public void SolveTest() {
      double[,] costs = new double[,] {
        {  5,  9,  3,  6 },
        {  8,  7,  8,  2 },
        {  6, 10, 12,  7 },
        {  3, 10,  8,  6 }};
      double quality;
      Permutation p;
      p = new Permutation(PermutationTypes.Absolute, LinearAssignmentProblemSolver.Solve(new DoubleMatrix(costs), out quality));
      Assert.AreEqual(18, quality);
      Assert.IsTrue(p.Validate());

      costs = new double[,] {
        { 11,  7, 10, 17, 10 },
        { 13, 21,  7, 11, 13 },
        { 13, 13, 15, 13, 14 },
        { 18, 10, 13, 16, 14 },
        { 12,  8, 16, 19, 10 }};

      p = new Permutation(PermutationTypes.Absolute, LinearAssignmentProblemSolver.Solve(new DoubleMatrix(costs), out quality));
      Assert.AreEqual(51, quality);
      Assert.IsTrue(p.Validate());

      costs = new double[,] {
        {  3,  1,  1,  4 },
        {  4,  2,  2,  5 },
        {  5,  3,  4,  8 },
        {  4,  2,  5,  9 }};

      p = new Permutation(PermutationTypes.Absolute, LinearAssignmentProblemSolver.Solve(new DoubleMatrix(costs), out quality));
      Assert.AreEqual(13, quality);
      Assert.IsTrue(p.Validate());
    }

    /// <summary>
    /// Performs a slight variation of the order crossover of two permutations.
    /// </summary>
    /// <exception cref="ArgumentException">Thrown when <paramref name="parent1"/> and <paramref name="parent2"/> are not of equal length.</exception>
    /// <remarks>
    /// Crosses two permutations by copying a randomly chosen interval from the first permutation, preserving
    /// the positions. Then, from the beginning of the permutation, copies the missing values from the second permutation
    /// in the order they occur.
    /// </remarks>
    /// <param name="random">A random number generator.</param>
    /// <param name="parent1">The first parent permutation to cross.</param>
    /// <param name="parent2">The second parent permutation to cross.</param>
    /// <returns>The new permutation resulting from the crossover.</returns>
    public static Permutation Apply(IRandom random, Permutation parent1, Permutation parent2) {
      if (parent1.Length != parent2.Length) throw new ArgumentException("OrderCrossover2: The parent permutations are of unequal length.");
      int[] result = new int[parent1.Length];
      bool[] copied = new bool[result.Length];

      int breakPoint1 = random.Next(result.Length - 1);
      int breakPoint2 = random.Next(breakPoint1 + 1, result.Length);

      for (int i = breakPoint1; i <= breakPoint2; i++) {  // copy part of first permutation
        result[i] = parent1[i];
        copied[parent1[i]] = true;
      }

      int index = 0;
      for (int i = 0; i < parent2.Length; i++) {  // copy remaining part of second permutation
        if (index == breakPoint1) {  // skip already copied part
          index = breakPoint2 + 1;
        }
        if (!copied[parent2[i]]) {
          result[index] = parent2[i];
          index++;
        }
      }
      return new Permutation(parent1.PermutationType, result);
    }

    /// <summary>
    /// Performs a cross over permutation of <paramref name="parent1"/> and <paramref name="parent2"/>
    /// based on randomly chosen positions to define which position to take from where.
    /// </summary>
    /// <exception cref="ArgumentException">Thrown when <paramref name="parent1"/> and <paramref name="parent2"/> are not of equal length.</exception>
    /// <param name="random">The random number generator.</param>
    /// <param name="parent1">First parent</param>
    /// <param name="parent2">Second Parent</param>
    /// <returns>Child</returns>
    public static Permutation Apply(IRandom random, Permutation parent1, Permutation parent2) {
      if (parent1.Length != parent2.Length) throw new ArgumentException("PositionBasedCrossover: The parent permutations are of unequal length.");
      int length = parent1.Length;
      int[] result = new int[length];
      bool[] randomPosition = new bool[length];
      bool[] numberCopied = new bool[length];
      int randomPosNumber = random.Next(length);

