public DoubleVectorIndividual createIndividual(
final EvolutionState state, int subpop, int index, int thread) {
Individual[] inds = state.population.subpops[subpop].individuals;
DoubleVectorIndividual v =
(DoubleVectorIndividual)
(state.population.subpops[subpop].species.newIndividual(state, thread));
int retry = -1;
do {
retry++;
// select three indexes different from each other and from that of the current parent
int r0, r1, r2;
// do
{
r0 = bestSoFarIndex[subpop];
}
// while( r0 == index );
do {
r1 = state.random[thread].nextInt(inds.length);
} while (r1 == r0 || r1 == index);
do {
r2 = state.random[thread].nextInt(inds.length);
} while (r2 == r1 || r2 == r0 || r2 == index);
DoubleVectorIndividual g0 = (DoubleVectorIndividual) (inds[r0]);
DoubleVectorIndividual g1 = (DoubleVectorIndividual) (inds[r1]);
DoubleVectorIndividual g2 = (DoubleVectorIndividual) (inds[r2]);
for (int i = 0; i < v.genome.length; i++)
v.genome[i] =
g0.genome[i]
+ (F + state.random[thread].nextDouble() * F_NOISE - (F_NOISE / 2.0))
* (g1.genome[i] - g2.genome[i]);
} while (!valid(v) && retry < retries);
if (retry >= retries && !valid(v)) // we reached our maximum
{
// completely reset and be done with it
v.reset(state, thread);
}
return crossover(state, (DoubleVectorIndividual) (inds[index]), v, thread);
}
/** Make a copy of the BitVectorIndividual. */
public Object clone() {
DoubleVectorIndividual tmp = (DoubleVectorIndividual) (super.clone());
tmp.genome = (double[]) genome.clone();
tmp.genome_size = genome_size;
return tmp;
}