public static double EvaluateByDistanceMatrix(Permutation permutation, TranslocationMove move, DistanceMatrix distanceMatrix) {
if (move.Index1 == move.Index3
|| move.Index2 == permutation.Length - 1 && move.Index3 == 0
|| move.Index1 == 0 && move.Index3 == permutation.Length - 1 - move.Index2) return 0;
int edge1source = permutation.GetCircular(move.Index1 - 1);
int edge1target = permutation[move.Index1];
int edge2source = permutation[move.Index2];
int edge2target = permutation.GetCircular(move.Index2 + 1);
int edge3source, edge3target;
if (move.Index3 > move.Index1) {
edge3source = permutation.GetCircular(move.Index3 + move.Index2 - move.Index1);
edge3target = permutation.GetCircular(move.Index3 + move.Index2 - move.Index1 + 1);
} else {
edge3source = permutation.GetCircular(move.Index3 - 1);
edge3target = permutation[move.Index3];
}
double moveQuality = 0;
// remove three edges
moveQuality -= distanceMatrix[edge1source, edge1target];
moveQuality -= distanceMatrix[edge2source, edge2target];
moveQuality -= distanceMatrix[edge3source, edge3target];
// add three edges
moveQuality += distanceMatrix[edge3source, edge1target];
moveQuality += distanceMatrix[edge2source, edge3target];
moveQuality += distanceMatrix[edge1source, edge2target];
return moveQuality;
}
public static double Apply(Permutation assignment, TranslocationMove move, DoubleMatrix weights, DoubleMatrix distances) {
double moveQuality = 0;
int min = Math.Min(move.Index1, move.Index3);
int max = Math.Max(move.Index2, move.Index3 + (move.Index2 - move.Index1));
int iOffset, changeOffset;
if (move.Index1 < move.Index3) {
iOffset = move.Index2 - move.Index1 + 1;
changeOffset = min + max - move.Index2;
} else {
iOffset = move.Index1 - move.Index3;
changeOffset = min + move.Index2 - move.Index1 + 1;
}
for (int i = min; i <= max; i++) {
if (i == changeOffset) iOffset -= (max - min + 1);
int jOffset = ((move.Index1 < move.Index3) ? (move.Index2 - move.Index1 + 1) : (move.Index1 - move.Index3));
for (int j = 0; j < assignment.Length; j++) {
moveQuality -= weights[i, j] * distances[assignment[i], assignment[j]];
if (j < min || j > max) {
moveQuality -= weights[j, i] * distances[assignment[j], assignment[i]];
moveQuality += weights[i, j] * distances[assignment[i + iOffset], assignment[j]];
moveQuality += weights[j, i] * distances[assignment[j], assignment[i + iOffset]];
} else {
if (j == changeOffset) jOffset -= (max - min + 1);
moveQuality += weights[i, j] * distances[assignment[i + iOffset], assignment[j + jOffset]];
}
}
}
return moveQuality;
}
public static double EvaluateByCoordinates(Permutation permutation, TranslocationMove move, DoubleMatrix coordinates, TSPTranslocationMovePathEvaluator evaluator) {
if (move.Index1 == move.Index3
|| move.Index2 == permutation.Length - 1 && move.Index3 == 0
|| move.Index1 == 0 && move.Index3 == permutation.Length - 1 - move.Index2) return 0;
int edge1source = permutation.GetCircular(move.Index1 - 1);
int edge1target = permutation[move.Index1];
int edge2source = permutation[move.Index2];
int edge2target = permutation.GetCircular(move.Index2 + 1);
int edge3source, edge3target;
if (move.Index3 > move.Index1) {
edge3source = permutation.GetCircular(move.Index3 + move.Index2 - move.Index1);
edge3target = permutation.GetCircular(move.Index3 + move.Index2 - move.Index1 + 1);
} else {
edge3source = permutation.GetCircular(move.Index3 - 1);
edge3target = permutation[move.Index3];
}
double moveQuality = 0;
// remove three edges
