public void BuildArchive(IEvolutionState state, IList <Individual> oldInds, IList <Individual> newInds, int archiveSize)
{
// step 1: load the archive with the pareto-nondominated front
var archive = new List <Individual>();
var nonFront = new List <Individual>();
MultiObjectiveFitness.PartitionIntoParetoFront(oldInds, archive, nonFront);
var currentArchiveSize = archive.Count;
// step 2: if the archive isn't full, load the remainder with the fittest individuals (using customFitnessMetric) that aren't in the archive yet
if (currentArchiveSize < archiveSize)
{
// BRS : The following uses Individual's IComparable implementation based on Fitness.
// The fitter individuals will be earlier
nonFront.SortByFitnessDescending();
var len = archiveSize - currentArchiveSize;
for (var i = 0; i < len; i++)
{
archive.Add(nonFront[i]);
currentArchiveSize++;
}
}
// step 3: if the archive is OVERFULL, iterate as follows:
// step 3a: remove the k-closest individual in the archive
//var evaluator = ((ISPEA2Evaluator)(state.Evaluator));
//var inds = archive.ToArray();
while (currentArchiveSize > archiveSize)
{
var closest = archive[0];
var closestIndex = 0;
var closestD = CalculateDistancesFromIndividual(closest, oldInds);
for (var i = 1; i < currentArchiveSize; i++)
{
var competitor = archive[i];
var competitorD = CalculateDistancesFromIndividual(competitor, oldInds);
for (var k = 0; k < oldInds.Count; k++)
{
if (closestD[i] > competitorD[i])
{
closest = competitor;
closestD = competitorD;
closestIndex = k;
break;
}
else if (closestD[i] < competitorD[i])
{
break;
}
}
}
// remove him destructively -- put the top guy in his place and remove the top guy. This is O(1)
archive[closestIndex] = archive[archive.Count - 1];
archive.RemoveAt(archive.Count - 1);
currentArchiveSize--;
}
// step 4: put clones of the archive in the new individuals
var arr = archive.ToArray();
for (var i = 0; i < archiveSize; i++)
{
newInds[newInds.Count - archiveSize + i] = (Individual)arr[i].Clone();
}
}
