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Changeset 14477


Ignore:
Timestamp:
12/12/16 14:14:11 (7 years ago)
Author:
abeham
Message:

#2701:

  • Added TryGetBy(First|Second) method to BidirectionalDictionary
  • Updated linear linkage encoding
    • Added move generator and moves for shift, merge, split, and extract moves
    • Added unit test (Apply/Undo)
  • Updated MemPR (linear linkage)
    • Added basic tabu walk
  • Fixed bug in MemPR (permutation)
  • Updated Tests project
Location:
branches/MemPRAlgorithm
Files:
9 added
2 deleted
20 edited

Legend:

Unmodified
Added
Removed

  • branches/MemPRAlgorithm/HeuristicLab.Algorithms.MemPR/3.3/LinearLinkage/LinearLinkageMemPR.cs

    r14471 r14477  
    2626using HeuristicLab.Algorithms.MemPR.Interfaces;
    2727using HeuristicLab.Algorithms.MemPR.Util;
     28using HeuristicLab.Collections;
    2829using HeuristicLab.Common;
    2930using HeuristicLab.Core;
    … …  
    9293    }
    9394
    94     protected override int TabuWalk(ISingleObjectiveSolutionScope<Encodings.LinearLinkageEncoding.LinearLinkage> scope, int maxEvals, CancellationToken token, ISolutionSubspace<Encodings.LinearLinkageEncoding.LinearLinkage> subspace = null) {
    95       return 0;
    96       /*Func<Encodings.LinearLinkageEncoding.LinearLinkage, IRandom, double> eval = new EvaluationWrapper<Encodings.LinearLinkageEncoding.LinearLinkage>(Context.Problem, scope).Evaluate;
     95    protected override int TabuWalk(
     96        ISingleObjectiveSolutionScope<Encodings.LinearLinkageEncoding.LinearLinkage> scope,
     97        int maxEvals, CancellationToken token,
     98        ISolutionSubspace<Encodings.LinearLinkageEncoding.LinearLinkage> sub_space = null) {
     99      var maximization = Context.Problem.Maximization;
     100      var subspace = sub_space is LinearLinkageSolutionSubspace ? ((LinearLinkageSolutionSubspace)sub_space).Subspace : null;
     101      var evaluations = 0;
    97102      var quality = scope.Fitness;
    98       var lle = scope.Solution;
    99       var random = Context.Random;
    100       var evaluations = 0;
    101       var maximization = Context.Problem.Maximization;
     103      var bestQuality = quality;
    102104      if (double.IsNaN(quality)) {
    103         quality = eval(lle, random);
     105        Evaluate(scope, token);
     106        quality = scope.Fitness;
    104107        evaluations++;
    105       }
    106       Encodings.LinearLinkageEncoding.LinearLinkage bestOfTheWalk = null;
    107       double bestOfTheWalkF = double.NaN;
    108       var current = (Encodings.LinearLinkageEncoding.LinearLinkage)lle.Clone();
    109       var currentF = quality;
    110       var overallImprovement = false;
     108        if (evaluations >= maxEvals) return evaluations;
     109      }
     110      var currentScope = (ISingleObjectiveSolutionScope<Encodings.LinearLinkageEncoding.LinearLinkage>)scope.Clone();
     111      var current = currentScope.Solution;
     112
    111113      var tabu = new double[current.Length, current.Length];
    112114      for (var i = 0; i < current.Length; i++) {
    113115        for (var j = i; j < current.Length; j++) {
    114           tabu[i, j] = tabu[j, i] = double.MaxValue;
    115         }
    116         tabu[i, current[i]] = currentF;
    117       }
    118 
    119       var steps = 0;
    120       var stepsUntilBestOfWalk = 0;
     116          tabu[i, j] = tabu[j, i] = maximization ? double.MinValue : double.MaxValue;
     117        }
     118        tabu[i, current[i]] = quality;
     119      }
     120     
     121      // this dictionary holds the last relevant links
     122      var links = new BidirectionalDictionary<int, int>();
     123      bool allMoveTabu;
    121124      for (var iter = 0; iter < int.MaxValue; iter++) {
    122         var allTabu = true;
    123         var bestOfTheRestF = double.NaN;
    124         object bestOfTheRest = null;
    125         var improved = false;
    126         foreach () {
    127           if (subspace != null && !(subspace[swap.Index1, 0] && subspace[swap.Index2, 0]))
     125        allMoveTabu = true;
     126        // clear the dictionary before a new pass through the array is made
     127        links.Clear();
     128        for (var i = 0; i < current.Length; i++) {
     129          if (subspace != null && !subspace[i]) {
     130            links.RemoveBySecond(i);
     131            links.Add(i, current[i]);
    128132            continue;
    129 
    130 
    131           var q = eval(current, random);
    132           evaluations++;
    133           if (FitnessComparer.IsBetter(maximization, q, quality)) {
    134             overallImprovement = true;
    135             quality = q;
    136             for (var i = 0; i < current.Length; i++) lle[i] = current[i];
    137           }
    138           // check if it would not be an improvement to swap these into their positions
    139           var isTabu = !FitnessComparer.IsBetter(maximization, q, tabu[swap.Index1, current[swap.Index1]])
    140                     && !FitnessComparer.IsBetter(maximization, q, tabu[swap.Index2, current[swap.Index2]]);
