- Timestamp:
- 04/02/11 16:34:32 (14 years ago)
- Location:
- branches/QAP/HeuristicLab.Problems.QuadraticAssignment/3.3
- Files:
-
- 1 added
- 1 deleted
- 3 edited
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branches/QAP/HeuristicLab.Problems.QuadraticAssignment/3.3/Evaluators/QAPInversionMoveEvaluator.cs
r5838 r5930 54 54 int min = Math.Min(move.Index1, move.Index2); 55 55 int max = Math.Max(move.Index1, move.Index2); 56 56 57 for (int i = min; i <= max; i++) { 58 int locI = assignment[i]; 59 int newlocI = assignment[max - i + min]; 60 57 61 for (int j = 0; j < assignment.Length; j++) { 58 moveQuality -= weights[i, j] * distances[assignment[i], assignment[j]]; 59 if (j < min || j > max) { 60 moveQuality -= weights[j, i] * distances[assignment[j], assignment[i]]; 61 moveQuality += weights[i, j] * distances[assignment[max - i + min], assignment[j]]; 62 moveQuality += weights[j, i] * distances[assignment[j], assignment[max - i + min]]; 62 int locJ = assignment[j]; 63 if (j >= min && j <= max) { 64 int newlocJ = assignment[max - j + min]; 65 moveQuality += weights[i, j] * (distances[newlocI, newlocJ] - distances[locI, locJ]); 63 66 } else { 64 moveQuality += weights[i, j] * distances[assignment[max - i + min], assignment[max - j + min]]; 67 moveQuality += weights[i, j] * (distances[newlocI, locJ] - distances[locI, locJ]); 68 moveQuality += weights[j, i] * (distances[locJ, newlocI] - distances[locJ, locI]); 65 69 } 66 70 } -
branches/QAP/HeuristicLab.Problems.QuadraticAssignment/3.3/HeuristicLab.Problems.QuadraticAssignment-3.3.csproj
r5873 r5930 139 139 <ItemGroup> 140 140 <Compile Include="Analyzers\BestQAPSolutionAnalyzer.cs" /> 141 <Compile Include="Evaluators\QAPSwap MoveEvaluator.cs" />141 <Compile Include="Evaluators\QAPSwap2MoveEvaluator.cs" /> 142 142 <Compile Include="Evaluators\QAPEvaluator.cs" /> 143 143 <Compile Include="Evaluators\QAPInversionMoveEvaluator.cs" /> -
branches/QAP/HeuristicLab.Problems.QuadraticAssignment/3.3/Tests/QAPMoveEvaluatorTest.cs
r5838 r5930 34 34 [TestClass()] 35 35 public class QAPSwapMoveEvaluatorTest { 36 private const int ProblemSize = 10; 37 private static DoubleMatrix symmetricDistances, symmetricWeights, asymmetricDistances, asymmetricWeights, nonZeroDiagonalWeights, nonZeroDiagonalDistances; 38 private static Permutation assignment; 39 private static MersenneTwister random; 36 40 37 41 private TestContext testContextInstance; … … 45 49 } 46 50 47 #region Additional test attributes 48 // 49 //You can use the following additional attributes as you write your tests: 50 // 51 //Use ClassInitialize to run code before running the first test in the class 52 //[ClassInitialize()] 53 //public static void MyClassInitialize(TestContext testContext) 54 //{ 55 //} 56 // 57 //Use ClassCleanup to run code after all tests in a class have run 58 //[ClassCleanup()] 59 //public static void MyClassCleanup() 60 //{ 61 //} 62 // 63 //Use TestInitialize to run code before running each test 64 //[TestInitialize()] 65 //public void MyTestInitialize() 66 //{ 67 //} 68 // 69 //Use TestCleanup to run code after each test has run 70 //[TestCleanup()] 71 //public void MyTestCleanup() 72 //{ 73 //} 74 // 75 #endregion 51 [ClassInitialize] 52 public static void MyClassInitialize(TestContext testContext) { 53 random = new MersenneTwister(); 54 symmetricDistances = new DoubleMatrix(ProblemSize, ProblemSize); 55 symmetricWeights = new DoubleMatrix(ProblemSize, ProblemSize); 56 asymmetricDistances = new DoubleMatrix(ProblemSize, ProblemSize); 57 asymmetricWeights = new DoubleMatrix(ProblemSize, ProblemSize); 58 nonZeroDiagonalDistances = new DoubleMatrix(ProblemSize, ProblemSize); 59 nonZeroDiagonalWeights = new DoubleMatrix(ProblemSize, ProblemSize); 60 for (int i = 0; i < ProblemSize - 1; i++) { 61 for (int j = i + 1; j < ProblemSize; j++) { 62 symmetricDistances[i, j] = random.Next(ProblemSize); 63 symmetricDistances[j, i] = symmetricDistances[i, j]; 64 symmetricWeights[i, j] = random.Next(ProblemSize); 65 symmetricWeights[j, i] = symmetricWeights[i, j]; 66 asymmetricDistances[i, j] = random.Next(ProblemSize); 67 asymmetricDistances[j, i] = random.Next(ProblemSize); 68 asymmetricWeights[i, j] = random.Next(ProblemSize); 69 asymmetricWeights[j, i] = random.Next(ProblemSize); 70 nonZeroDiagonalDistances[i, j] = random.Next(ProblemSize); 71 nonZeroDiagonalDistances[j, i] = random.Next(ProblemSize); 72 nonZeroDiagonalWeights[i, j] = random.Next(ProblemSize); 73 nonZeroDiagonalWeights[j, i] = random.Next(ProblemSize); 74 } 75 nonZeroDiagonalDistances[i, i] = random.Next(ProblemSize); 76 nonZeroDiagonalWeights[i, i] = random.Next(ProblemSize); 77 } 78 int index = random.Next(ProblemSize); 79 if (nonZeroDiagonalDistances[index, index] == 0) 80 nonZeroDiagonalDistances[index, index] = random.Next(1, ProblemSize); 81 index = random.Next(ProblemSize); 82 if (nonZeroDiagonalWeights[index, index] == 0) 83 nonZeroDiagonalWeights[index, index] = random.Next(1, ProblemSize); 84 assignment = new Permutation(PermutationTypes.Absolute, ProblemSize, random); 85 } 76 86 77 87 [TestMethod] 78 public void SwapMoveEvaluatorTest() { 79 DoubleMatrix distances = new DoubleMatrix( 80 new double[,] { { 0, 1, 2, 3 }, 81 { 1, 0, 3, 4 }, 82 { 2, 3, 0, 5 }, 83 { 3, 4, 5, 0 } }); 84 DoubleMatrix weights = new DoubleMatrix( 85 new double[,] { { 0, 1, 0, 0 }, 86 { 1, 0, 2, 0 }, 87 { 0, 2, 0, 1 }, 88 { 0, 0, 1, 0 } }); 89 Permutation assignment = new Permutation(PermutationTypes.Absolute, 90 new int[] { 0, 1, 2, 3 }); 91 MersenneTwister random = new MersenneTwister(); 88 public void Swap2MoveEvaluatorTest() { 92 89 for (int i = 0; i < 500; i++) { 93 int index1 = random.Next(4); 94 int index2 = random.Next(4); 95 double before = QAPEvaluator.Apply(assignment, weights, distances); 90 int index1 = random.Next(ProblemSize); 91 int index2 = random.Next(ProblemSize); 92 93 // SYMMETRIC MATRICES 94 double before = QAPEvaluator.Apply(assignment, symmetricWeights, symmetricDistances); 96 95 Swap2Manipulator.Apply(assignment, index1, index2); 97 double after = QAPEvaluator.Apply(assignment, weights, distances); 98 // evaluate swap back 99 double move = QAPSwap2MoveEvaluator.Apply(assignment, new Swap2Move(index1, index2, assignment), weights, distances); 100 Assert.IsTrue(move.IsAlmost(before - after)); 96 double after = QAPEvaluator.Apply(assignment, symmetricWeights, symmetricDistances); 97 double move = QAPSwap2MoveEvaluator.Apply(assignment, new Swap2Move(index1, index2, assignment), symmetricWeights, symmetricDistances); 98 Assert.IsTrue(move.IsAlmost(before - after), "Failed on symmetric matrices"); 99 100 // ASYMMETRIC MATRICES 101 before = QAPEvaluator.Apply(assignment, asymmetricWeights, asymmetricDistances); 