      for (int i = 0; i < randomPosNumber; i++) {  // generate random bit mask
        randomPosition[random.Next(length)] = true;
      }

      for (int i = 0; i < length; i++) {  // copy numbers masked as true from second permutation
        if (randomPosition[i]) {
          result[i] = parent2[i];
          numberCopied[parent2[i]] = true;
        }
      }

      int index = 0;
      for (int i = 0; i < length; i++) {  // copy numbers masked as false from first permutation
        if (!numberCopied[parent1[i]]) {
          if (randomPosition[index]) {
            while (randomPosition[index]) {
              index++;
            }
          }
          result[index] = parent1[i];
          index++;
        }
      }

      return new Permutation(parent1.PermutationType, result);
    }

 public static void Apply(Permutation permutation, int breakPoint1, int breakPoint2) {
   for (int i = 0; i <= (breakPoint2 - breakPoint1) / 2; i++) {  // invert permutation between breakpoints
     int temp = permutation[breakPoint1 + i];
     permutation[breakPoint1 + i] = permutation[breakPoint2 - i];
     permutation[breakPoint2 - i] = temp;
   }
 }

    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;
    }

    /// <summary>
    /// Performs the order crossover of two permutations.
    /// </summary>
    /// <exception cref="ArgumentException">Thrown when <paramref name="parent1"/> and <paramref name="parent2"/> are not of equal length.</exception>
    /// <exception cref="InvalidOperationException">Thrown if the numbers in the permutation elements are not in the range [0,N) with N = length of the permutation.</exception>
    /// <remarks>
    /// Crosses two permutations by copying a randomly chosen interval from the first permutation, preserving
    /// the positions. Then, starting from the end of the copied interval, copies the missing values from the second permutation
    /// in the order they occur.
    /// </remarks>
    /// <param name="random">A random number generator.</param>
    /// <param name="parent1">The first parent permutation to cross.</param>
    /// <param name="parent2">The second parent permutation to cross.</param>
    /// <returns>The new permutation resulting from the crossover.</returns>
    public static Permutation Apply(IRandom random, Permutation parent1, Permutation parent2) {
      if (parent1.Length != parent2.Length) throw new ArgumentException("OrderCrossover: The parent permutations are of unequal length.");
      int length = parent1.Length;
      int[] result = new int[length];
      bool[] copied = new bool[length];

      int breakPoint1 = random.Next(length - 1);
      int breakPoint2 = random.Next(breakPoint1 + 1, length);

      try {
        for (int j = breakPoint1; j <= breakPoint2; j++) {  // copy part of first permutation
          result[j] = parent1[j];
          copied[parent1[j]] = true;
        }

        int index = ((breakPoint2 + 1 >= length) ? (0) : (breakPoint2 + 1));
        int i = index; // for moving in parent2
        while (index != breakPoint1) {
          if (!copied[parent2[i]]) {
            result[index] = parent2[i];
            index++;
            if (index >= length) index = 0;
          }
          i++;
          if (i >= length) i = 0;
        }
      }
      catch (IndexOutOfRangeException) {
        throw new InvalidOperationException("OrderCrossover: The permutation must consist of numbers in the interval [0;N) with N = length of the permutation.");
      }
      return new Permutation(parent1.PermutationType, result);
    }

 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 IEnumerable<TwoPointFiveMove> Generate(Permutation permutation) {
      int length = permutation.Length;
      if (length == 1) throw new ArgumentException("Exhaustive 2.5-MoveGenerator: There cannot be a 2.5 move given a permutation of length 1.", "permutation");
      int totalMoves = (length) * (length - 1) / 2;