    141           if (!isTabu) allTabu = false;
    142           if (FitnessComparer.IsBetter(maximization, q, currentF) && !isTabu) {
    143             if (FitnessComparer.IsBetter(maximization, q, bestOfTheWalkF)) {
    144               bestOfTheWalk = (Encodings.LinearLinkageEncoding.LinearLinkage)current.Clone();
    145               bestOfTheWalkF = q;
    146               stepsUntilBestOfWalk = steps;
    147             }
    148             steps++;
    149             improved = true;
    150             // perform the move
    151             currentF = q;
    152             // mark that to move them to their previous position requires to make an improvement
    153             tabu[swap.Index1, current[swap.Index2]] = maximization ? Math.Max(q, tabu[swap.Index1, current[swap.Index2]])
    154                                                                    : Math.Min(q, tabu[swap.Index1, current[swap.Index2]]);
    155             tabu[swap.Index2, current[swap.Index1]] = maximization ? Math.Max(q, tabu[swap.Index2, current[swap.Index1]])
    156                                                                    : Math.Min(q, tabu[swap.Index2, current[swap.Index1]]);
    157           } else { // undo the move
    158             if (!isTabu && FitnessComparer.IsBetter(maximization, q, bestOfTheRestF)) {
    159               bestOfTheRest = swap;
    160               bestOfTheRestF = q;
    161             }
    162             current[swap.Index2] = current[swap.Index1];
    163             current[swap.Index1] = h;
    164           }
     133          }
     134
     135          var next = current[i];
     136          foreach (var move in MoveGenerator.GenerateForItem(i, next, links)) {
     137            // we intend to break link i -> next
     138            var qualityToBreak = tabu[i, next];
     139            move.Apply(current);
     140            var qualityToRestore = tabu[i, current[i]]; // current[i] is new next
     141            Evaluate(currentScope, token);
     142            evaluations++;
     143            var moveF = currentScope.Fitness;
     144            var isNotTabu = FitnessComparer.IsBetter(maximization, moveF, qualityToBreak)
     145                         && FitnessComparer.IsBetter(maximization, moveF, qualityToRestore);
     146            if (isNotTabu) allMoveTabu = false;
     147            var isImprovement = FitnessComparer.IsBetter(maximization, moveF, bestQuality);
     148            if (isNotTabu || isImprovement) {
     149              if (maximization) {
     150                tabu[i, next] = Math.Max(tabu[i, next], moveF);
     151                tabu[i, current[i]] = Math.Max(tabu[i, current[i]], moveF);
     152              } else {
     153                tabu[i, next] = Math.Min(tabu[i, next], moveF);
     154                tabu[i, current[i]] = Math.Min(tabu[i, current[i]], moveF);
     155              }
     156              quality = moveF;
     157              if (isImprovement) bestQuality = quality;
     158
     159              move.UpdateLinks(links);
     160              break;
     161            } else move.Undo(current);
     162            if (evaluations >= maxEvals) break;
     163          }
     164          links.RemoveBySecond(i);
     165          links.Add(i, current[i]);
    165166          if (evaluations >= maxEvals) break;
    166         }
    167         if (!allTabu && !improved && bestOfTheRest != null) {
    168           tabu[bestOfTheRest.Index1, current[bestOfTheRest.Index1]] = maximization ? Math.Max(currentF, tabu[bestOfTheRest.Index1, current[bestOfTheRest.Index1]])
    169                                                                                    : Math.Min(currentF, tabu[bestOfTheRest.Index1, current[bestOfTheRest.Index1]]);
    170           tabu[bestOfTheRest.Index2, current[bestOfTheRest.Index2]] = maximization ? Math.Max(currentF, tabu[bestOfTheRest.Index2, current[bestOfTheRest.Index2]])
    171                                                                                    : Math.Min(currentF, tabu[bestOfTheRest.Index2, current[bestOfTheRest.Index2]]);
    172 
    173           var h = current[bestOfTheRest.Index1];
    174           current[bestOfTheRest.Index1] = current[bestOfTheRest.Index2];
    175           current[bestOfTheRest.Index2] = h;
    176 
    177           currentF = bestOfTheRestF;
    178           steps++;
    179         } else if (allTabu) break;
     167          if (token.IsCancellationRequested) break;
     168        }
     169        if (allMoveTabu) break;
    180170        if (evaluations >= maxEvals) break;
    181       }
    182       Context.IncrementEvaluatedSolutions(evaluations);
    183       if (!overallImprovement && bestOfTheWalk != null) {
    184         quality = bestOfTheWalkF;
    185         for (var i = 0; i < current.Length; i++) lle[i] = bestOfTheWalk[i];
    186       }
    187       return stepsUntilBestOfWalk;*/
     171        if (token.IsCancellationRequested) break;
     172      }
     173      return evaluations;
    188174    }
    189175

