private LocalSearch CreateLocalSearchKnapsackSample() {
      LocalSearch ls = new LocalSearch();
      #region Problem Configuration
      KnapsackProblem problem = new KnapsackProblem();
      problem.BestKnownQuality = new DoubleValue(362);
      problem.BestKnownSolution = new HeuristicLab.Encodings.BinaryVectorEncoding.BinaryVector(new bool[] { 
       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});
      problem.EvaluatorParameter.Value = new KnapsackEvaluator();
      problem.SolutionCreatorParameter.Value = new RandomBinaryVectorCreator();
      problem.KnapsackCapacity.Value = 297;
      problem.Maximization.Value = true;
      problem.Penalty.Value = 1;
      problem.Values = new IntArray(new int[] { 
  6, 1, 1, 6, 7, 8, 7, 4, 2, 5, 2, 6, 7, 8, 7, 1, 7, 1, 9, 4, 2, 6, 5,  3, 5, 3, 3, 6, 5, 2, 4, 9, 4, 5, 7, 1, 4, 3, 5, 5, 8, 3, 6, 7, 3, 9, 7, 7, 5, 5, 7, 1, 4, 4, 3, 9, 5, 1, 6, 2, 2, 6, 1, 6, 5, 4, 4, 7, 1,  8, 9, 9, 7, 4, 3, 8, 7, 5, 7, 4, 4, 5});
      problem.Weights = new IntArray(new int[] { 
 1, 9, 3, 6, 5, 3, 8, 1, 7, 4, 2, 1, 2, 7, 9, 9, 8, 4, 9, 2, 4, 8, 3, 7, 5, 7, 5, 5, 1, 9, 8, 7, 8, 9, 1, 3, 3, 8, 8, 5, 1, 2, 4, 3, 6, 9, 4, 4, 9, 7, 4, 5, 1, 9, 7, 6, 7, 4, 7, 1, 2, 1, 2, 9, 8, 6, 8, 4, 7, 6, 7, 5, 3, 9, 4, 7, 4, 6, 1, 2, 5, 4});
      problem.Name = "Knapsack Problem";
      problem.Description = "Represents a Knapsack problem.";
      #endregion
      #region Algorithm Configuration
      ls.Name = "Local Search - Knapsack";
      ls.Description = "A local search algorithm that solves a randomly generated Knapsack problem";
      ls.Problem = problem;
      ls.MaximumIterations.Value = 1000;
      ls.MoveEvaluator = ls.MoveEvaluatorParameter.ValidValues
        .OfType<KnapsackOneBitflipMoveEvaluator>()
        .Single();
      ls.MoveGenerator = ls.MoveGeneratorParameter.ValidValues
        .OfType<ExhaustiveOneBitflipMoveGenerator>()
        .Single();
      ls.MoveMaker = ls.MoveMakerParameter.ValidValues
        .OfType<OneBitflipMoveMaker>()
        .Single();
      ls.SampleSize.Value = 100;
      ls.Seed.Value = 0;
      ls.SetSeedRandomly.Value = true;
      #endregion
      ls.Engine = new ParallelEngine.ParallelEngine();
      return ls;
    }
Ejemplo n.º 2
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 private LocalSearch(LocalSearch original, Cloner cloner)
     : base(original, cloner)
 {
     moveQualityAnalyzer = cloner.Clone(original.moveQualityAnalyzer);
     Initialize();
 }
Ejemplo n.º 3
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 private LocalSearch(LocalSearch original, Cloner cloner)
   : base(original, cloner) {
   moveQualityAnalyzer = cloner.Clone(original.moveQualityAnalyzer);
   Initialize();
 }