102 Permutation clone = (Permutation)assignment.Clone(); 103 Swap2Manipulator.Apply(assignment, index1, index2); 104 after = QAPEvaluator.Apply(assignment, asymmetricWeights, asymmetricDistances); 105 move = QAPSwap2MoveEvaluator.Apply(clone, new Swap2Move(index1, index2), asymmetricWeights, asymmetricDistances); 106 Assert.IsTrue(move.IsAlmost(after - before), "Failed on asymmetric matrices"); 107 108 // NON-ZERO DIAGONAL ASSYMETRIC MATRICES 109 before = QAPEvaluator.Apply(assignment, nonZeroDiagonalWeights, nonZeroDiagonalDistances); 110 clone = (Permutation)assignment.Clone(); 111 Swap2Manipulator.Apply(assignment, index1, index2); 112 after = QAPEvaluator.Apply(assignment, nonZeroDiagonalWeights, nonZeroDiagonalDistances); 113 move = QAPSwap2MoveEvaluator.Apply(clone, new Swap2Move(index1, index2), nonZeroDiagonalWeights, nonZeroDiagonalDistances); 114 Assert.IsTrue(move.IsAlmost(after - before), "Failed on non-zero diagonal matrices"); 101 115 } 102 116 } … … 104 118 [TestMethod] 105 119 public void InversionMoveEvaluatorTest() { 106 DoubleMatrix distances = new DoubleMatrix(107 new double[,] { { 0, 1, 2, 3 },108 { 1, 0, 3, 4 },109 { 2, 3, 0, 5 },110 { 3, 4, 5, 0 } });111 DoubleMatrix weights = new DoubleMatrix(112 new double[,] { { 0, 1, 0, 0 },113 { 1, 0, 2, 0 },114 { 0, 2, 0, 1 },115 { 0, 0, 1, 0 } });116 Permutation assignment = new Permutation(PermutationTypes.Absolute,117 new int[] { 0, 1, 2, 3 });118 MersenneTwister random = new MersenneTwister();119 120 for (int i = 0; i < 500; i++) { 120 int index1 = random.Next(4); 121 int index2 = random.Next(4); 122 double before = QAPEvaluator.Apply(assignment, weights, distances); 123 // invert 121 int index1 = random.Next(ProblemSize); 122 int index2 = random.Next(ProblemSize); 123 if (index1 > index2) { int h = index1; index1 = index2; index2 = h; } 124 125 // SYMMETRIC MATRICES 126 double before = QAPEvaluator.Apply(assignment, symmetricWeights, symmetricDistances); 124 127 InversionManipulator.Apply(assignment, Math.Min(index1, index2), Math.Max(index1, index2)); 125 double after = QAPEvaluator.Apply(assignment, weights, distances); 126 // evaluate invert back 127 double move = QAPInversionMoveEvaluator.Apply(assignment, new InversionMove(index1, index2, assignment), weights, distances); 128 Assert.IsTrue(move.IsAlmost(before - after)); 128 double after = QAPEvaluator.Apply(assignment, symmetricWeights, symmetricDistances); 129 double move = QAPInversionMoveEvaluator.Apply(assignment, new InversionMove(index1, index2, assignment), symmetricWeights, symmetricDistances); 130 Assert.IsTrue(move.IsAlmost(before - after), "Failed on symmetric matrices"); 131 132 // ASYMMETRIC MATRICES 133 before = QAPEvaluator.Apply(assignment, asymmetricWeights, asymmetricDistances); 134 Permutation clone = (Permutation)assignment.Clone(); 135 InversionManipulator.Apply(assignment, index1, index2); 136 after = QAPEvaluator.Apply(assignment, asymmetricWeights, asymmetricDistances); 137 move = QAPInversionMoveEvaluator.Apply(clone, new InversionMove(index1, index2), asymmetricWeights, asymmetricDistances); 138 Assert.IsTrue(move.IsAlmost(after - before), "Failed on asymmetric matrices"); 139 140 // NON-ZERO DIAGONAL ASYMMETRIC MATRICES 141 before = QAPEvaluator.Apply(assignment, nonZeroDiagonalWeights, nonZeroDiagonalDistances); 