  • branches/MemPRAlgorithm/HeuristicLab.Algorithms.MemPR/3.3/LinearLinkage/LocalSearch/StaticAPI/ExhaustiveLocalSearch.cs

    r14466 r14477  
    4949            continue;
    5050          }
    51           var isFirst = !links.ContainsSecond(i);
    5251          var pred = -1;
     52          var isFirst = !links.TryGetBySecond(i, out pred);
    5353          var keepLink = false;
    5454          if (!isFirst) {
    55             pred = links.GetBySecond(i);
    5655            keepLink = subspace != null && !subspace[pred];
    5756          }

  • branches/MemPRAlgorithm/HeuristicLab.Algorithms.MemPR/3.3/MemPRAlgorithm.cs

    r14456 r14477  
    216216        Context.Problem = Problem;
    217217      }
     218
     219      if (MaximumExecutionTime.HasValue)
     220        CancellationTokenSource.CancelAfter(MaximumExecutionTime.Value);
    218221
    219222      IExecutionContext context = null;

  • branches/MemPRAlgorithm/HeuristicLab.Algorithms.MemPR/3.3/Permutation/PermutationMemPR.cs

    r14466 r14477  
    187187      for (var i = 0; i < current.Length; i++) {
    188188        for (var j = i; j < current.Length; j++) {
    189           tabu[i, j] = tabu[j, i] = double.MaxValue;
     189          tabu[i, j] = tabu[j, i] = maximization ? double.MinValue : double.MaxValue;
    190190        }
    191191        tabu[i, current[i]] = currentF;

  • branches/MemPRAlgorithm/HeuristicLab.Collections/3.3/BidirectionalDictionary.cs

    r14185 r14477  
    135135    }
    136136
     137    public bool TryGetByFirst(TFirst key, out TSecond secondValue) {
     138      return firstToSecond.TryGetValue(key, out secondValue);
     139    }
     140
     141    public bool TryGetBySecond(TSecond key, out TFirst firstValue) {
     142      return secondToFirst.TryGetValue(key, out firstValue);
     143    }
     144
    137145    public void Clear() {
    138146      firstToSecond.Clear();