      if (permutation.PermutationType == PermutationTypes.RelativeUndirected) {
        if (totalMoves - 3 > 0) {
          for (int i = 0; i < length - 1; i++) {
            for (int j = i + 1; j < length; j++) {
              // doesn't make sense to inverse the whole permutation or the whole but one in case of relative undirected permutations
              if (j - i >= length - 2) continue;
              yield return new TwoPointFiveMove(i, j, true);
              yield return new TwoPointFiveMove(i, j, false);
            }
          }
        } else { // when length is 3 or less, there's actually no difference, but for the sake of not crashing the algorithm create a dummy move
          yield return new TwoPointFiveMove(0, 1, true);
        }
      } else {
        for (int i = 0; i < length - 1; i++)
          for (int j = i + 1; j < length; j++) {
            yield return new TwoPointFiveMove(i, j, true);
            yield return new TwoPointFiveMove(i, j, false);
          }
      }
    }

    private static int[] GetSubSequenceAtPosition(Permutation p1, int index, int subSequenceLength) {
      var result = new int[subSequenceLength];
      for (int i = 0; i < subSequenceLength; i++)
        result[i] = p1[i + index];

      return result;
    }

 private static void ExchangeSubsequences(Permutation p1, int index1, Permutation p2, int index2, int subSequenceLength) {
   var aux = (Permutation)p1.Clone();
   for (int i = 0; i < subSequenceLength; i++) {
     p1[i + index1] = p2[i + index2];
     p2[i + index2] = aux[i + index1];
   }
 }

 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 void MyClassInitialize(TestContext testContext) {
   random = new MersenneTwister();
   symmetricDistances = new DoubleMatrix(ProblemSize, ProblemSize);
   symmetricWeights = new DoubleMatrix(ProblemSize, ProblemSize);
   asymmetricDistances = new DoubleMatrix(ProblemSize, ProblemSize);
   asymmetricWeights = new DoubleMatrix(ProblemSize, ProblemSize);
   nonZeroDiagonalDistances = new DoubleMatrix(ProblemSize, ProblemSize);
   nonZeroDiagonalWeights = new DoubleMatrix(ProblemSize, ProblemSize);
   for (int i = 0; i < ProblemSize - 1; i++) {
     for (int j = i + 1; j < ProblemSize; j++) {
       symmetricDistances[i, j] = random.Next(ProblemSize * 100);
       symmetricDistances[j, i] = symmetricDistances[i, j];
       symmetricWeights[i, j] = random.Next(ProblemSize * 100);
       symmetricWeights[j, i] = symmetricWeights[i, j];
       asymmetricDistances[i, j] = random.Next(ProblemSize * 100);
       asymmetricDistances[j, i] = random.Next(ProblemSize * 100);
       asymmetricWeights[i, j] = random.Next(ProblemSize * 100);
       asymmetricWeights[j, i] = random.Next(ProblemSize * 100);
       nonZeroDiagonalDistances[i, j] = random.Next(ProblemSize * 100);
       nonZeroDiagonalDistances[j, i] = random.Next(ProblemSize * 100);
       nonZeroDiagonalWeights[i, j] = random.Next(ProblemSize * 100);
       nonZeroDiagonalWeights[j, i] = random.Next(ProblemSize * 100);
     }
     nonZeroDiagonalDistances[i, i] = random.Next(ProblemSize * 100);
     nonZeroDiagonalWeights[i, i] = random.Next(ProblemSize * 100);
   }
   int index = random.Next(ProblemSize);
   if (nonZeroDiagonalDistances[index, index] == 0)
     nonZeroDiagonalDistances[index, index] = random.Next(1, ProblemSize * 100);
   index = random.Next(ProblemSize);
   if (nonZeroDiagonalWeights[index, index] == 0)
     nonZeroDiagonalWeights[index, index] = random.Next(1, ProblemSize * 100);
   assignment = new Permutation(PermutationTypes.Absolute, ProblemSize, random);
 }

