public void Recombinate()
{
IndividualEvaluations evaluations = new IndividualEvaluations();
Random random = new Random();
_populationAfterCrossing = new Population();
for (var i = 0; i < _matingPool.Size() / 2; i++)
{
var chosenIndividual1 = random.Next(_matingPool.Size());
var chosenIndividual2 = random.Next(_matingPool.Size());
var newIndividuals = evaluations.Cross(_matingPool.GetIndividual(chosenIndividual1), _matingPool.GetIndividual(chosenIndividual2));
var tempCrsProb = random.NextDouble();
if (tempCrsProb < _crossingProbability)
{
_populationAfterCrossing.Add(newIndividuals[0]);
_populationAfterCrossing.Add(newIndividuals[1]);
}
else
{
_populationAfterCrossing.Add(_matingPool.GetIndividual(chosenIndividual1));
_populationAfterCrossing.Add(_matingPool.GetIndividual(chosenIndividual2));
}
}
}
public void Mutation()
{
IndividualEvaluations evaluations = new IndividualEvaluations();
_populationAfterMutation = new Population();
_populationAfterCrossing.GenerateProbabilities();
for (var i = 0; i < _populationAfterCrossing.Size(); i++)
{
_populationAfterMutation.Add(
_populationAfterCrossing.GetIndividual(i).GetMutationProbability() < _mutationProbability
? evaluations.Mutate(_populationAfterCrossing.GetIndividual(i))
: _populationAfterCrossing.GetIndividual(i));
_populationAfterMutation.GetIndividual(i).Calculate(_function1, _function2);
}
}
public static Population EvolvePopulation(Population p)
{
Population newPopulation = new Population(p.Size(), false);
if (elitism)
{
newPopulation.SaveIndividual(0, p.GetFittest());
}
int elitismOffset;
if (elitism)
{
elitismOffset = 1;
}
else
{
elitismOffset = 0;
}
for (int i = elitismOffset; i < p.Size(); i++)
{
Individual indiv1 = TournamentSelection(p);
Individual indiv2 = TournamentSelection(p);
Individual newIndiv = Crossover(indiv1, indiv2);
newPopulation.SaveIndividual(i, newIndiv);
}
for (int i = elitismOffset; i < newPopulation.Size(); i++)
{
Mutate(newPopulation.GetIndividual(i));
}
return(newPopulation);
}
/// <summary>
///
/// </summary>
/// <param name="p"></param>
/// <returns></returns>
private static Individual TournamentSelection(Population p)
{
Population tournament = new Population(tournamentSize, false);
Random rndgen = new Random();
for (int i = 0; i < tournamentSize; i++)
{
int randomID = (int)(rndgen.NextDouble() * p.Size());
tournament.SaveIndividual(i, p.GetIndividual(randomID));
}
Individual fittest = tournament.GetFittest();
return(fittest);
}
private void button1_Click(object sender, EventArgs e)
{
FunctionStruct functionStruct1 = new FunctionStruct(comboBox1.SelectedItem.ToString(), func1.Text);
FunctionStruct functionStruct2 = new FunctionStruct(comboBox1.SelectedItem.ToString(), func2.Text);
Population nonDominatedPopulation = new Population();
//chart2.Visible = false;
chart1.Series["Series1"].Points.Clear();
chart2.Series["Series1"].Points.Clear();
//chart1.ChartAreas[0].AxisX.RoundAxisValues();
dataGridView1.Rows.Clear();
int lo = 0;
int up = 0;
int[] lotab = new int[comboBox1.SelectedIndex + 1];
int[] uptab = new int[comboBox1.SelectedIndex + 1];
for (int i = 0; i <= comboBox1.SelectedIndex; i++)
{
switch (i)
{
case 0:
lo = int.Parse(tbL1.Text);
up = int.Parse(tbU1.Text);
break;
case 1:
lo = int.Parse(tbL2.Text);
up = int.Parse(tbU2.Text);
break;
case 2:
lo = int.Parse(tbL3.Text);
up = int.Parse(tbU3.Text);
break;
case 3:
lo = int.Parse(tbL4.Text);
up = int.Parse(tbU4.Text);
break;
case 4:
lo = int.Parse(tbL5.Text);
up = int.Parse(tbU5.Text);
break;
}
lotab[i] = lo;
uptab[i] = up;
}
Constraints constraints = new Constraints(lotab, uptab);
Vega vega = new Vega(int.Parse(popSize.Text), int.Parse(iterations.Text),
Double.Parse(crossingPb.Text, CultureInfo.InvariantCulture),
Double.Parse(mutationPb.Text, CultureInfo.InvariantCulture), functionStruct1, functionStruct2,
constraints);
vega.Initialization();
var result = vega.Iterate();
var index = 0;
if (result.GetIndividual(0).GetFitness2() < result.GetIndividual(1).GetFitness2())
{
nonDominatedPopulation.Add(result.GetIndividual(0));
}
else
{
nonDominatedPopulation.Add(result.GetIndividual(1));
index = 1;
}
result.SortF1();
chart2.Series["Series1"].ChartType = SeriesChartType.Point;
for (var i = 0; i < result.Size(); i++)
{
chart2.Series["Series1"].Points.AddXY(result.GetIndividual(i).GetFitness1(),
result.GetIndividual(i).GetFitness2());
}
for (var i = 1; i < result.Size(); i++)
{
if (result.GetIndividual(i).GetFitness2() < nonDominatedPopulation.GetIndividual(nonDominatedPopulation.Size() - 1).GetFitness2())
{
nonDominatedPopulation.Add(result.GetIndividual(i));
}
}
if (nonDominatedPopulation.GetIndividual(0).GetFitness1() > nonDominatedPopulation.GetIndividual(1).GetFitness1())
{
nonDominatedPopulation.DeleteIndividual(0);
}
chart1.Series["Series1"].ChartType = SeriesChartType.Point;
for (var i = 0; i < nonDominatedPopulation.Size(); i++)
{
string[] mystring = new string[] { "", "", "", "", "", "", "" };
chart1.Series["Series1"].Points.AddXY(nonDominatedPopulation.GetIndividual(i).GetFitness1(),
nonDominatedPopulation.GetIndividual(i).GetFitness2());
mystring[0] = nonDominatedPopulation.GetIndividual(i).GetFitness1().ToString();
mystring[1] = nonDominatedPopulation.GetIndividual(i).GetFitness2().ToString();
for (var j = 0; j < nonDominatedPopulation.GetIndividual(i).GetArgsVector().Count; j++)
{
mystring[j + 2] = Math.Round(nonDominatedPopulation.GetIndividual(i).GetArgsVector()[j], 3).ToString();
}
dataGridView1.Rows.Add(mystring);
}
}