moveQuality -= evaluator.CalculateDistance(coordinates[edge1source, 0], coordinates[edge1source, 1],
coordinates[edge1target, 0], coordinates[edge1target, 1]);
moveQuality -= evaluator.CalculateDistance(coordinates[edge2source, 0], coordinates[edge2source, 1],
coordinates[edge2target, 0], coordinates[edge2target, 1]);
moveQuality -= evaluator.CalculateDistance(coordinates[edge3source, 0], coordinates[edge3source, 1],
coordinates[edge3target, 0], coordinates[edge3target, 1]);
// add three edges
moveQuality += evaluator.CalculateDistance(coordinates[edge3source, 0], coordinates[edge3source, 1],
coordinates[edge1target, 0], coordinates[edge1target, 1]);
moveQuality += evaluator.CalculateDistance(coordinates[edge2source, 0], coordinates[edge2source, 1],
coordinates[edge3target, 0], coordinates[edge3target, 1]);
moveQuality += evaluator.CalculateDistance(coordinates[edge1source, 0], coordinates[edge1source, 1],
coordinates[edge2target, 0], coordinates[edge2target, 1]);
return moveQuality;
}
public static TranslocationMove[] Apply(Permutation permutation, IRandom random, int sampleSize) {
int length = permutation.Length;
TranslocationMove[] moves = new TranslocationMove[sampleSize];
for (int i = 0; i < sampleSize; i++) {
moves[i] = StochasticTranslocationSingleMoveGenerator.Apply(permutation, random);
}
return moves;
}
public static TranslocationMove[] Apply(Permutation permutation, IRandom random, int sampleSize)
{
int length = permutation.Length;
TranslocationMove[] moves = new TranslocationMove[sampleSize];
for (int i = 0; i < sampleSize; i++)
{
moves[i] = StochasticTranslocationSingleMoveGenerator.Apply(permutation, random);
}
return(moves);
}
public override IOperation Apply()
{
TranslocationMove move = TranslocationMoveParameter.ActualValue;
Permutation permutation = PermutationParameter.ActualValue;
DoubleValue moveQuality = MoveQualityParameter.ActualValue;
DoubleValue quality = QualityParameter.ActualValue;
TranslocationManipulator.Apply(permutation, move.Index1, move.Index2, move.Index3);
quality.Value = moveQuality.Value;
return(base.Apply());
}
protected override IItem GetTabuAttribute(bool maximization, double quality, double moveQuality)
{
TranslocationMove move = TranslocationMoveParameter.ActualValue;
Permutation permutation = PermutationParameter.ActualValue;
double baseQuality = moveQuality;
if (maximization && quality > moveQuality || !maximization && quality < moveQuality)
{
baseQuality = quality; // we make an uphill move, the lower bound is the solution quality
}
if (permutation.PermutationType == PermutationTypes.Absolute)
{
int[] numbers = new int[move.Index2 - move.Index1 + 1];
for (int i = 0; i < numbers.Length; i++)
{
numbers[i] = permutation[i + move.Index1];
}
return(new TranslocationMoveAbsoluteAttribute(numbers, move.Index1, move.Index3, baseQuality));;
}
else
{
if (move.Index3 > move.Index1)
{
return(new TranslocationMoveRelativeAttribute(permutation.GetCircular(move.Index1 - 1),
permutation[move.Index1],
permutation[move.Index2],
permutation.GetCircular(move.Index2 + 1),
permutation.GetCircular(move.Index3 + move.Index2 - move.Index1),
permutation.GetCircular(move.Index3 + move.Index2 - move.Index1 + 1),
baseQuality));
}
else
{
return(new TranslocationMoveRelativeAttribute(permutation.GetCircular(move.Index1 - 1),
permutation[move.Index1],
permutation[move.Index2],
permutation.GetCircular(move.Index2 + 1),
permutation.GetCircular(move.Index3 - 1),
permutation.GetCircular(move.Index3),
baseQuality));
}
}
}
public static TranslocationMove[] Apply(Permutation permutation, IRandom random, int sampleSize) {
