@Override
public Topology<Particle> f(PSO pso) {
Topology<Particle> newTopology = pso.getTopology().getClone();
newTopology.clear();
for (Particle p : pso.getTopology()) {
newTopology.add(function.f(p));
}
return newTopology;
}
/*
* Performs an iteration of the standard co-operative algorithm.
* It holds a context particle, adapts the swarms to hold the context particle
* with the appropriate dimension difference,updates the personal and global
* bests and then updates the particles.
*/
@Override
public void performIteration(CooperativePSO algorithm) {
int populationIndex = 0;
table = new StandardDataTable();
DataClusteringPSO pso;
Topology newTopology;
ClusterParticle particleWithContext;
for (PopulationBasedAlgorithm currentAlgorithm : algorithm.getPopulations()) {
table =
((SinglePopulationDataClusteringIterationStrategy)
((DataClusteringPSO) currentAlgorithm).getIterationStrategy())
.getDataset();
if (!contextinitialised) {
initialiseContextParticle(algorithm);
}
pso = ((DataClusteringPSO) currentAlgorithm);
newTopology = ((DataClusteringPSO) currentAlgorithm).getTopology().getClone();
newTopology.clear();
for (ClusterParticle particle : ((DataClusteringPSO) currentAlgorithm).getTopology()) {
clearDataPatterns(contextParticle);
assignDataPatternsToParticle(
(CentroidHolder) contextParticle.getCandidateSolution(), table);
contextParticle.calculateFitness();
particleWithContext = new ClusterParticle();
particleWithContext.setCandidateSolution(contextParticle.getCandidateSolution().getClone());
particleWithContext
.getProperties()
.put(EntityType.Particle.BEST_POSITION, particle.getBestPosition().getClone());
particleWithContext
.getProperties()
.put(EntityType.Particle.BEST_FITNESS, particle.getBestFitness().getClone());
particleWithContext
.getProperties()
.put(EntityType.Particle.VELOCITY, particle.getVelocity().getClone());
particleWithContext.setNeighbourhoodBest(particle.getNeighbourhoodBest());
((CentroidHolder) particleWithContext.getCandidateSolution())
.set(
populationIndex,
((CentroidHolder) particle.getCandidateSolution()).get(populationIndex));
particleWithContext
.getProperties()
.put(
EntityType.Particle.Count.PBEST_STAGNATION_COUNTER,
particle
.getProperties()
.get(EntityType.Particle.Count.PBEST_STAGNATION_COUNTER)
.getClone());
particleWithContext.setCentroidInitialisationStrategy(
particle.getCentroidInitialisationStrategyCandidate().getClone());
clearDataPatterns(particleWithContext);
assignDataPatternsToParticle(
(CentroidHolder) particleWithContext.getCandidateSolution(), table);
particleWithContext.calculateFitness();
if (particleWithContext.getFitness().compareTo(particleWithContext.getBestFitness()) > 0) {
particle.getProperties().put(EntityType.Particle.BEST_POSITION, particle.getPosition());
particle.getProperties().put(EntityType.Particle.BEST_FITNESS, particle.getFitness());
particleWithContext
.getProperties()
.put(EntityType.Particle.BEST_POSITION, particle.getPosition());
particleWithContext
.getProperties()
.put(EntityType.Particle.BEST_FITNESS, particle.getFitness());
}
if (particleWithContext.getBestFitness().compareTo(contextParticle.getFitness()) > 0) {
((CentroidHolder) contextParticle.getCandidateSolution())
.set(
populationIndex,
((CentroidHolder) particle.getCandidateSolution()).get(populationIndex));
}
if (contextParticle.getFitness().compareTo(contextParticle.getBestFitness()) > 0) {
contextParticle
.getProperties()
.put(EntityType.Particle.BEST_POSITION, contextParticle.getPosition())
.getClone();
contextParticle
.getProperties()
.put(EntityType.Particle.BEST_FITNESS, contextParticle.getFitness())
.getClone();
}
newTopology.add(particleWithContext);
}
if (elitist) {
contextParticle
.getProperties()
.put(EntityType.CANDIDATE_SOLUTION, contextParticle.getBestPosition().getClone());
contextParticle
.getProperties()
.put(EntityType.FITNESS, contextParticle.getBestFitness().getClone());
}
pso.setTopology(newTopology);
pso.performIteration();
populationIndex++;
}
}
