private TwoPointFiveMove(TwoPointFiveMove original, Cloner cloner)
: base(original, cloner) {
this.Index1 = original.Index1;
this.Index2 = original.Index2;
this.IsInvert = original.IsInvert;
this.Permutation = cloner.Clone(original.Permutation);
}
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++)
{
TwoPointFiveMove 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 ExhaustiveTwoPointFiveMoveGenerator.Generate(assignment))
{
var moveQuality = PTSPAnalyticalTwoPointFiveMoveEvaluator.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;
}
TwoPointFiveMoveMaker.Apply(assignment, bestMove);
quality.Value = bestQuality;
localIterations.Value++;
cancellation.ThrowIfCancellationRequested();
}
}
public static TwoPointFiveMove[] Apply(Permutation permutation, IRandom random, int sampleSize) {
var moves = new TwoPointFiveMove[sampleSize];
for (var i = 0; i < sampleSize; i++) {
moves[i] = StochasticTwoPointFiveSingleMoveGenerator.Apply(permutation, random);
}
return moves;
}
public static void Apply(Permutation permutation, TwoPointFiveMove move) {
if (move.IsInvert) {
InversionManipulator.Apply(permutation, move.Index1, move.Index2);
} else {
TranslocationManipulator.Apply(permutation, move.Index1, move.Index1, move.Index2);
}
}
public static TwoPointFiveMove[] Apply(Permutation permutation, IRandom random, int sampleSize) {
var moves = new TwoPointFiveMove[sampleSize];
for (var i = 0; i < sampleSize; i++) {
moves[i] = StochasticTwoPointFiveSingleMoveGenerator.Apply(permutation, random);
}
return moves;
}
private TwoPointFiveMove(TwoPointFiveMove original, Cloner cloner)
: base(original, cloner)
{
this.Index1 = original.Index1;
this.Index2 = original.Index2;
this.IsInvert = original.IsInvert;
this.Permutation = cloner.Clone(original.Permutation);
}
public static double EvaluateMove(Permutation permutation, TwoPointFiveMove move, Func<int, int, double> distance, ItemList<BoolArray> realizations) {
if (move.IsInvert) {
return PTSPEstimatedInversionMoveEvaluator.EvaluateMove(permutation,
new InversionMove(move.Index1, move.Index2, move.Permutation), distance, realizations);
} else {
return PTSPEstimatedInsertionMoveEvaluator.EvaluateMove(permutation,
new TranslocationMove(move.Index1, move.Index1, move.Index2), distance, realizations);
}
}
public static double EvaluateMove(Permutation permutation, TwoPointFiveMove move, Func<int, int, double> distance, DoubleArray probabilities) {
if (move.IsInvert) {
return PTSPAnalyticalInversionMoveEvaluator.EvaluateMove(permutation,
new InversionMove(move.Index1, move.Index2, move.Permutation), distance, probabilities);
} else {
return PTSPAnalyticalInsertionMoveEvaluator.EvaluateMove(permutation,
new TranslocationMove(move.Index1, move.Index1, move.Index2), distance, probabilities);
}
}
public static void Apply(Permutation permutation, TwoPointFiveMove move)
{
if (move.IsInvert)
{
InversionManipulator.Apply(permutation, move.Index1, move.Index2);
}
else
{
TranslocationManipulator.Apply(permutation, move.Index1, move.Index1, move.Index2);
}
}
public static double EvaluateMove(Permutation permutation, TwoPointFiveMove move, Func <int, int, double> distance, DoubleArray probabilities)
{
if (move.IsInvert)
{
return(PTSPAnalyticalInversionMoveEvaluator.EvaluateMove(permutation,
new InversionMove(move.Index1, move.Index2, move.Permutation), distance, probabilities));
}
else
{
return(PTSPAnalyticalInsertionMoveEvaluator.EvaluateMove(permutation,
new TranslocationMove(move.Index1, move.Index1, move.Index2), distance, probabilities));
}
}
public static double EvaluateMove(Permutation permutation, TwoPointFiveMove move, Func <int, int, double> distance, ItemList <BoolArray> realizations)
{
if (move.IsInvert)
{
return(PTSPEstimatedInversionMoveEvaluator.EvaluateMove(permutation,
new InversionMove(move.Index1, move.Index2, move.Permutation), distance, realizations));
}
else
{
return(PTSPEstimatedInsertionMoveEvaluator.EvaluateMove(permutation,
new TranslocationMove(move.Index1, move.Index1, move.Index2), distance, realizations));
}
}
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++)
{
TwoPointFiveMove bestMove = null;
var bestQuality = 0.0; // we have to make an improvement, so 0 is the baseline
var evaluations = 0.0;
foreach (var move in ExhaustiveTwoPointFiveMoveGenerator.Generate(assignment))
{
var moveQuality = PTSPEstimatedTwoPointFiveMoveEvaluator.EvaluateMove(assignment, move, distance, realizations);
if (move.IsInvert)
{
evaluations += realizations.Count * 4.0 / (assignment.Length * assignment.Length);
}
else
{
evaluations += realizations.Count * 6.0 / (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;
}
TwoPointFiveMoveMaker.Apply(assignment, bestMove);
quality.Value += bestQuality;
localIterations.Value++;
cancellation.ThrowIfCancellationRequested();
}
}