  • branches/MemPRAlgorithm/HeuristicLab.Encodings.LinearLinkageEncoding/3.3/HeuristicLab.Encodings.LinearLinkageEncoding-3.3.csproj

    r14471 r14477  
    181181    <Compile Include="Moves\Swap\Swap2MoveGenerator.cs" />
    182182    <Compile Include="Moves\Swap\Swap2MoveMaker.cs" />
     183    <Compile Include="Moves\ExtractMove.cs" />
     184    <Compile Include="Moves\MergeMove.cs" />
     185    <Compile Include="Moves\Move.cs" />
     186    <Compile Include="Moves\ShiftMove.cs" />
     187    <Compile Include="Moves\SplitMove.cs" />
     188    <Compile Include="Moves\StaticAPI\MoveGenerator.cs" />
    183189    <Compile Include="ShakingOperators\LLEShakingOperator.cs" />
    184190    <Compile Include="SimilarityCalculators\HammingSimilarityCalculator.cs" />

  • branches/MemPRAlgorithm/HeuristicLab.Problems.Instances.DIMACS/3.3

    • Property svn:ignore

      •  

        old new  
         1*.aps
         2*.eto
         3*.user
         4ClientBin
         5GeneratedArtifacts
         6Plugin.cs
        17[Bb]in
        2 obj
        38[Dd]ebug
        49[Rr]elease
        5 *.user
        6 *.aps
        7 *.eto
        8 ClientBin
        9 GeneratedArtifacts
        1010_Pvt_Extensions
         11obj

  • branches/MemPRAlgorithm/HeuristicLab.Problems.Instances.DIMACS/3.3/Properties

    • Property svn:ignore set to
      AssemblyInfo.cs

  • branches/MemPRAlgorithm/HeuristicLab.Tests/HeuristicLab-3.3/DeepCloneableCloningTest.cs

    r14209 r14477  
    4242    public DeepCloneableCloningTest() {
    4343      excludedTypes = new HashSet<Type> {
    44         typeof (HeuristicLab.Problems.DataAnalysis.Dataset),
    45         typeof (HeuristicLab.Problems.TravelingSalesman.DistanceMatrix),
    46         typeof (HeuristicLab.Problems.DataAnalysis.ClassificationEnsembleSolution),
    47         typeof (HeuristicLab.Problems.DataAnalysis.RegressionEnsembleSolution),
    48         typeof (HeuristicLab.Problems.Orienteering.DistanceMatrix),
    49         typeof (HeuristicLab.Problems.PTSP.DistanceMatrix)
     44        typeof (global::HeuristicLab.Problems.DataAnalysis.Dataset),
     45        typeof (global::HeuristicLab.Problems.TravelingSalesman.DistanceMatrix),
     46        typeof (global::HeuristicLab.Problems.DataAnalysis.ClassificationEnsembleSolution),
     47        typeof (global::HeuristicLab.Problems.DataAnalysis.RegressionEnsembleSolution),
     48        typeof (global::HeuristicLab.Problems.Orienteering.DistanceMatrix),
     49        typeof (global::HeuristicLab.Problems.PTSP.DistanceMatrix)
    5050      };
    5151      excludedTypes.Add(typeof(SymbolicExpressionGrammar).Assembly.GetType("HeuristicLab.Encodings.SymbolicExpressionTreeEncoding.EmptySymbolicExpressionTreeGrammar"));
    5252
    53       foreach (var symbolType in ApplicationManager.Manager.GetTypes(typeof(HeuristicLab.Encodings.SymbolicExpressionTreeEncoding.Symbol)))
     53      foreach (var symbolType in ApplicationManager.Manager.GetTypes(typeof(global::HeuristicLab.Encodings.SymbolicExpressionTreeEncoding.Symbol)))
    5454        excludedTypes.Add(symbolType);
    5555      // SimpleSymbol is a non-discoverable type and thus needs to be added manually
    56       excludedTypes.Add(typeof(HeuristicLab.Encodings.SymbolicExpressionTreeEncoding.SimpleSymbol));
    57       foreach (var grammarType in ApplicationManager.Manager.GetTypes(typeof(HeuristicLab.Encodings.SymbolicExpressionTreeEncoding.SymbolicExpressionGrammarBase)))
     56      excludedTypes.Add(typeof(global::HeuristicLab.Encodings.SymbolicExpressionTreeEncoding.SimpleSymbol));
     57      foreach (var grammarType in ApplicationManager.Manager.GetTypes(typeof(global::HeuristicLab.Encodings.SymbolicExpressionTreeEncoding.SymbolicExpressionGrammarBase)))
    5858        excludedTypes.Add(grammarType);
    5959    }

