public void AssignCrowdingDistance_InfiniteReferencePoint_Works()
{
ParetoFrontMetrics.AssignCrowdingDistance(new[]
{ moTestInd, indParetoEqual1, indParetoEqual2, indParetoEqual3 },
"crowdingDistance",
minimise,
moTestInd.SolutionVector.Select(i => double.MaxValue));
Assert.True(moTestInd.GetProperty <double>("crowdingDistance") > 1e300);
Assert.True(indParetoEqual1.GetProperty <double>("crowdingDistance") > 1e300);
// Crowding distance should be 0.09/0.1 + 0.18/0.2 + 0.09/0.1
Assert.True(Math.Abs(indParetoEqual2.GetProperty <double>("crowdingDistance") - 2.7) < 1e-6);
Assert.True(indParetoEqual3.GetProperty <double>("crowdingDistance") > 1e300);
}
public void AssignCrowdingDistance_InsideReferencePoint_Works()
{
ParetoFrontMetrics.AssignCrowdingDistance(new[]
{ moTestInd, indParetoEqual1, indParetoEqual2, indParetoEqual3 },
"crowdingDistance",
minimise,
new[] { WorstSolution1 + 0.1, WorstSolution2 - 0.02, WorstSolution3 + 0.1 });
// Best for objective 3
Assert.True(moTestInd.GetProperty <double>("crowdingDistance") > 1e300);
// Out of bounds on objective 2
Assert.Equal(0.0, indParetoEqual1.GetProperty <double>("crowdingDistance"));
// Crowding distance should be 0.09/0.1 + 0.16/0.18 + 0.09/0.1
Assert.True(Math.Abs(indParetoEqual2.GetProperty <double>("crowdingDistance") - 2.68888889) < 1e-6);
// Best for objective 2
Assert.True(indParetoEqual3.GetProperty <double>("crowdingDistance") > 1e300);
}
/// <summary>
/// Performs the fitness calculation based on:
/// 1) Non-dominated sorting into Pareto Fronts;
/// 2) Crowding distance assignment and comparison
/// </summary>
/// <remarks>
/// If the number of individuals provided is less than the population size provided in the constructor,
/// then only a simple fitness assignment is performed (assumes this is used during initial population
/// creation: <see cref="EvolutionaryAlgorithm"/>).
/// </remarks>
/// <param name="individuals">All individuals to be considered for fitness calculation.</param>
public void CalculateAndAssignFitness(IEnumerable <Individual> individuals)
{
var inds = individuals as Individual[] ?? individuals.ToArray();
if (inds.Length <= populationSize)
{
// Don't bother with Pareto Front calculation, it's too time consuming.
// Just assign sum of ranks on each objective.
for (var m = 0; m < inds[0].SolutionVector.Length; m++)
{
var individualsOrderedByThisObjective = inds.OrderBy(i => i.SolutionVector.ElementAt(m) * (minimise[m] ? 1 : -1)).ToArray();
for (int o = 0; o < individualsOrderedByThisObjective.Count(); o++)
{
individualsOrderedByThisObjective[o].SetFitness(o + individualsOrderedByThisObjective[o].Fitness);
}
}
return;
}
if (useReferencePoint & double.IsInfinity(referencePoint.ElementAt(0)))
{
// Calculate a reference point
for (var m = 0; m < inds[0].SolutionVector.Length; m++)
{
// Use the worst value found for each objective, after the initial population generation.
referencePoint[m] = minimise[m]
? inds.Max(i => i.SolutionVector.ElementAt(m))
: inds.Min(i => i.SolutionVector.ElementAt(m));
}
}
// Calculate Pareto Fronts
sorter.PerformSort(inds, minimise);
// Go through, assigning fitness
var paretoFront = 1;
var currentParetoFront = inds.Where(i => i.GetProperty <int>(OptimiserPropertyNames.ParetoFront) == paretoFront).ToArray();
var individualsAssessed = 0;
while (currentParetoFront.Length > 0)
{
foreach (var ind in currentParetoFront)
{
ind.SetFitness(paretoFront);
}
if (individualsAssessed < populationSize && individualsAssessed + currentParetoFront.Length > populationSize)
{
// We're in the Pareto Front which partially overlaps with the population size.
// Perform crowding distance assignment
ParetoFrontMetrics.AssignCrowdingDistance(currentParetoFront, CrowdingDistance,
minimise, referencePoint);
var sortedParetoFront = currentParetoFront
.OrderByDescending(i => i.GetProperty <double>(CrowdingDistance))
.ToArray();
var crowdingComparison = 0.0;
for (int i = 1; i < sortedParetoFront.Length; i++)
{
if (sortedParetoFront[i - 1].GetProperty <double>(CrowdingDistance) >
sortedParetoFront[i].GetProperty <double>(CrowdingDistance))
{
crowdingComparison += 1.0 / (currentParetoFront.Length + 10.0); // Small enough that we won't end up more than 1 in total...
}
sortedParetoFront[i].SetFitness(sortedParetoFront[i].Fitness + crowdingComparison);
}
}
individualsAssessed += currentParetoFront.Length;
// Get next Pareto Front
paretoFront++;
currentParetoFront = inds.Where(i => i.GetProperty <int>(OptimiserPropertyNames.ParetoFront) == paretoFront).ToArray();
}
}
