public void EvaluateAndLoadAssignment(int[] assignment)
{
if (assignment == null || assignment.Length == 0)
{
return;
}
var vector = new Permutation(PermutationTypes.Absolute, assignment);
var result = QAPEvaluator.Apply(vector, Weights, Distances);
BestKnownQuality = new DoubleValue(result);
BestKnownSolution = vector;
BestKnownSolutions = new ItemSet <Permutation>();
BestKnownSolutions.Add((Permutation)vector.Clone());
}
private void UpdateParameterValues()
{
Permutation lbSolution;
// calculate the optimum of a LAP relaxation and use it as lower bound of our QAP
LowerBound = new DoubleValue(GilmoreLawlerBoundCalculator.CalculateLowerBound(Weights, Distances, out lbSolution));
// evalute the LAP optimal solution as if it was a QAP solution
var lbSolutionQuality = QAPEvaluator.Apply(lbSolution, Weights, Distances);
// in case both qualities are the same it means that the LAP optimum is also a QAP optimum
if (LowerBound.Value.IsAlmost(lbSolutionQuality))
{
BestKnownSolution = lbSolution;
BestKnownQuality = new DoubleValue(LowerBound.Value);
}
AverageQuality = new DoubleValue(ComputeAverageQuality());
}
protected QAPEvaluator(QAPEvaluator original, Cloner cloner) : base(original, cloner) { }
protected QAPEvaluator(QAPEvaluator original, Cloner cloner) : base(original, cloner)
{
}