  • branches/MemPRAlgorithm/HeuristicLab.Tests/HeuristicLab-3.3/Samples/AlpsSampleTest.cs

    r14185 r14477  
    8888      TravelingSalesmanProblem tspProblem = new TravelingSalesmanProblem();
    8989      tspProblem.Load(provider.LoadData(instance));
    90       tspProblem.UseDistanceMatrix.Value = true;
     90      tspProblem.UseDistanceMatrix = true;
    9191      #endregion
    9292      #region Algorithm Configuration

  • branches/MemPRAlgorithm/HeuristicLab.Tests/HeuristicLab-3.3/Samples/GATspSampleTest.cs

    r14185 r14477  
    6565      TravelingSalesmanProblem tspProblem = new TravelingSalesmanProblem();
    6666      tspProblem.Load(provider.LoadData(instance));
    67       tspProblem.UseDistanceMatrix.Value = true;
     67      tspProblem.UseDistanceMatrix = true;
    6868      #endregion
    6969      #region Algorithm Configuration

  • branches/MemPRAlgorithm/HeuristicLab.Tests/HeuristicLab-3.3/Samples/GPMultiplexerSampleTest.cs

    r14185 r14477  
    5555
    5656    public static OffspringSelectionGeneticAlgorithm CreateGpMultiplexerSample() {
    57       var problem = new HeuristicLab.Problems.GeneticProgramming.Boolean.MultiplexerProblem();
     57      var problem = new global::HeuristicLab.Problems.GeneticProgramming.Boolean.MultiplexerProblem();
    5858      problem.Name = "11-Multiplexer Problem";
    5959      problem.Encoding.TreeLength = 50;

  • branches/MemPRAlgorithm/HeuristicLab.Tests/HeuristicLab-3.3/Samples/GeSymbolicRegressionSampleTest.cs

    r14185 r14477  
    5757
    5858      #region Problem Configuration
    59       var problem = new HeuristicLab.Problems.GrammaticalEvolution.GEArtificialAntProblem();
     59      var problem = new global::HeuristicLab.Problems.GrammaticalEvolution.GEArtificialAntProblem();
    6060      #endregion
    6161      #region Algorithm Configuration
    … …  
    9696
    9797      #region Problem Configuration
    98       var problem = new HeuristicLab.Problems.GrammaticalEvolution.GESymbolicRegressionSingleObjectiveProblem();
     98      var problem = new global::HeuristicLab.Problems.GrammaticalEvolution.GESymbolicRegressionSingleObjectiveProblem();
    9999
    100100      #endregion

  • branches/MemPRAlgorithm/HeuristicLab.Tests/HeuristicLab-3.3/Samples/IslandGaTspSampleTest.cs

    r14185 r14477  
    6464      TravelingSalesmanProblem tspProblem = new TravelingSalesmanProblem();
    6565      tspProblem.Load(provider.LoadData(instance));
    66       tspProblem.UseDistanceMatrix.Value = true;
     66      tspProblem.UseDistanceMatrix = true;
    6767      #endregion
    6868      #region Algorithm Configuration