142 clone = (Permutation)assignment.Clone(); 143 InversionManipulator.Apply(assignment, index1, index2); 144 after = QAPEvaluator.Apply(assignment, nonZeroDiagonalWeights, nonZeroDiagonalDistances); 145 move = QAPInversionMoveEvaluator.Apply(clone, new InversionMove(index1, index2), nonZeroDiagonalWeights, nonZeroDiagonalDistances); 146 Assert.IsTrue(move.IsAlmost(after - before), "Failed on non-zero diagonal matrices"); 129 147 } 130 148 } … … 132 150 [TestMethod] 133 151 public void TranslocationMoveEvaluatorTest() { 134 DoubleMatrix distances = new DoubleMatrix(135 new double[,] { { 0, 1, 2, 3 },136 { 1, 0, 3, 4 },137 { 2, 3, 0, 5 },138 { 3, 4, 5, 0 } });139 DoubleMatrix weights = new DoubleMatrix(140 new double[,] { { 0, 1, 0, 0 },141 { 1, 0, 2, 0 },142 { 0, 2, 0, 1 },143 { 0, 0, 1, 0 } });144 Permutation assignment = new Permutation(PermutationTypes.Absolute,145 new int[] { 0, 1, 2, 3 });146 MersenneTwister random = new MersenneTwister();147 152 for (int i = 0; i < 500; i++) { 148 153 int index1 = random.Next(assignment.Length - 1); … … 154 159 else 155 160 insertPoint = 0; 156 double before = QAPEvaluator.Apply(assignment, weights, distances); 157 // translocate 161 162 // SYMMETRIC MATRICES 163 double before = QAPEvaluator.Apply(assignment, symmetricWeights, symmetricDistances); 158 164 Permutation clone = new Cloner().Clone(assignment); 159 165 TranslocationManipulator.Apply(assignment, index1, index2, insertPoint); 160 double after = QAPEvaluator.Apply(assignment, weights, distances); 161 // evaluate translocate move 162 double move = QAPTranslocationMoveEvaluator.Apply(clone, new TranslocationMove(index1, index2, insertPoint, assignment), weights, distances); 163 Assert.IsTrue(move.IsAlmost(after - before)); 166 double after = QAPEvaluator.Apply(assignment, symmetricWeights, symmetricDistances); 167 double move = QAPTranslocationMoveEvaluator.Apply(clone, new TranslocationMove(index1, index2, insertPoint, assignment), symmetricWeights, symmetricDistances); 168 Assert.IsTrue(move.IsAlmost(after - before), "Failed on symmetric matrices"); 169 170 // ASYMMETRIC MATRICES 171 before = QAPEvaluator.Apply(assignment, asymmetricWeights, asymmetricDistances); 172 clone = new Cloner().Clone(assignment); 173 TranslocationManipulator.Apply(assignment, index1, index2, insertPoint); 174 after = QAPEvaluator.Apply(assignment, asymmetricWeights, asymmetricDistances); 175 move = QAPTranslocationMoveEvaluator.Apply(clone, new TranslocationMove(index1, index2, insertPoint, assignment), asymmetricWeights, asymmetricDistances); 176 Assert.IsTrue(move.IsAlmost(after - before), "Failed on asymmetric matrices"); 177 178 // NON-ZERO DIAGONAL ASYMMETRIC MATRICES 179 before = QAPEvaluator.Apply(assignment, nonZeroDiagonalWeights, nonZeroDiagonalDistances); 180 clone = new Cloner().Clone(assignment); 181 TranslocationManipulator.Apply(assignment, index1, index2, insertPoint); 182 after = QAPEvaluator.Apply(assignment, nonZeroDiagonalWeights, nonZeroDiagonalDistances); 183 move = QAPTranslocationMoveEvaluator.Apply(clone, new TranslocationMove(index1, index2, insertPoint, assignment), nonZeroDiagonalWeights, nonZeroDiagonalDistances); 184 Assert.IsTrue(move.IsAlmost(after - before), "Failed on non-zero diagonal matrices"); 164 185 } 165 186 }
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