    /// <summary>
    /// Moves a randomly chosen interval of elements to another (randomly chosen) position in the given
    /// <paramref name="permutation"/> array and reverses it.
    /// </summary>
    /// <param name="random">The random number generator.</param>
    /// <param name="permutation">The permutation array to manipulate.</param>
    public static void Apply(IRandom random, Permutation permutation) {
      Permutation original = (Permutation)permutation.Clone();
      int breakPoint1, breakPoint2, insertPoint, insertPointLimit;

      breakPoint1 = random.Next(original.Length - 1);
      breakPoint2 = random.Next(breakPoint1 + 1, original.Length);
      insertPointLimit = original.Length - breakPoint2 + breakPoint1 - 1;  // get insertion point in remaining part
      if (insertPointLimit > 0)
        insertPoint = random.Next(insertPointLimit);
      else
        insertPoint = 0;

      int i = 0;  // index in new permutation
      int j = 0;  // index in old permutation
      while (i < original.Length) {
        if (i == insertPoint) {  // copy translocated area
          for (int k = breakPoint2; k >= breakPoint1; k--) {
            permutation[i] = original[k];
            i++;
          }
        }
        if (j == breakPoint1) {  // skip area between breakpoints
          j = breakPoint2 + 1;
        }
        if ((i < original.Length) && (j < original.Length)) {
          permutation[i] = original[j];
          i++;
          j++;
        }
      }
    }

    /// <summary>
    /// Mixes the elements of the given <paramref name="permutation"/> randomly 
    /// in a randomly chosen interval.
    /// </summary>
    /// <param name="random">The random number generator.</param>
    /// <param name="permutation">The permutation to manipulate.</param>
    public static void Apply(IRandom random, Permutation permutation) {
      int breakPoint1, breakPoint2;
      int[] scrambledIndices, remainingIndices, temp;
      int selectedIndex, index;

      breakPoint1 = random.Next(permutation.Length - 1);
      breakPoint2 = random.Next(breakPoint1 + 1, permutation.Length);

      scrambledIndices = new int[breakPoint2 - breakPoint1 + 1];
      remainingIndices = new int[breakPoint2 - breakPoint1 + 1];
      for (int i = 0; i < remainingIndices.Length; i++) {  // initialise indices
        remainingIndices[i] = i;
      }
      for (int i = 0; i < scrambledIndices.Length; i++) {  // generate permutation of indices
        selectedIndex = random.Next(remainingIndices.Length);
        scrambledIndices[i] = remainingIndices[selectedIndex];

        temp = remainingIndices;
        remainingIndices = new int[temp.Length - 1];
        index = 0;
        for (int j = 0; j < remainingIndices.Length; j++) {
          if (index == selectedIndex) {
            index++;
          }
          remainingIndices[j] = temp[index];
          index++;
        }
      }

      Apply(permutation, breakPoint1, scrambledIndices);
    }

    /// <summary>
    /// Performs the partially matched crossover on <paramref name="parent1"/> and <paramref name="parent2"/>.
    /// </summary>
    /// <exception cref="ArgumentException">Thrown when <paramref name="parent1"/> and <paramref name="parent2"/> are not of equal length or when the permutations are shorter than 4 elements.</exception>
    /// <exception cref="InvalidOperationException">Thrown if the numbers in the permutation elements are not in the range [0,N) with N = length of the permutation.</exception>
    /// <remarks>
    /// Initially the new offspring is a clone of <paramref name="parent2"/>.
    /// Then a segment is extracted from <paramref name="parent1"/> and copied to the offspring position by position.
    /// Whenever a position is copied, the number at that position currently in the offspring is transfered to the position where the copied number has been.
    /// E.g.: Position 15 is selected to be copied from <paramref name="parent1"/> to <paramref name="parent2"/>. At position 15 there is a '3' in <paramref name="parent1"/> and a '5' in the new offspring.
    /// The '5' in the offspring is then moved to replace the '3' in the offspring and '3' is written at position 15.
    /// </remarks>
    /// <param name="random">A random number generator.</param>
    /// <param name="parent1">The first parent permutation to cross.</param>
    /// <param name="parent2">The second parent permutation to cross.</param>
    /// <returns>The new permutation resulting from the crossover.</returns>
    public static Permutation Apply(IRandom random, Permutation parent1, Permutation parent2) {
      if (parent1.Length != parent2.Length) throw new ArgumentException("PartiallyMatchedCrossover: The parent permutations are of unequal length.");
      if (parent1.Length < 4) throw new ArgumentException("PartiallyMatchedCrossover: The parent permutation must be at least of size 4.");
      int length = parent1.Length;
      int[] result = new int[length];
      int[] invResult = new int[length];

      int breakPoint1, breakPoint2;
      do {
        breakPoint1 = random.Next(length - 1);
        breakPoint2 = random.Next(breakPoint1 + 1, length);
      } while (breakPoint2 - breakPoint1 >= length - 2); // prevent the case [0,length-1) -> clone of parent1

