public NSGA2(int numParents, int populationSize)
{
PopulationSize = populationSize;
NumParents = numParents;
GenePool = new Solution[PopulationSize];
Parents = new Solution[numParents];
}
public Solution[] Tournament()
{
FitnessFunction(GenePool);
// Tournament and assign first front
var fronts = new List<List<Solution>>(NumFronts);
fronts.Add(new List<Solution>());
foreach (var solution in GenePool)
{
solution.DominatedSolutions = new List<Solution>();
solution.DominationCounter = 0;
foreach(var competitor in GenePool.Except(new List<Solution>() { solution }))
{
if(solution.Fitnesses.Average() > competitor.Fitnesses.Average())
{
solution.DominatedSolutions.Add(competitor);
}
else if(solution.Fitnesses.Average() < competitor.Fitnesses.Average())
{
solution.DominationCounter++;
}
}
if(solution.Rank == 0)
{
solution.Rank = 1;
fronts[0].Add(solution);
}
}
// Assign other fronts
for(var i = 0; i < NumFronts; i++)
{
foreach(var solution in fronts[i])
{
foreach(var domCompetitor in solution.DominatedSolutions)
{
domCompetitor.DominationCounter--;
if(domCompetitor.DominationCounter == 0)
{
domCompetitor.Rank = i + 1;
fronts[i + 1].Add(domCompetitor);
}
}
}
}
// Assign crowding distance
var numObjectives = fronts[0][0].Fitnesses.Count();
foreach (var front in fronts)
{
for(var m = 0; m < numObjectives; m++)
{
front.Sort((solA, solB) => solA.Fitnesses[m].CompareTo(solB.Fitnesses[m]));
var max = front.Max(sol => sol.Fitnesses[m]);
var min = front.Min(sol => sol.Fitnesses[m]);
var range = max - min;
for (var i = 1; i < front.Count -1; i++)
{
front[i].CrowdingDistance[m] += (front[i].Fitnesses[i + 1] - front[i].Fitnesses[i - 1]) / range;
}
}
}
// Select the best
var remaining = NumParents;
var nParents = new Solution[NumParents];
while (remaining != 0)
{
foreach (var front in fronts)
{
var startIndex = NumParents - remaining;
front.Sort((solA, solB) =>
{
if (solA.Rank < solB.Rank || ((solA.Rank == solB.Rank) && solA.CrowdingDistance.Average() > solB.CrowdingDistance.Average()))
{
return 1;
}
else if (solB.Rank > solA.Rank || ((solA.Rank == solB.Rank) && solA.CrowdingDistance.Average() > solB.CrowdingDistance.Average()))
{
return -1;
}
else
{
return 0;
}
});
if (front.Count >= remaining)
{
for (var i = 0; i < remaining; i++)
{
nParents[startIndex + i] = front[i];
}
}
else
{
for (var i = 0; i < remaining; i++)
{
nParents[startIndex + i] = front[i];
}
remaining -= front.Count;
}
}
}
return nParents;
}
