private ChromosomeVector ProportionalCrossover(ChromosomeVector parentA, ChromosomeVector parentB)
{
double fitnessA = Math.Abs(1 / _equation(parentA));
double fitnessB = Math.Abs(1 / _equation(parentB));
double probabilityA = fitnessA / (fitnessA + fitnessB);
double probabilityB = 1 - probabilityA;
ChromosomeVector child = new ChromosomeVector();
for (int i = 0; i < ChromosomeVector.Length; i++)
{
double probability = Random.NextDouble();
if (probability < probabilityA)
{
if (probability < probabilityB)
{
child[i] = probabilityA >= probabilityB ? parentA[i] : parentB[i];
}
else
{
child[i] = parentA[i];
}
}
else
{
child[i] = parentB[i];
}
}
return(child);
}
private List <ChromosomeVector> Crossover(List <ChromosomeVector> parents)
{
var children = new List <ChromosomeVector>();
while (children.Count < _childrenAmount)
{
// removing self-crossover ?
var(parentAIndex, parentBIndex) = (0, 0);
while (parentAIndex == parentBIndex)
{
(parentAIndex, parentBIndex) = (Random.Next(parents.Count), Random.Next(parents.Count));
}
ChromosomeVector child = ProportionalCrossover(parents[parentAIndex], parents[parentBIndex]);
children.Add(child);
}
return(children);
}
public static int EquationA(ChromosomeVector chromosome)
{
var(u, w, x, y, z) = (chromosome.U, chromosome.W, chromosome.X, chromosome.Y, chromosome.Z);
return(Math.Abs(((w * w) * x * (y * y) * z) + ((w * w) * (x * x) * (y * y) * z) + ((u * u) * w * x) + ((w * w) * (x * x) * (y * y) * (z * z)) + (y * z) + 5));
}
public static int EquationExtra(ChromosomeVector chromosome)
{
var(u, w, x, y, z) = (chromosome.U, chromosome.W, chromosome.X, chromosome.Y, chromosome.Z);
return(Math.Abs(-22 + ((y * y) + (w * w * z) + (w * y * z) + (u * (z * z) + (u * w * (x * x) * (y * y) * (z * z))))));
}
public static int EquationB(ChromosomeVector chromosome)
{
var(u, w, x, y, z) = (chromosome.U, chromosome.W, chromosome.X, chromosome.Y, chromosome.Z);
return(Math.Abs(z + (u * x * y) + ((w * w) * x * (z * z)) + (w * (x * x) * (z * z)) + ((u * u) * (x * x) * y * (z * z)) + 50));
}
