@Override
protected void iterate() {
Population offspring = new Population();
int populationSize = population.size();
while (offspring.size() < populationSize) {
Solution[] parents = selection.select(variation.getArity(), population);
Solution[] children = variation.evolve(parents);
offspring.addAll(children);
}
evaluateAll(offspring);
population.addAll(offspring);
fitnessEvaluator.evaluate(population);
while (population.size() > populationSize) {
int worstIndex = findWorstIndex();
fitnessEvaluator.removeAndUpdate(population, worstIndex);
}
}
/**
* Constructs a new IBEA instance.
*
* @param problem the problem
* @param archive the external archive; or {@code null} if no external archive is used
* @param initialization the initialization operator
* @param variation the variation operator
* @param fitnessEvaluator the indicator fitness evaluator to use (e.g., hypervolume
* additive-epsilon indicator)
*/
public IBEA(
Problem problem,
NondominatedPopulation archive,
Initialization initialization,
Variation variation,
IndicatorFitnessEvaluator fitnessEvaluator) {
super(problem, new Population(), archive, initialization);
this.variation = variation;
this.fitnessEvaluator = fitnessEvaluator;
fitnessComparator = new FitnessComparator(fitnessEvaluator.areLargerValuesPreferred());
selection = new TournamentSelection(fitnessComparator);
}
@Override
protected void initialize() {
super.initialize();
fitnessEvaluator.evaluate(population);
}
