@Override
public Vector get(Particle particle) {
Vector localGuide = (Vector) particle.getLocalGuide(); // personal best (yi)
Vector globalGuide = (Vector) particle.getGlobalGuide(); // global best (y^i)
Vector.Builder builder = Vector.newBuilder();
for (int i = 0; i < particle.getDimension(); ++i) {
// double tmp1 = cognitive.getParameter();
// double tmp2 = social.getParameter();
double sigma = Math.abs(localGuide.doubleValueOf(i) - globalGuide.doubleValueOf(i));
if (sigma == 0) {
sigma = 1;
}
// System.out.println("Sigma: "+sigma);
// according to Kennedy
double mean = (localGuide.doubleValueOf(i) + globalGuide.doubleValueOf(i)) / 2;
// andries proposal: double mean = (tmp1*personalBestPosition.getReal(i) +
// tmp2*nBestPosition.getReal(i)) / (tmp1+tmp2);
if (Rand.nextDouble() < p) {
builder.add(
localGuide.doubleValueOf(i) + this.cauchyDistribution.getRandomNumber(mean, sigma));
} else {
builder.add(
globalGuide.doubleValueOf(i) + this.gaussianDistribution.getRandomNumber(mean, sigma));
}
}
return builder.build();
}
/** {@inheritDoc} */
@Override
public void randomise() {
double tmp =
Rand.nextDouble() * (getBounds().getUpperBound() - getBounds().getLowerBound())
+ getBounds().getLowerBound();
this.value = Double.valueOf(tmp).intValue();
}
@Override
public Vector get(Particle particle) {
Vector velocity = (Vector) particle.getVelocity();
Vector position = (Vector) particle.getPosition();
PSO algorithm = (PSO) AbstractAlgorithm.get();
int ns = (int) nSize.getParameter();
fj.data.List<Particle> neighbours =
algorithm
.getTopology()
.sort(
Ord.ord(
VectorBasedFunctions.sortByDistance(particle, new EuclideanDistanceMeasure())))
.take(ns);
Vector.Builder builder = Vector.newBuilder();
for (int i = 0; i < particle.getDimension(); ++i) {
double informationSum = 0.0;
double randomSum = 0;
for (Particle currentTarget : neighbours) {
Vector currentTargetPosition = (Vector) currentTarget.getBestPosition();
double randomComponent = Rand.nextDouble() * (4.1 / ns);
informationSum += randomComponent * currentTargetPosition.doubleValueOf(i);
randomSum += randomComponent;
}
double value =
inertiaWeight.getParameter()
* (velocity.doubleValueOf(i)
+ randomSum * ((informationSum / (ns * randomSum) - position.doubleValueOf(i))));
builder.add(value);
}
return builder.build();
}
