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Ignore:
Timestamp:
12/22/17 01:32:13 (6 years ago)
Author:
abeham
Message:

#1614: fixed bugs

File:
1 edited

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Added
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  • branches/GeneralizedQAP/HeuristicLab.Problems.GeneralizedQuadraticAssignment/3.3/Operators/LocalImprovers/ApproximateLocalSearch.cs

    r15555 r15558  
    7676      get { return (ILookupParameter<ResultCollection>)Parameters["Results"]; }
    7777    }
     78    public IValueLookupParameter<BoolValue> GreedyParameter {
     79      get { return (IValueLookupParameter<BoolValue>)Parameters["Greedy"]; }
     80    }
    7881
    7982    [StorableConstructor]
    … …  
    9295      Parameters.Add(new ValueLookupParameter<PercentValue>("OneMoveProbability", "The probability for performing a 1-move, which is the opposite of performing a 2-move.", new PercentValue(.5)));
    9396      Parameters.Add(new LookupParameter<ResultCollection>("Results", "The result collection that stores the results."));
     97      Parameters.Add(new ValueLookupParameter<BoolValue>("Greedy", "Whether to use a greedy selection strategy or a probabilistic one.", new BoolValue(true)));
    9498    }
    9599
    … …  
    100104    public static void Apply(IRandom random, GQAPSolution sol, int maxCLS,
    101105      double oneMoveProbability, int maximumIterations,
    102       GQAPInstance problemInstance, out int evaluatedSolutions) {
     106      GQAPInstance problemInstance, out int evaluatedSolutions, bool greedy = true) {
    103107      var fit = problemInstance.ToSingleObjective(sol.Evaluation);
    104108      var eval = sol.Evaluation;
    105109      Apply(random, sol.Assignment, ref fit, ref eval, maxCLS, oneMoveProbability, maximumIterations, problemInstance,
    106         out evaluatedSolutions);
     110        out evaluatedSolutions, greedy);
    107111      sol.Evaluation = eval;
    108112    }
    109113
    110       /// <summary>
    111       /// </summary>
    112       /// <param name="random">The random number generator to use.</param>
    113       /// <param name="assignment">The equipment-location assignment vector.</param>
    114       /// <param name="quality">The solution quality.</param>
    115       /// <param name="evaluation">The evaluation result of the solution.</param>
    116       /// <param name="maxCLS">The maximum number of candidates that should be found in each step.</param>
    117       /// <param name="oneMoveProbability">The probability for performing a 1-move, which is the opposite of performing a 2-move.</param>
    118       /// <param name="maximumIterations">The maximum number of iterations that should be performed each time the candidate list is generated.</param>
    119       /// <param name="problemInstance">The problem instance that contains the data.</param>
    120       /// <param name="evaluatedSolutions">The number of evaluated solutions.</param>
    121       public static void Apply(IRandom random, IntegerVector assignment,
     114    /// <summary>
     115    /// </summary>
     116    /// <param name="random">The random number generator to use.</param>
     117    /// <param name="assignment">The equipment-location assignment vector.</param>
     118    /// <param name="quality">The solution quality.</param>
     119    /// <param name="evaluation">The evaluation result of the solution.</param>
     120    /// <param name="maxCLS">The maximum number of candidates that should be found in each step.</param>
     121    /// <param name="oneMoveProbability">The probability for performing a 1-move, which is the opposite of performing a 2-move.</param>
     122    /// <param name="maximumIterations">The maximum number of iterations that should be performed each time the candidate list is generated.</param>
     123    /// <param name="problemInstance">The problem instance that contains the data.</param>
     124    /// <param name="evaluatedSolutions">The number of evaluated solutions.</param>
     125    /// <param name="greedy">Greedy selection performed better in 5 of 8 instances according to the paper</param>
     126    public static void Apply(IRandom random, IntegerVector assignment,
    122127      ref double quality, ref Evaluation evaluation, int maxCLS,
    123128      double oneMoveProbability, int maximumIterations,
    124       GQAPInstance problemInstance, out int evaluatedSolutions) {
     129      GQAPInstance problemInstance, out int evaluatedSolutions, bool greedy = true) {
    125130      evaluatedSolutions = 0;
    126131      var capacities = problemInstance.Capacities;
    … …  
    128133      var evaluations = 0.0;
    129134      var deltaEvaluationFactor = 1.0 / assignment.Length;
    130       var greedy = true; // greedy selection performed better in 5 of 8 instances according to the paper
    131135      while (true) { // line 1 of Algorithm 3
    132136        var count = 0; // line 2 of Algorithm 3
    … …  
    183187        MaximumIterationsParameter.ActualValue.Value,
    184188        ProblemInstanceParameter.ActualValue,
    185         out evaluatedSolutions);
     189        out evaluatedSolutions,
     190        GreedyParameter.ActualValue.Value);
    186191
    187192      EvaluationParameter.ActualValue = evaluation;
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