public void Crossover(ref Genome genome2, out Genome child1, out Genome child2)
{
int pos = (int)(m_random.NextDouble() * (double)m_length);
child1 = new Genome(m_length, false);
child2 = new Genome(m_length, false);
// Array.Copy is the same speed (fraction slower) than iterating over the array.
/*// Copy first half for child1 with random genes, second half with parent genes.
Array.Copy(m_genes, 0, child1.m_genes, 0, pos);
Array.Copy(genome2.m_genes, pos, child1.m_genes, pos, m_length - pos);
// Copy first half for child2 with parent genes, second half with random genes.
Array.Copy(genome2.m_genes, 0, child2.m_genes, 0, pos);
Array.Copy(m_genes, pos, child2.m_genes, pos, m_length - pos);*/
for (int i = 0; i < m_length; i++)
{
if (i < pos)
{
child1.m_genes[i] = m_genes[i];
child2.m_genes[i] = genome2.m_genes[i];
}
else
{
child1.m_genes[i] = genome2.m_genes[i];
child2.m_genes[i] = m_genes[i];
}
}
}
/// <summary>
/// Create the *initial* genomes by repeated calling the supplied fitness function
/// </summary>
private void CreateGenomes()
{
for (int i = 0; i < GAParams.PopulationSize; i++)
{
Genome g = new Genome(GAParams.GenomeSize);
GAParams.ThisGeneration.Add(g);
}
}
public Genome DeepCopy()
{
Genome g = new Genome(m_length, false);
Array.Copy(m_genes, g.m_genes, m_length);
return g;
}