      // clone parent2 and calculate inverse permutation (number -> index)
      try {
        for (int j = 0; j < length; j++) {
          result[j] = parent2[j];
          invResult[result[j]] = j;
        }
      }
      catch (IndexOutOfRangeException) {
        throw new InvalidOperationException("PartiallyMatchedCrossover: The permutation must consist of consecutive numbers from 0 to N-1 with N = length of the permutation.");
      }

      for (int j = breakPoint1; j <= breakPoint2; j++) {
        int orig = result[j]; // save the former value
        result[j] = parent1[j]; // overwrite the former value with the new value
        int index = invResult[result[j]]; // look where the new value is in the offspring
        result[index] = orig; // write the former value to this position
        invResult[orig] = index; // update the inverse mapping
        // it's not necessary to do 'invResult[result[j]] = j' as this will not be needed again
      }

      return new Permutation(parent1.PermutationType, result);
    }

 public static double Evaluate(Permutation tour, Func<int, int, double> distance, DoubleArray probabilities) {
   // Analytical evaluation
   var firstSum = 0.0;
   for (var i = 0; i < tour.Length - 1; i++) {
     for (var j = i + 1; j < tour.Length; j++) {
       var prod1 = distance(tour[i], tour[j]) * probabilities[tour[i]] * probabilities[tour[j]];
       for (var k = i + 1; k < j; k++) {
         prod1 = prod1 * (1 - probabilities[tour[k]]);
       }
       firstSum += prod1;
     }
   }
   var secondSum = 0.0;
   for (var j = 0; j < tour.Length; j++) {
     for (var i = 0; i < j; i++) {
       var prod2 = distance(tour[j], tour[i]) * probabilities[tour[i]] * probabilities[tour[j]];
       for (var k = j + 1; k < tour.Length; k++) {
         prod2 = prod2 * (1 - probabilities[tour[k]]);
       }
       for (var k = 0; k < i; k++) {
         prod2 = prod2 * (1 - probabilities[tour[k]]);
       }
       secondSum += prod2;
     }
   }
   return firstSum + secondSum;
 }

    /// <summary>
    /// Performs a variant of the cyclic crossover on <paramref name="parent1"/> and <paramref name="parent2"/>.
    /// </summary>
    /// <exception cref="ArgumentException">Thrown when <paramref name="parent1"/> and <paramref name="parent2"/> are not of equal length.</exception>
    /// <exception cref="InvalidOperationException">Thrown if the numbers in the permutation elements are not in the range [0;N) with N = length of the permutation.</exception>
    /// <remarks>
    /// Start at a randomly chosen position x in parent1 and transfer it to the child at the same position.
    /// Now this position x is no longer available for the node on position x in parent2, so
    /// the value of the node at position x in parent2 is searched in parent1 and is then transferred
    /// to the child preserving the position. Now this new position y is no longer available for the node in parent2 and so on.<br/>
    /// This procedure is repeated until it is again at position x, then the cycle is over.<br/>
    /// All further positions are copied from the second permutation.
    /// </remarks>
    /// <exception cref="ArgumentException">Thrown if the two parents are not of equal length.</exception>
    /// <param name="random">The random number generator.</param>
    /// <param name="parent1">The parent scope 1 to cross over.</param>
    /// <param name="parent2">The parent scope 2 to cross over.</param>
    /// <returns>The created cross over permutation as int array.</returns>
    public static Permutation Apply(IRandom random, Permutation parent1, Permutation parent2) {
      if (parent1.Length != parent2.Length) throw new ArgumentException("CyclicCrossover2: The parent permutations are of unequal length.");
      int length = parent1.Length;
      int[] result = new int[length];
      bool[] indexCopied = new bool[length];
      int j, number;

