private void btnStart_Click(object sender, EventArgs e)
{
GeneticAlgo geneticAlgo = new GeneticAlgo();
geneticAlgo.progress += new Progress(updateProgress);
//progressBar1.Maximum = (int)txtGen.Value;
//progressBar1.Value = 0;
if (Algo == 2)
{
List <Chromosome> initPopulation = GetInitialPopulation((int)txtPop.Value);
//if(chkPorgress.Checked)
geneticAlgo.DoMating(ref initPopulation, (int)txtGen.Value, (double)txtCrosProb.Value, (double)txtMutProb.Value);
dgResults.Rows.Clear();
for (int i = 0; i < initPopulation.Count - 1; i++)
{
label8.Text = i.ToString();
String sol = "| ";
for (int j = 0; j < 8; j++)
{
sol = sol + initPopulation[i].genes[j] + " | ";
}
dgResults.Rows.Add(new Object[] { sol, initPopulation[i].fitness });
}
//int[] x = new int[]{ 1, 2 };
board1.Genes = initPopulation[0].genes;
}
}
private List <Chromosome> GetInitialPopulation(int population)
{
List <Chromosome> initPop = new List <Chromosome>();
GeneticAlgo RandomGen = new GeneticAlgo();
for (int i = 0; i < population; i++)
{
List <int> genes = new List <int>(new int[] { 0, 1, 2, 3, 4, 5, 6, 7 });
Chromosome chromosome = new Chromosome();
chromosome.genes = new int[8];
for (int j = 0; j < 8; j++)
{
int geneIndex = (int)(RandomGen.GetRandomVal(0, genes.Count - 1) + 0.5);
chromosome.genes[j] = genes[geneIndex];
genes.RemoveAt(geneIndex);
}
initPop.Add(chromosome);
}
return(initPop);
}