int length = permutation.Length;
if (length == 1) throw new ArgumentException("ExhaustiveSingleInsertionMoveGenerator: There cannot be an insertion move given a permutation of length 1.", "permutation");
TranslocationMove[] moves = new TranslocationMove[sampleSize];
int count = 0;
HashSet<int> usedIndices = new HashSet<int>();
while (count < sampleSize) {
int index = random.Next(length);
if (usedIndices.Count != length)
while (usedIndices.Contains(index))
index = random.Next(length);
usedIndices.Add(index);
if (permutation.PermutationType == PermutationTypes.Absolute) {
for (int j = 1; j <= length - 1; j++) {
moves[count++] = new TranslocationMove(index, index, (index + j) % length);
if (count == sampleSize) break;
}
} else {
if (length > 2) {
for (int j = 1; j < length - 1; j++) {
int insertPoint = (index + j) % length;
if (index + j >= length) insertPoint++;
moves[count++] = new TranslocationMove(index, index, insertPoint);
if (count == sampleSize) break;
}
} else { // doesn't make sense, but just create a dummy move to not crash the algorithms
moves = new TranslocationMove[1];
moves[0] = new TranslocationMove(0, 0, 1);
count = sampleSize;
}
}
}
return moves;
}
public static TranslocationMove[] Apply(Permutation permutation, IRandom random, int sampleSize)
{
int length = permutation.Length;
if (length == 1)
{
throw new ArgumentException("ExhaustiveSingleInsertionMoveGenerator: There cannot be an insertion move given a permutation of length 1.", "permutation");
}
TranslocationMove[] moves = new TranslocationMove[sampleSize];
int count = 0;
HashSet <int> usedIndices = new HashSet <int>();
while (count < sampleSize)
{
int index = random.Next(length);
if (usedIndices.Count != length)
{
while (usedIndices.Contains(index))
{
index = random.Next(length);
}
}
usedIndices.Add(index);
if (permutation.PermutationType == PermutationTypes.Absolute)
{
for (int j = 1; j <= length - 1; j++)
{
moves[count++] = new TranslocationMove(index, index, (index + j) % length);
if (count == sampleSize)
{
break;
}
}
}
else
{
if (length > 2)
{
for (int j = 1; j < length - 1; j++)
{
int insertPoint = (index + j) % length;
if (index + j >= length)
{
insertPoint++;
}
moves[count++] = new TranslocationMove(index, index, insertPoint);
if (count == sampleSize)
{
break;
}
}
}
else // doesn't make sense, but just create a dummy move to not crash the algorithms
{
moves = new TranslocationMove[1];
moves[0] = new TranslocationMove(0, 0, 1);
count = sampleSize;
}
}
}
return(moves);
}
public override IOperation Apply()
{
ItemList <IItem> tabuList = TabuListParameter.ActualValue;
TranslocationMove move = TranslocationMoveParameter.ActualValue;
Permutation permutation = PermutationParameter.ActualValue;
int length = permutation.Length;
double moveQuality = MoveQualityParameter.ActualValue.Value;
bool maximization = MaximizationParameter.ActualValue.Value;
bool useAspiration = UseAspirationCriterion.Value;
bool isTabu = false;
if (permutation.PermutationType == PermutationTypes.Absolute)
{
int count = move.Index2 - move.Index1 + 1;
int[] numbers = new int[count];
for (int i = move.Index1; i <= move.Index2; i++)
{
numbers[i - move.Index1] = permutation[i];
}
foreach (IItem tabuMove in tabuList)
{
TranslocationMoveAbsoluteAttribute attribute = (tabuMove as TranslocationMoveAbsoluteAttribute);
if (attribute != null)
{
if (!useAspiration ||
maximization && moveQuality <= attribute.MoveQuality ||
