@Before
public void setUp() throws Exception {
FunctionMinimisationProblem problem = new FunctionMinimisationProblem();
problem.setDomain("R(-5.0, 5.0)^5");
problem.setFunction(new Rastrigin());
StoppingCondition condition = new MaximumIterations(2);
abc = new ABC();
ClonedPopulationInitialisationStrategy initStrategy =
new ClonedPopulationInitialisationStrategy();
initStrategy.setEntityNumber(10);
WorkerBee bee = new WorkerBee();
initStrategy.setEntityType(bee);
abc.setForageLimit(new ConstantControlParameter(-1));
abc.setInitialisationStrategy(initStrategy);
abc.setWorkerBeePercentage(new ConstantControlParameter(0.5));
abc.addStoppingCondition(condition);
abc.setOptimisationProblem(problem);
abc.initialise();
}
private void updateVPs() {
if (this.getIterations() == 0) {
try {
FunctionMaximisationProblem prob =
(FunctionMaximisationProblem) this.getOptimisationProblem();
function = (ContinuousFunction) prob.getFunction();
isMax = true;
} catch (ClassCastException e) {
FunctionMinimisationProblem prob =
(FunctionMinimisationProblem) this.getOptimisationProblem();
function = (ContinuousFunction) prob.getFunction();
isMax = false;
} finally {
double s;
for (VBParticle p : mainSwarm.getTopology()) {
p.calculateFitness();
Vector random = (Vector) p.getPosition().getClone();
random.randomize(randomProvider);
s = function.apply(random);
if (isMax) {
if (s > p.getFitness().getValue()) {
p.setPersonalBest(random);
} else {
p.setPersonalBest(p.getPosition());
p.setPosition(random);
}
} else {
if (s < p.getFitness().getValue()) {
p.setPersonalBest(random);
} else {
p.setPersonalBest(p.getPosition());
p.setPosition(random);
}
}
p.setNeighbourhoodBest(p.getClone());
p.calculateVP();
}
}
}
}