public int LeastContributer(IReadOnlyList <Individual> front, MultiObjectiveBasicProblem <RealVectorEncoding> problem)
{
var bounds = problem.Encoding.Bounds;
var extracted = front.Select(x => x.PenalizedFitness).ToArray();
if (extracted.Length <= 2)
{
return(0);
}
var pointsums = new double[extracted.Length];
for (var dim = 0; dim < problem.Maximization.Length; dim++)
{
var arr = extracted.Select(x => x[dim]).ToArray();
Array.Sort(arr);
var fmax = problem.Encoding.Bounds[dim % bounds.Rows, 1];
var fmin = bounds[dim % bounds.Rows, 0];
var pointIdx = 0;
foreach (var point in extracted)
{
var pos = Array.BinarySearch(arr, point[dim]);
var d = pos != 0 && pos != arr.Length - 1 ? (arr[pos + 1] - arr[pos - 1]) / (fmax - fmin) : double.PositiveInfinity;
pointsums[pointIdx] += d;
pointIdx++;
}
}
return(pointsums.Select((value, index) => new { value, index }).OrderBy(x => x.value).First().index);
}
public int LeastContributer(IReadOnlyList <Individual> front, MultiObjectiveBasicProblem <RealVectorEncoding> problem)
{
var frontCopy = front.Select(x => x.PenalizedFitness).ToList();
if (frontCopy.Count <= 1)
{
return(0);
}
var p = problem as MultiObjectiveTestFunctionProblem;
var refPoint = BuildReferencePoint(p != null ? frontCopy.Concat(new[] { p.ReferencePoint.CloneAsArray() }) : frontCopy, problem.Maximization);
var contributions = Enumerable.Range(0, frontCopy.Count).Select(i => Contribution(frontCopy, i, problem.Maximization, refPoint));
return(contributions.Select((value, index) => new { value, index }).OrderBy(x => x.value).First().index);
}
public int LeastContributer(IReadOnlyList <Individual> front, MultiObjectiveBasicProblem <RealVectorEncoding> problem)
{
var extracted = front.Select(x => x.PenalizedFitness).ToArray();
if (extracted.Length <= 2)
{
return(0);
}
var distances = CalcDistances(extracted);
var mindexI = 0;
var mindexJ = 0;
var min = double.MaxValue;
for (var i = 0; i < extracted.Length; i++)
{
var d = double.MaxValue;
var minj = 0;
for (var j = 0; j < extracted.Length; j++)
{
if (i == j)
{
continue;
}
var d1 = distances[i, j];
if (!(d1 < d))
{
continue;
}
minj = j;
d = d1;
}
if (!(d < min))
{
continue;
}
min = d;
mindexI = i;
mindexJ = minj;
}
//break tie with distance to second nearest
var minI = double.MaxValue;
var minJ = double.MaxValue;
for (var i = 0; i < extracted.Length; i++)
{
double d;
if (mindexI != i)
{
d = distances[mindexI, i];
if (!d.IsAlmost(min))
{
minI = Math.Min(minI, d);
}
}
if (mindexJ == i)
{
continue;
}
d = distances[mindexJ, i];
if (!d.IsAlmost(min))
{
minJ = Math.Min(minJ, d);
}
}
//find min
return(minI < minJ ? mindexI : mindexJ);
}