  • branches/MemPRAlgorithm/HeuristicLab.Tests/HeuristicLab-3.3/Samples/LocalSearchKnapsackSampleTest.cs

    r14185 r14477  
    6060      KnapsackProblem problem = new KnapsackProblem();
    6161      problem.BestKnownQuality = new DoubleValue(362);
    62       problem.BestKnownSolution = new HeuristicLab.Encodings.BinaryVectorEncoding.BinaryVector(new bool[] {
     62      problem.BestKnownSolution = new global::HeuristicLab.Encodings.BinaryVectorEncoding.BinaryVector(new bool[] {
    6363       true , false, false, true , true , true , true , true , false, true , true , true , true , true , true , false, true , false, true , true , false, true , true , false, true , false, true , true , true , false, true , true , false, true , true , false, true , false, true , true , true , true , true , true , true , true , true , true , true , true , true , false, true , false, false, true , true , false, true , true , true , true , true , true , true , true , false, true , false, true , true , true , true , false, true , true , true , true , true , true , true , true});
    6464      problem.EvaluatorParameter.Value = new KnapsackEvaluator();

  • branches/MemPRAlgorithm/HeuristicLab.Tests/HeuristicLab-3.3/Samples/TabuSearchTspSampleTest.cs

    r14185 r14477  
    6262      TravelingSalesmanProblem tspProblem = new TravelingSalesmanProblem();
    6363      tspProblem.Load(provider.LoadData(instance));
    64       tspProblem.UseDistanceMatrix.Value = true;
     64      tspProblem.UseDistanceMatrix = true;
    6565      #endregion
    6666      #region Algorithm Configuration
    … …  
    7676      ts.MoveGenerator = moveGenerator;
    7777      var moveEvaluator = ts.MoveEvaluatorParameter.ValidValues
    78         .OfType<TSPInversionMoveRoundedEuclideanPathEvaluator>()
     78        .OfType<TSPInversionMovePathEvaluator>()
    7979        .Single();
    8080      ts.MoveEvaluator = moveEvaluator;

  • branches/MemPRAlgorithm/HeuristicLab.Tests/HeuristicLab-3.3/Samples/VnsTspSampleTest.cs

    r14185 r14477  
    6666{48, 71}, {49, 71}, {50, 71}, {44, 70}, {45, 70}, {52, 70}, {53, 70}, {54, 70}, {41, 69}, {42, 69}, {55, 69}, {56, 69}, {40, 68}, {56, 68}, {57, 68}, {39, 67}, {57, 67}, {58, 67}, {59, 67}, {38, 66}, {59, 66}, {60, 66}, {37, 65}, {60, 65}, {36, 64}, {43, 64}, {35, 63}, {37, 63}, {41, 63}, {42, 63}, {43, 63}, {47, 63}, {61, 63}, {40, 62}, {41, 62}, {42, 62}, {43, 62}, {45, 62}, {46, 62}, {47, 62}, {62, 62}, {34, 61}, {38, 61}, {39, 61}, {42, 61}, {43, 61}, {44, 61}, {45, 61}, {46, 61}, {47, 61}, {52, 61}, {62, 61}, {63, 61}, {26, 60}, {38, 60}, {42, 60}, {43, 60}, {44, 60}, {46, 60}, {47, 60}, {63, 60}, {23, 59}, {24, 59}, {27, 59}, {29, 59}, {30, 59}, {31, 59}, {33, 59}, {42, 59}, {46, 59}, {47, 59}, {63, 59}, {21, 58}, {32, 58}, {33, 58}, {34, 58}, {35, 58}, {46, 58}, {47, 58}, {48, 58}, {53, 58}, {21, 57}, {35, 57}, {47, 57}, {48, 57}, {53, 57}, {36, 56}, {37, 56}, {46, 56}, {47, 56}, {48, 56}, {64, 56}, {65, 56}, {20, 55}, {38, 55}, {46, 55}, {47, 55}, {48, 55}, {52, 55}, 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    6767      });
    68       tspProblem.BestKnownQuality = new DoubleValue(867);
     68      tspProblem.BestKnownQuality = 867;
    6969
    70       tspProblem.EvaluatorParameter.Value = new TSPRoundedEuclideanPathEvaluator();
     70      tspProblem.DistanceFunction = TSPDistanceFunction.RoundedEuclidean;
    7171      tspProblem.SolutionCreatorParameter.Value = new RandomPermutationCreator();
    72       tspProblem.UseDistanceMatrix.Value = true;
     72      tspProblem.UseDistanceMatrix = true;
    7373      tspProblem.Name = "Funny TSP";
    7474      tspProblem.Description = "Represents a symmetric Traveling Salesman Problem.";
    … …  
    8787        .Single();
    8888      localImprovement.MoveEvaluator = localImprovement.MoveEvaluatorParameter.ValidValues
    89         .OfType<TSPInversionMoveRoundedEuclideanPathEvaluator>()
     89        .OfType<TSPInversionMovePathEvaluator>()
    9090        .Single();
    9191      localImprovement.MoveMaker = localImprovement.MoveMakerParameter.ValidValues

