private void Mutate(SudokuChromesome aGene)
{
if (Sudokufitness.TheSeed.Next(100) < (int)(kMutationFrequency * 100.0))
{
aGene.Mutate();
}
}
public override void CopyGeneInfo(SudokuChromesome dest)
{
Sudokufitness theGene = (Sudokufitness)dest;
theGene.Length = Length;
theGene.TheMin = TheMin;
theGene.TheMax = TheMax;
}
// Calculer Generateur
public void CalculateGeneration(int nPopulation, int nGeneration)
{
int _previousFitness = 0;
Population TestPopulation = new Population();
for (int i = 0; i < nGeneration; i++)
{
if (_threadFlag)
{
break;
}
TestPopulation.NextGeneration();
SudokuChromesome g = TestPopulation.GetHighestScoreGenome();
if (i % 100 == 0)
{
Console.WriteLine("Generation #{0}", i);
if (ToPercent(g.CurrentFitness) != _previousFitness)
{
Console.WriteLine(g.ToString());
_gene = g;
statusBar1.Text = String.Format(" Fitness = {0}", g.CurrentFitness.ToString("0.00"));
this.Text = String.Format("Sudoko - Generation {0}", i);
Invalidate();
_previousFitness = ToPercent(g.CurrentFitness);
}
if (g.CurrentFitness > .9999)
{
Console.WriteLine("Solution Final Generation {0}", i);
statusBar1.Text = "Terminer";
Console.WriteLine(g.ToString());
break;
}
}
}
}
abstract public void CopyGeneInfo(SudokuChromesome g);
abstract public SudokuChromesome Crossover(SudokuChromesome g);
public override SudokuChromesome Crossover(SudokuChromesome g)
{
Sudokufitness aGene1 = new Sudokufitness();
Sudokufitness aGene2 = new Sudokufitness();
g.CopyGeneInfo(aGene1);
g.CopyGeneInfo(aGene2);
Sudokufitness CrossingGene = (Sudokufitness)g;
if (TheSeed.Next(2) == 1)
{
for (int j = 0; j < 9; j++)
{
CrossoverPoint = TheSeed.Next(8) + 1;
for (int k = 0; k < CrossoverPoint; k++)
{
aGene1.TheArray[k, j] = CrossingGene.TheArray[k, j];
// aGene1.TheArray[8 - k,j] = TheArray[8-k, j];
aGene2.TheArray[k, j] = TheArray[k, j];
// aGene2.TheArray[8 - k ,j] = CrossingGene.TheArray[8 - k,j];
}
for (int k = CrossoverPoint; k < 9; k++)
{
aGene2.TheArray[k, j] = CrossingGene.TheArray[k, j];
// aGene1.TheArray[8 - k,j] = TheArray[8-k, j];
aGene1.TheArray[k, j] = TheArray[k, j];
// aGene2.TheArray[8 - k ,j] = CrossingGene.TheArray[8 - k,j];
}
}
}
else
{
for (int j = 0; j < 9; j++)
{
CrossoverPoint = TheSeed.Next(8) + 1;
for (int k = 0; k < CrossoverPoint; k++)
{
aGene1.TheArray[j, k] = CrossingGene.TheArray[j, k];
// aGene1.TheArray[8 - k,j] = TheArray[8-k, j];
aGene2.TheArray[j, k] = TheArray[j, k];
// aGene2.TheArray[8 - k ,j] = CrossingGene.TheArray[8 - k,j];
}
for (int k = CrossoverPoint; k < 9; k++)
{
aGene2.TheArray[j, k] = CrossingGene.TheArray[j, k];
// aGene1.TheArray[8 - k,j] = TheArray[8-k, j];
aGene1.TheArray[j, k] = TheArray[j, k];
// aGene2.TheArray[8 - k ,j] = CrossingGene.TheArray[8 - k,j];
}
}
}
/*
* SudokuGenome CrossingGene = (SudokuGenome)g;
* for (int i = 0; i < CrossoverPoint; i++)
* {
* for (int j = 0; j < CrossoverPoint; j++)
* {
* aGene1.TheArray[i,j] = CrossingGene.TheArray[i,j];
* aGene2.TheArray[i,j] = TheArray[i, j];
* }
* }
*
* for (int i = CrossoverPoint; i < 9; i++)
* for (int j = CrossoverPoint; j < 9; j++)
* {
* aGene1.TheArray[i,j] = TheArray[i,j];
* aGene2.TheArray[i,j] = CrossingGene.TheArray[i,j];
* }
*
* for (int i = CrossoverPoint; i < 9; i++)
* for (int j = 0; j < CrossoverPoint; j++)
* {
* aGene1.TheArray[i,j] = TheArray[i,j];
* aGene2.TheArray[i,j] = CrossingGene.TheArray[i,j];
* }
*
* for (int i = 0; i < CrossoverPoint; i++)
* for (int j = CrossoverPoint; j < 9; j++)
* {
* aGene1.TheArray[i,j] = CrossingGene.TheArray[i,j];
* aGene2.TheArray[i,j] = TheArray[i,j];
* }
*/
// 50/50 chance of returning gene1 or gene2
Sudokufitness aGene = null;
if (TheSeed.Next(2) == 1)
{
aGene = aGene1;
}
else
{
aGene = aGene2;
}
return(aGene);
}
