public static void Improve(Permutation assignment, DoubleMatrix weights, DoubleMatrix distances, DoubleValue quality, IntValue localIterations, IntValue evaluatedSolutions, bool maximization, int maxIterations, CancellationToken cancellation)
{
for (int i = localIterations.Value; i < maxIterations; i++)
{
InversionMove bestMove = null;
double bestQuality = 0; // we have to make an improvement, so 0 is the baseline
double evaluations = 0.0;
foreach (var move in ExhaustiveInversionMoveGenerator.Generate(assignment))
{
double moveQuality = QAPInversionMoveEvaluator.Apply(assignment, move, weights, distances);
evaluations += 2 * (move.Index2 - move.Index1 + 1) / (double)assignment.Length;
if (maximization && moveQuality > bestQuality ||
!maximization && moveQuality < bestQuality)
{
bestQuality = moveQuality;
bestMove = move;
}
}
evaluatedSolutions.Value += (int)Math.Ceiling(evaluations);
if (bestMove == null)
{
break;
}
InversionManipulator.Apply(assignment, bestMove.Index1, bestMove.Index2);
quality.Value += bestQuality;
localIterations.Value++;
cancellation.ThrowIfCancellationRequested();
}
}
public static void Improve(Permutation assignment, DoubleMatrix distances, DoubleValue quality, IntValue localIterations, IntValue evaluatedSolutions, bool maximization, int maxIterations, DoubleArray probabilities, CancellationToken cancellation)
{
var distanceM = (DistanceMatrix)distances;
Func <int, int, double> distance = (a, b) => distanceM[a, b];
for (var i = localIterations.Value; i < maxIterations; i++)
{
InversionMove bestMove = null;
var bestQuality = quality.Value; // we have to make an improvement, so current quality is the baseline
var evaluations = 0.0;
foreach (var move in ExhaustiveInversionMoveGenerator.Generate(assignment))
{
var moveQuality = PTSPAnalyticalInversionMoveEvaluator.EvaluateMove(assignment, move, distance, probabilities);
evaluations++;
if (maximization && moveQuality > bestQuality ||
!maximization && moveQuality < bestQuality)
{
bestQuality = moveQuality;
bestMove = move;
}
}
evaluatedSolutions.Value += (int)Math.Ceiling(evaluations);
if (bestMove == null)
{
break;
}
InversionManipulator.Apply(assignment, bestMove.Index1, bestMove.Index2);
quality.Value = bestQuality;
localIterations.Value++;
cancellation.ThrowIfCancellationRequested();
}
}
public static void Improve(Permutation assignment, DoubleMatrix distances, DoubleValue quality, IntValue localIterations, IntValue evaluatedSolutions, bool maximization, int maxIterations, ItemList <BoolArray> realizations, CancellationToken cancellation)
{
var distanceM = (DistanceMatrix)distances;
Func <int, int, double> distance = (a, b) => distanceM[a, b];
for (var i = localIterations.Value; i < maxIterations; i++)
{
InversionMove bestMove = null;
double bestQuality = 0; // we have to make an improvement, so 0 is the baseline
double evaluations = 0.0;
foreach (var move in ExhaustiveInversionMoveGenerator.Generate(assignment))
{
double moveQuality = PTSPEstimatedInversionMoveEvaluator.EvaluateMove(assignment, move, distance, realizations);
evaluations += realizations.Count * 4.0 / (assignment.Length * assignment.Length);
if (maximization && moveQuality > bestQuality ||
!maximization && moveQuality < bestQuality)
{
bestQuality = moveQuality;
bestMove = move;
}
}
evaluatedSolutions.Value += (int)Math.Ceiling(evaluations);
if (bestMove == null)
{
break;
}
InversionManipulator.Apply(assignment, bestMove.Index1, bestMove.Index2);
quality.Value += bestQuality;
localIterations.Value++;
cancellation.ThrowIfCancellationRequested();
}
}
