private void plotLines(Population population, Color color)
{
Pen penBestIndividual = new Pen(color, 4);
int genA, genB;
Individual best = population.GetBestIndividual();
for (int i = 0; i < ConfigurationGA.sizeChromossome; i++)
{
if (i < ConfigurationGA.sizeChromossome - 1)
{
genA = best.GetGene(i);
genB = best.GetGene(i + 1);
}
else
{
genA = best.GetGene(i);
genB = best.GetGene(0);
}
int[] vetA = TablePoints.getCoordinates(genA);
int[] vetB = TablePoints.getCoordinates(genB);
g.DrawLine(penBestIndividual, vetA[0], vetA[1], vetB[0], vetB[1]);
}
}
private void BtnExecute_Click(object sender, EventArgs e)
{
btnPopulationGenerate.Enabled = false;
ConfigurationGA.rateCrossOver = float.Parse(txtCrossOverTax.Text);
ConfigurationGA.rateMutation = float.Parse(txtMutationTax.Text);
ConfigurationGA.tournamentCompetitors = int.Parse(txtFight.Text);
evolucoes += int.Parse(txtEvolution.Text);
if (rbNewInd.Checked)
{
ConfigurationGA.mutationType = Mutation.NewIndividual;
}
else if (rbPopulation.Checked)
{
ConfigurationGA.mutationType = Mutation.InPopulation;
}
if (chElitsm.Checked)
{
ConfigurationGA.elitism = true;
ConfigurationGA.sizeElitism = int.Parse(txtQtyElitsm.Text);
}
else
{
ConfigurationGA.elitism = false;
}
GeneticAlgorithm ag = new GeneticAlgorithm();
for (i = itemp; i < evolucoes; i++)
{
itemp++;
lbEvolucoes.Text = i.ToString();
lbEvolucoes.Refresh();
pop = ag.ExecuteGA(pop);
zedMedia.GraphPane.CurveList.Clear();
zedMedia.GraphPane.GraphObjList.Clear();
double mediaPop = pop.GetAveragePopulation();
double bestFitness = pop.GetBestIndividual().GetFitness();
mediaPopulation.Add(i, mediaPop);
lbDistance.Text = bestFitness.ToString();
lbDistance.Refresh();
LineItem media = paneMedia.AddCurve("Média", mediaPopulation, Color.Red, SymbolType.None);
if (i % 6 == 0 && bestFitness < bestAux)
{
bestAux = bestFitness;
g.Clear(Color.White);
plotLines(pop, Color.Blue);
plotPoints();
}
zedMedia.AxisChange();
zedMedia.Invalidate();
zedMedia.Refresh();
}
g.Clear(Color.White);
plotLines(pop, Color.Blue);
plotPoints();
}
