@Override
public void performIteration(PSO algorithm) {
delegate.performIteration(algorithm);
Topology<Particle> topology = algorithm.getTopology();
// calculate vAvg
Vector avgV =
Vectors.mean(
Lists.transform(
topology,
new Function<Particle, Vector>() {
@Override
public Vector apply(Particle f) {
return (Vector) f.getVelocity();
}
}));
Vector.Builder builder = Vector.newBuilder();
for (Numeric n : avgV) {
if (Math.abs(n.doubleValue()) > vMax.getParameter()) {
builder.add(vMax.getParameter());
} else {
builder.add(n);
}
}
avgV = builder.build();
// mutation
Particle gBest = Topologies.getBestEntity(topology, new SocialBestFitnessComparator());
Particle mutated = gBest.getClone();
Vector pos = (Vector) gBest.getBestPosition();
final Bounds bounds = pos.boundsOf(0);
pos =
pos.plus(
avgV.multiply(
new Supplier<Number>() {
@Override
public Number get() {
return distribution.getRandomNumber() * bounds.getRange()
+ bounds.getLowerBound();
}
}));
mutated.setCandidateSolution(pos);
mutated.calculateFitness();
if (gBest.getBestFitness().compareTo(mutated.getFitness()) < 0) {
gBest.getProperties().put(EntityType.Particle.BEST_FITNESS, mutated.getBestFitness());
gBest.getProperties().put(EntityType.Particle.BEST_POSITION, mutated.getBestPosition());
}
}