      j = random.Next(length);  // get number to start cycle
      while (!indexCopied[j]) {  // copy whole cycle to new permutation
        result[j] = parent1[j];
        number = parent2[j];
        indexCopied[j] = true;

        j = 0;
        while ((j < length) && (parent1[j] != number)) {  // search copied number in second permutation
          j++;
        }
      }

      for (int i = 0; i < length; i++) {  // copy rest of secound permutation to new permutation
        if (!indexCopied[i]) {
          result[i] = parent2[i];
        }
      }
      return new Permutation(parent1.PermutationType, result);
    }

    /// <summary>
    /// Calculates the quality of the move <paramref name="move"/> by evaluating the changes.
    /// The runtime complexity of this method is O(N) with N being the size of the permutation.
    /// </summary>
    /// <param name="assignment">The current permutation.</param>
    /// <param name="move">The move that is to be evaluated if it was applied to the current permutation.</param>
    /// <param name="weights">The weights matrix.</param>
    /// <param name="distances">The distances matrix.</param>
    /// <returns>The relative change in quality if <paramref name="move"/> was applied to <paramref name="assignment"/>.</returns>
    public static double Apply(Permutation assignment, ScrambleMove move, DoubleMatrix weights, DoubleMatrix distances) {
      double moveQuality = 0;
      int min = move.StartIndex;
      int max = min + move.ScrambledIndices.Length - 1;

      for (int i = min; i <= max; i++) {
        int locI = assignment[i];
        int newlocI = assignment[min + move.ScrambledIndices[i - min]];
        if (locI == newlocI) continue;

        for (int j = 0; j < assignment.Length; j++) {
          int locJ = assignment[j];
          if (j >= min && j <= max) {
            int newlocJ = assignment[min + move.ScrambledIndices[j - min]];
            moveQuality += weights[i, j] * (distances[newlocI, newlocJ] - distances[locI, locJ]);
            if (locJ == newlocJ)
              moveQuality += weights[j, i] * (distances[newlocJ, newlocI] - distances[locJ, locI]);
          } else {
            moveQuality += weights[i, j] * (distances[newlocI, locJ] - distances[locI, locJ]);
            moveQuality += weights[j, i] * (distances[locJ, newlocI] - distances[locJ, locI]);
          }
        }
      }
      return moveQuality;
    }

 public TwoPointFiveMove(int index1, int index2, Permutation permutation, bool isinvert)
   : base() {
   Index1 = index1;
   Index2 = index2;
   IsInvert = isinvert;
   Permutation = permutation;
 }

    public static ScrambleMove GenerateRandomMove(Permutation permutation, IRandom random) {
      int breakPoint1, breakPoint2;
      int[] scrambledIndices;

      breakPoint1 = random.Next(permutation.Length);
      do {
        breakPoint2 = random.Next(permutation.Length);
      } while (Math.Abs(breakPoint2 - breakPoint1) <= 1);
      if (breakPoint2 < breakPoint1) { int h = breakPoint1; breakPoint1 = breakPoint2; breakPoint2 = h; }

      scrambledIndices = new int[breakPoint2 - breakPoint1 + 1];
      for (int i = 0; i < scrambledIndices.Length; i++)
        scrambledIndices[i] = i;
      bool[] moved = new bool[scrambledIndices.Length];
      bool changed = false;
      do {
        for (int i = scrambledIndices.Length - 1; i > 0; i--) {
          int j = random.Next(i + 1);
          int t = scrambledIndices[j];
          scrambledIndices[j] = scrambledIndices[i];
          scrambledIndices[i] = t;
          if (scrambledIndices[j] == j) moved[j] = false;
          else moved[j] = true;
          if (scrambledIndices[i] == i) moved[i] = false;
          else moved[i] = true;
        }
        changed = moved.Any(x => x);
      } while (!changed);

      return new ScrambleMove(breakPoint1, scrambledIndices);
    }