/// <summary>
/// Perform DE crossover.
/// </summary>
/// <param name="crossover">Crossover variant to be performed.</param>
/// <param name="CR">Crossover probability.</param>
/// <param name="n">Dimensionality for problem.</param>
/// <param name="w">Differential weight (vector).</param>
/// <param name="x">Current agent position.</param>
/// <param name="y">Potentially new agent position.</param>
/// <param name="g">Population's best known position.</param>
/// <param name="agents">Entire population.</param>
/// <param name="randomSet">Random-set used for drawing distinct agents.</param>
public static void DoCrossover(Variant crossover, double CR, int n, double[] w, double[] x, ref double[] y, double[] g, double[][] agents, RandomOps.Set randomSet)
{
// Agents used in crossover.
double[] a, b, c;
switch (crossover)
{
case Variant.Best1Bin:
{
// The first agent used in crossover is g.
a = g;
// Pick random and distinct agent-indices.
// Also distinct from agent x.
int R1 = randomSet.Draw();
int R2 = randomSet.Draw();
b = agents[R1];
c = agents[R2];
}
break;
case Variant.Rand1Bin:
default:
{
// Pick random and distinct agent-indices.
// Also distinct from agent x.
int R1 = randomSet.Draw();
int R2 = randomSet.Draw();
int R3 = randomSet.Draw();
// Refer to the randomly picked agents as a and b.
a = agents[R1];
b = agents[R2];
c = agents[R3];
}
break;
}
// Pick a random dimension.
int R = Globals.Random.Index(n);
// Compute potentially new position.
for (int k = 0; k < n; k++)
{
if (k == R || Globals.Random.Bool(CR))
{
y[k] = a[k] + w[k] * (b[k] - c[k]);
}
else
{
y[k] = x[k];
}
}
}
