public void postGeneration() {
// Create the solutionSet union of solutionSet and offSpring
union_ = ((SolutionSet) population_).union(offspringPopulation_);
// Ranking the union
Ranking ranking = new Ranking(union_);
if (ranking.getNumberOfSubfronts() == 0) System.out.println("No hay subfrentes!!");
int remain = populationSize_;
int index = 0;
SolutionSet front = null;
population_.clear();
// Obtain the next front
front = ranking.getSubfront(index);
while ((remain > 0) && (remain >= front.size())) {
// Assign crowding distance to individuals
distance_.crowdingDistanceAssignment(front, problem_.getNumberOfObjectives());
// Add the individuals of this front
for (int k = 0; k < front.size(); k++) {
population_.add(front.get(k));
} // for
// Decrement remain
remain = remain - front.size();
// Obtain the next front
index++;
if (remain > 0) {
front = ranking.getSubfront(index);
} // if
} // while
// Remain is less than front(index).size, insert only the best one
if (remain > 0) { // front contains individuals to insert
distance_.crowdingDistanceAssignment(front, problem_.getNumberOfObjectives());
front.sort(new jmetal.coevolutionary.base.operator.comparator.CrowdingComparator());
for (int k = 0; k < remain; k++) {
population_.add(front.get(k));
} // for
remain = 0;
} // if
// This piece of code shows how to use the indicator object into the code
// of NSGA-II. In particular, it finds the number of evaluations required
// by the algorithm to obtain a Pareto front with a hypervolume higher
// than the hypervolume of the true Pareto front.
if ((indicators_ != null) && (requiredEvaluations_ == 0)) {
double HV = indicators_.getHypervolume(population_);
if (HV >= (0.98 * indicators_.getTrueParetoFrontHypervolume())) {
requiredEvaluations_ = evaluations_;
} // if
} // if
prepareBestSolutions();
} // postGeneration