!maximization && moveQuality >= attribute.MoveQuality) // if the move quality is improving beyond what was recorded when the move in the tabu list was recorded the move is regarded as okay
{
for (int i = 0; i < count; i++)
{
for (int j = 0; j < attribute.Number.Length; j++)
{
if (attribute.Number[j] == numbers[i])
{
isTabu = true;
break;
}
}
if (isTabu)
{
break;
}
}
}
}
if (isTabu)
{
break;
}
}
}
else
{
int E1S = permutation.GetCircular(move.Index1 - 1);
int E1T = permutation[move.Index1];
int E2S = permutation[move.Index2];
int E2T = permutation.GetCircular(move.Index2 + 1);
int E3S, E3T;
if (move.Index3 > move.Index1)
{
E3S = permutation.GetCircular(move.Index3 + move.Index2 - move.Index1);
E3T = permutation.GetCircular(move.Index3 + move.Index2 - move.Index1 + 1);
}
else
{
E3S = permutation.GetCircular(move.Index3 - 1);
E3T = permutation[move.Index3];
}
foreach (IItem tabuMove in tabuList)
{
TranslocationMoveRelativeAttribute attribute = (tabuMove as TranslocationMoveRelativeAttribute);
if (attribute != null)
{
if (!useAspiration ||
maximization && moveQuality <= attribute.MoveQuality ||
!maximization && moveQuality >= attribute.MoveQuality)
{
if (permutation.PermutationType == PermutationTypes.RelativeUndirected)
{
if (// if previously added Edge3Source-Edge1Target is deleted
attribute.Edge3Source == E1S && attribute.Edge1Target == E1T || attribute.Edge3Source == E1T && attribute.Edge1Target == E1S ||
attribute.Edge3Source == E2S && attribute.Edge1Target == E2T || attribute.Edge3Source == E2T && attribute.Edge1Target == E2S ||
attribute.Edge3Source == E3S && attribute.Edge1Target == E3T || attribute.Edge3Source == E3T && attribute.Edge1Target == E3S
// if previously added Edge2Source-Edge3Target is deleted
|| attribute.Edge2Source == E1S && attribute.Edge3Target == E1T || attribute.Edge2Source == E1T && attribute.Edge3Target == E1S ||
attribute.Edge2Source == E2S && attribute.Edge3Target == E2T || attribute.Edge2Source == E2T && attribute.Edge3Target == E2S ||
attribute.Edge2Source == E3S && attribute.Edge3Target == E3T || attribute.Edge2Source == E3T && attribute.Edge3Target == E3S
// if previously added Edge1Source-Edge2Target is deleted
|| attribute.Edge1Source == E1S && attribute.Edge2Target == E1T || attribute.Edge1Source == E1T && attribute.Edge2Target == E1S ||
attribute.Edge1Source == E2S && attribute.Edge2Target == E2T || attribute.Edge1Source == E2T && attribute.Edge2Target == E2S ||
attribute.Edge1Source == E3S && attribute.Edge2Target == E3T || attribute.Edge1Source == E3T && attribute.Edge2Target == E3S)
{
isTabu = true;
break;
}
}
else
{
if (// if previously added Edge3Source-Edge1Target is deleted
attribute.Edge3Source == E1S && attribute.Edge1Target == E1T ||
attribute.Edge3Source == E2S && attribute.Edge1Target == E2T ||
attribute.Edge3Source == E3S && attribute.Edge1Target == E3T
// if previously added Edge2Source-Edge3Target is deleted
|| attribute.Edge2Source == E1S && attribute.Edge3Target == E1T ||
attribute.Edge2Source == E2S && attribute.Edge3Target == E2T ||
attribute.Edge2Source == E3S && attribute.Edge3Target == E3T
// if previously added Edge1Source-Edge2Target is deleted
|| attribute.Edge1Source == E1S && attribute.Edge2Target == E1T ||
attribute.Edge1Source == E2S && attribute.Edge2Target == E2T ||
attribute.Edge1Source == E3S && attribute.Edge2Target == E3T)
{
isTabu = true;
break;
}
}
}
}
}
}
MoveTabuParameter.ActualValue = new BoolValue(isTabu);
return(base.Apply());
}
protected TranslocationMove(TranslocationMove original, Cloner cloner) : base(original, cloner)
{
}