  • branches/MemPRAlgorithm/HeuristicLab.Tests/HeuristicLab.Algorithms.DataAnalysis-3.4/SupportVectorMachineTest.cs

    r14185 r14477  
    6161      var cv = new CrossValidation();
    6262      cv.Algorithm = new SupportVectorRegression();
    63       var rand = new HeuristicLab.Random.MersenneTwister();
     63      var rand = new global::HeuristicLab.Random.MersenneTwister();
    6464      double[,] data = GenerateData(1000, rand);
    6565      List<string> variables = new List<string>() { "x1", "x2", "x3", "x4", "x5", "x6", "x7", "x8", "x9", "x10", "y" };

  • branches/MemPRAlgorithm/HeuristicLab.Tests/HeuristicLab.Problems.TravelingSalesman-3.3/TSPMoveEvaluatorTest.cs

    r14185 r14477  
    6161    [TestProperty("Time", "short")]
    6262    public void InversionMoveEvaluatorTest() {
    63       var evaluator = new TSPRoundedEuclideanPathEvaluator();
     63      /*var evaluator = new TSPRoundedEuclideanPathEvaluator();
    6464      var moveEvaluator = new TSPInversionMoveRoundedEuclideanPathEvaluator();
    6565      double beforeMatrix = TSPDistanceMatrixEvaluator.Apply(distances, tour);
    … …  
    8787        beforeMatrix = afterMatrix;
    8888        beforeCoordinates = afterCoordinates;
    89       }
     89      }*/
    9090    }
    9191
    … …  
    9494    [TestProperty("Time", "short")]
    9595    public void TranslocationMoveEvaluatorTest() {
    96       var evaluator = new TSPRoundedEuclideanPathEvaluator();
     96      /*var evaluator = new TSPRoundedEuclideanPathEvaluator();
    9797      var moveEvaluator = new TSPTranslocationMoveRoundedEuclideanPathEvaluator();
    9898      double beforeMatrix = TSPDistanceMatrixEvaluator.Apply(distances, tour);
    … …  
    119119        beforeMatrix = afterMatrix;
    120120        beforeCoordinates = afterCoordinates;
    121       }
     121      }*/
    122122    }
    123123

  • branches/MemPRAlgorithm/HeuristicLab.Tests/HeuristicLab.Tests.csproj

    r14354 r14477  
    510510    <Compile Include="HeuristicLab.Encodings.IntegerVectorEncoding-3.3\SinglePointCrossoverTest.cs" />
    511511    <Compile Include="HeuristicLab.Encodings.IntegerVectorEncoding-3.3\UniformOnePositionManipulatorTest.cs" />
     512    <Compile Include="HeuristicLab.Encodings.LinearLinkageEncoding-3.3\MoveTests.cs" />
    512513    <Compile Include="HeuristicLab.Encodings.PermutationEncoding-3.3\Auxiliary.cs" />
    513514    <Compile Include="HeuristicLab.Encodings.PermutationEncoding-3.3\CosaCrossoverTest.cs" />
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