/*
* Selects among the feasible and infeasible solutions
* @param iterable This is the iterable container holding the solutions among which one must be selected
* @return a PartialSelection holding the objects retrieved
*/
@Override
public PartialSelection<E> on(Iterable<E> iterable) {
E bestIndividual = iterable.iterator().next();
E temp;
double difference;
ArrayList feasibleEntities = new ArrayList();
ArrayList inFeasibleEntities = new ArrayList();
E winningIndividual;
EuclideanDistanceMeasure euclideanDistanceMeasure = new EuclideanDistanceMeasure();
for (E current : iterable) {
temp = (E) current.getClone();
constraint.enforce(temp);
difference = euclideanDistanceMeasure.distance(temp.getPosition(), current.getPosition());
if (difference == 0) {
feasibleEntities.add(current);
} else {
ExtendedIndividual newIndividual = new ExtendedIndividual();
newIndividual.setIndividual(current);
newIndividual.setSumOfConstrainViolation(difference);
inFeasibleEntities.add(newIndividual);
}
}
if (feasibleEntities.size() > 0) {
return Selection.copyOf(Arrays.asList(selectBestOfFeasible(feasibleEntities)));
}
return Selection.copyOf(Arrays.asList(selectBestOfInfeasible(inFeasibleEntities)));
}
/*
* Selects the individual with the lowest sum of constraint violation among a set of infeasible solutions
*@param iterable The set of infeasible solutions
*@return The best individual among these infeasible solutions
*/
protected E selectBestOfInfeasible(Iterable<ExtendedIndividual> iterable) {
E bestIndividual = iterable.iterator().next().getIndividual();
ExtendedIndividual temp;
double sumOfConstraintViolation = Double.POSITIVE_INFINITY;
double sumPerDimension;
Vector difference;
for (ExtendedIndividual current : iterable) {
sumPerDimension = current.getSumOfConstrainViolation();
if (sumPerDimension < sumOfConstraintViolation) {
bestIndividual = (E) current.getIndividual().getClone();
sumOfConstraintViolation = sumPerDimension;
}
}
return bestIndividual;
}
