- Timestamp:
- 12/12/16 13:53:16 (8 years ago)
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trunk/sources/HeuristicLab.Tests/HeuristicLab-3.3/Samples/GAGroupingProblemSampleTest.cs
r14185 r14475 49 49 public bool Maximization { get { return false; } } 50 50 51 private bool[,] a llowedTogether;51 private bool[,] adjacencyMatrix; 52 52 53 53 public override void Initialize() { 54 54 var encoding = new LinearLinkageEncoding(""lle"", length: ProblemSize); 55 a llowedTogether= new bool[encoding.Length, encoding.Length];55 adjacencyMatrix = new bool[encoding.Length, encoding.Length]; 56 56 var random = new System.Random(13); 57 57 for (var i = 0; i < encoding.Length - 1; i++) 58 58 for (var j = i + 1; j < encoding.Length; j++) 59 a llowedTogether[i, j] = allowedTogether[j, i] = random.Next(2) == 0;59 adjacencyMatrix[i, j] = adjacencyMatrix[j, i] = random.Next(2) == 0; 60 60 61 61 Encoding = encoding; … … 68 68 for (var j = 0; j < groups[i].Count; j++) 69 69 for (var k = j + 1; k < groups[i].Count; k++) 70 if (!a llowedTogether[groups[i][j], groups[i][k]]) penalty++;70 if (!adjacencyMatrix[groups[i][j], groups[i][k]]) penalty++; 71 71 } 72 if (penalty > 0) return penalty + ProblemSize; 73 else return groups.Count; 72 var result = groups.Count; 73 if (penalty > 0) result += penalty + ProblemSize; 74 return result; 74 75 } 75 76 … … 105 106 ga.SetSeedRandomly.Value = false; 106 107 SamplesUtils.RunAlgorithm(ga); 107 Assert.AreEqual( 26, SamplesUtils.GetDoubleResult(ga, "BestQuality"));108 Assert.AreEqual( 27.58, SamplesUtils.GetDoubleResult(ga, "CurrentAverageQuality"));109 Assert.AreEqual(1 05, SamplesUtils.GetDoubleResult(ga, "CurrentWorstQuality"));108 Assert.AreEqual(127, SamplesUtils.GetDoubleResult(ga, "BestQuality")); 109 Assert.AreEqual(129,38, SamplesUtils.GetDoubleResult(ga, "CurrentAverageQuality")); 110 Assert.AreEqual(132, SamplesUtils.GetDoubleResult(ga, "CurrentWorstQuality")); 110 111 Assert.AreEqual(99100, SamplesUtils.GetIntResult(ga, "EvaluatedSolutions")); 111 112 } … … 121 122 #endregion 122 123 #region Algorithm Configuration 123 ga.Name = "Genetic Algorithm - Gr ouping Problem";124 ga.Description = "A genetic algorithm which solves a gr ouping problem using the linear linkage encoding.";124 ga.Name = "Genetic Algorithm - Graph Coloring"; 125 ga.Description = "A genetic algorithm which solves a graph coloring problem using the linear linkage encoding."; 125 126 ga.Problem = problem; 126 127 SamplesUtils.ConfigureGeneticAlgorithmParameters<TournamentSelector, MultiLinearLinkageCrossover, MultiLinearLinkageManipulator>(
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