Show();
}
}
private void TableAndGraph_Load(object sender, EventArgs e)
{
UpdateGenIndex(DataStorage.selectionType);
// SelectionSchemeChoose combobox
SelectionSchemeChooseCB.Items.Add("Roulette wheel selection");
SelectionSchemeChooseCB.Items.Add("Random selection");
SelectionSchemeChooseCB.Items.Add("Rank selection");
SelectionSchemeChooseCB.Items.Add("Tournament selection");
////// Selection tables
SelectionDGV.DataSource = Selection.InitializeTable();
SelectionDGV.Columns[0].Width = 50;
SelectionAdditionalDGV.DataSource = Selection.InitializeAdditionalTable();
SelectionTypeLB.Text = DataStorage.selectionType;
mainSelectionTable = SelectionDGV.DataSource as DataTable;
additionalSelectionTable = SelectionAdditionalDGV.DataSource as DataTable;
toolTip1.SetToolTip(SelectionTypeLB, DataStorage.selectionToolTip[genIndex]);
// Crossover tables
CrossoverDGV.DataSource = Crossover.InitializeTable();
CrossoverDGV.Columns[0].Width = 50;
CrossoverTypeLB.Text = DataStorage.crossoverType;
CrosoverRateLB.Text = "Crossover rate: " + DataStorage.crossoverRate.ToString() + "%";
crossOverTable = CrossoverDGV.DataSource as DataTable;
toolTip1.SetToolTip(CrossoverTypeLB, DataStorage.GetCrossoverToolTip());
// Mutation tables
MutationDGV.DataSource = Mutation.InitializeTable();
MutationDGV.Columns[0].Width = 50;
MutationTypeLB.Text = DataStorage.mutationType;
MutationRateLB.Text = "Mutation rate: " + DataStorage.mutationRate.ToString() + "%";
mutationTable = MutationDGV.DataSource as DataTable;
toolTip1.SetToolTip(MutationTypeLB, DataStorage.GetMutationToolTip());
ShowFitnessFunLB.Text = DataStorage.fitnessFunction;
SelectionSchemeChooseCB.Text = DataStorage.selectionType;
maximaSaved = new int[DataStorage.generationCount, 4];
ConductGeneticAlgorithm();
}
private void TSPTableAndGraph_Load(object sender, EventArgs e)
{
UpdateGenIndex(DataStorage.selectionType);
// SelectionSchemeChoose combobox
this.SelectionSchemeChooseCB.Items.Add("Roulette wheel selection");
this.SelectionSchemeChooseCB.Items.Add("Random selection");
this.SelectionSchemeChooseCB.Items.Add("Rank selection");
this.SelectionSchemeChooseCB.Items.Add("Tournament selection");
// Selection tables
SelectDGV.DataSource = Selection.InitializeTable();
AdditionalSelectDGV.DataSource = Selection.InitializeAdditionalTable();
this.SelectionTypeLB.Text = DataStorage.selectionType;
mainSelectionTable = SelectDGV.DataSource as DataTable;
additionalSelectionTable = AdditionalSelectDGV.DataSource as DataTable;
toolTip1.SetToolTip(SelectionTypeLB, DataStorage.selectionToolTip[genIndex]);
// Crossover tables
CrossDGV.DataSource = Crossover.InitializeTable();
this.CrossoverTypeLB.Text = DataStorage.crossoverType;
this.CrosoverRateLB.Text = "Crossover rate: " + DataStorage.crossoverRate.ToString() + "%";
crossOverTable = CrossDGV.DataSource as DataTable;
toolTip1.SetToolTip(CrossoverTypeLB, DataStorage.GetCrossoverToolTip());
// Mutation tables
MutDGV.DataSource = Mutation.InitializeTable();
this.MutationTypeLB.Text = DataStorage.mutationType;
this.MutationRateLB.Text = "Mutation rate: " + DataStorage.mutationRate.ToString() + "%";
mutationTable = MutDGV.DataSource as DataTable;
toolTip1.SetToolTip(MutationTypeLB, DataStorage.GetMutationToolTip());
// Initializing the selection scheme choose combobox
this.SelectionSchemeChooseCB.Text = DataStorage.selectionType;
// Matrix containing the minimum distance from each generation for each selection scheme
minimaSaved = new int[DataStorage.generationCount, 4];
minimaPathSaved = new string[DataStorage.generationCount, 4];
// What are we waiting for, set start the games
ConductGeneticAlgorithm();
}
private void button2_Click(object sender, EventArgs e)
{
if (initflag == true)
{
chromoC = Crossover.TwoPoints(chromoP, 50, _random);
richTextBox1.Clear();
richTextBox2.Clear();
for (int i = 0; i < chromoP.Count(); i++)
{
richTextBox1.AppendText(chromoP[i] + "\n");
richTextBox2.AppendText(chromoC[i] + "\n");
}
chromoP = chromoC;
}
else
{
chromoP = Chromossome.Creates(6, 0, 63, 0, _random);
initflag = true;
}
}