protected TranslocationMove(TranslocationMove original, Cloner cloner) : base(original, cloner) { }
public static double EvaluateMove(Permutation tour, TranslocationMove move, Func<int, int, double> distance, ItemList<BoolArray> realizations) {
var afterMove = (Permutation)tour.Clone();
TranslocationManipulator.Apply(afterMove, move.Index1, move.Index1, move.Index3);
double moveQuality = 0;
var edges = new int[12];
var indices = new int[12];
edges[0] = tour.GetCircular(move.Index1 - 1);
indices[0] = DecreaseCircularIndex(tour.Length, move.Index1);
edges[1] = tour[move.Index1];
indices[1] = move.Index1;
edges[2] = tour[move.Index1];
indices[2] = move.Index1;
edges[3] = tour.GetCircular(move.Index1 + 1);
indices[3] = IncreaseCircularIndex(tour.Length, move.Index1);
edges[6] = afterMove.GetCircular(move.Index3 - 1);
indices[6] = DecreaseCircularIndex(afterMove.Length, move.Index3);
edges[7] = afterMove[move.Index3];
indices[7] = move.Index3;
edges[8] = afterMove[move.Index3];
indices[8] = move.Index3;
edges[9] = afterMove.GetCircular(move.Index3 + 1);
indices[9] = IncreaseCircularIndex(afterMove.Length, move.Index3);
if (move.Index3 > move.Index1) {
edges[4] = tour[move.Index3];
indices[4] = move.Index3;
edges[5] = tour.GetCircular(move.Index3 + 1);
indices[5] = indices[9];
edges[10] = afterMove.GetCircular(move.Index1 - 1);
indices[10] = indices[0];
edges[11] = afterMove[move.Index1];
indices[11] = move.Index1;
} else {
edges[4] = tour.GetCircular(move.Index3 - 1);
indices[4] = indices[6];
edges[5] = tour[move.Index3];
indices[5] = move.Index3;
edges[10] = afterMove[move.Index1];
indices[10] = move.Index1;
edges[11] = afterMove.GetCircular(move.Index1 + 1);
indices[11] = indices[3];
}
int[] aPosteriori = new int[12];
foreach (var realization in realizations) {
for (int i = 0; i < edges.Length; i++) {
Permutation tempPermutation;
if (i < 6) {
tempPermutation = tour;
} else {
tempPermutation = afterMove;
}
if (realization[edges[i]]) {
aPosteriori[i] = edges[i];
} else {
int j = 1;
if (i % 2 == 0) {
// find nearest predecessor in realization if source edge
while (!realization[tempPermutation.GetCircular(indices[i] - j)]) {
j++;
}
aPosteriori[i] = tempPermutation.GetCircular(indices[i] - j);
} else {
// find nearest successor in realization if target edge
while (!realization[tempPermutation.GetCircular(indices[i] + j)]) {
j++;
}
aPosteriori[i] = tempPermutation.GetCircular(indices[i] + j);
}
}
}
if (!(aPosteriori[0] == aPosteriori[2] && aPosteriori[1] == aPosteriori[3]) &&
!(aPosteriori[0] == aPosteriori[4] && aPosteriori[1] == aPosteriori[5]) &&
!(aPosteriori[2] == aPosteriori[4] && aPosteriori[3] == aPosteriori[5])) {
// compute cost difference between the two a posteriori solutions
moveQuality = moveQuality + distance(aPosteriori[6], aPosteriori[7]) + distance(aPosteriori[8], aPosteriori[9]) + distance(aPosteriori[10], aPosteriori[11]);
moveQuality = moveQuality - distance(aPosteriori[0], aPosteriori[1]) - distance(aPosteriori[2], aPosteriori[3]) - distance(aPosteriori[4], aPosteriori[5]);
}
Array.Clear(aPosteriori, 0, aPosteriori.Length);
}
// return average of cost differences
return moveQuality / realizations.Count;
}
public static double EvaluateMove(Permutation tour, TranslocationMove move, Func<int, int, double> distance, DoubleArray probabilities) {
var afterMove = (Permutation)tour.Clone();
TranslocationManipulator.Apply(afterMove, move.Index1, move.Index1, move.Index3);
return AnalyticalProbabilisticTravelingSalesmanProblem.Evaluate(afterMove, distance, probabilities);
}
