[6351] | 1 | #region License Information
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| 2 | /* HeuristicLab
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[11170] | 3 | * Copyright (C) 2002-2014 Heuristic and Evolutionary Algorithms Laboratory (HEAL)
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[6351] | 4 | *
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| 5 | * This file is part of HeuristicLab.
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| 6 | *
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| 7 | * HeuristicLab is free software: you can redistribute it and/or modify
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| 8 | * it under the terms of the GNU General Public License as published by
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| 9 | * the Free Software Foundation, either version 3 of the License, or
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| 10 | * (at your option) any later version.
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| 11 | *
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| 12 | * HeuristicLab is distributed in the hope that it will be useful,
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| 13 | * but WITHOUT ANY WARRANTY; without even the implied warranty of
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| 14 | * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
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| 15 | * GNU General Public License for more details.
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| 16 | *
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| 17 | * You should have received a copy of the GNU General Public License
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| 18 | * along with HeuristicLab. If not, see <http://www.gnu.org/licenses/>.
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| 19 | */
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| 20 | #endregion
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| 21 |
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| 22 | using System;
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| 23 | using System.Linq;
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| 24 | using HeuristicLab.Analysis;
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| 25 | using HeuristicLab.Common;
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| 26 | using HeuristicLab.Core;
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| 27 | using HeuristicLab.Data;
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| 28 | using HeuristicLab.Operators;
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| 29 | using HeuristicLab.Optimization;
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| 30 | using HeuristicLab.Optimization.Operators;
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| 31 | using HeuristicLab.Parameters;
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| 32 | using HeuristicLab.Persistence.Default.CompositeSerializers.Storable;
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| 33 | using HeuristicLab.Random;
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| 34 |
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| 35 | namespace HeuristicLab.Problems.QuadraticAssignment.Algorithms {
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[6586] | 36 | [Item("Robust Taboo Search", "The algorithm is described in Taillard, E. 1991. Robust Taboo Search for the Quadratic Assignment Problem. Parallel Computing 17, pp. 443-455.")]
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[6351] | 37 | [Creatable("Algorithms")]
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| 38 | [StorableClass]
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[6586] | 39 | public sealed class RobustTabooSearch : HeuristicOptimizationEngineAlgorithm, IStorableContent {
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[6351] | 40 | public string Filename { get; set; }
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| 41 |
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| 42 | #region Problem Properties
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| 43 | public override Type ProblemType {
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| 44 | get { return typeof(QuadraticAssignmentProblem); }
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| 45 | }
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| 46 | public new QuadraticAssignmentProblem Problem {
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| 47 | get { return (QuadraticAssignmentProblem)base.Problem; }
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| 48 | set { base.Problem = value; }
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| 49 | }
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| 50 | #endregion
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| 51 |
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| 52 | #region Parameter Properties
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[7040] | 53 | public IValueParameter<MultiAnalyzer> AnalyzerParameter {
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| 54 | get { return (IValueParameter<MultiAnalyzer>)Parameters["Analyzer"]; }
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[6351] | 55 | }
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[6953] | 56 | public FixedValueParameter<IntValue> SeedParameter {
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[6351] | 57 | get { return (FixedValueParameter<IntValue>)Parameters["Seed"]; }
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| 58 | }
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[6953] | 59 | public FixedValueParameter<BoolValue> SetSeedRandomlyParameter {
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[6351] | 60 | get { return (FixedValueParameter<BoolValue>)Parameters["SetSeedRandomly"]; }
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| 61 | }
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[6953] | 62 | public FixedValueParameter<IntValue> MaximumIterationsParameter {
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[6351] | 63 | get { return (FixedValueParameter<IntValue>)Parameters["MaximumIterations"]; }
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| 64 | }
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[6953] | 65 | public FixedValueParameter<IntValue> MinimumTabuTenureParameter {
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[6351] | 66 | get { return (FixedValueParameter<IntValue>)Parameters["MinimumTabuTenure"]; }
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| 67 | }
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[6953] | 68 | public FixedValueParameter<IntValue> MaximumTabuTenureParameter {
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[6351] | 69 | get { return (FixedValueParameter<IntValue>)Parameters["MaximumTabuTenure"]; }
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| 70 | }
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[6953] | 71 | public FixedValueParameter<BoolValue> UseAlternativeAspirationParameter {
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[6351] | 72 | get { return (FixedValueParameter<BoolValue>)Parameters["UseAlternativeAspiration"]; }
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| 73 | }
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[6953] | 74 | public FixedValueParameter<IntValue> AlternativeAspirationTenureParameter {
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[6351] | 75 | get { return (FixedValueParameter<IntValue>)Parameters["AlternativeAspirationTenure"]; }
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| 76 | }
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[6953] | 77 | public FixedValueParameter<BoolValue> UseNewTabuTenureAdaptionSchemeParameter {
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[6593] | 78 | get { return (FixedValueParameter<BoolValue>)Parameters["UseNewTabuTenureAdaptionScheme"]; }
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| 79 | }
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[7040] | 80 | public FixedValueParameter<BoolValue> TerminateOnOptimalSolutionParameter {
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| 81 | get { return (FixedValueParameter<BoolValue>)Parameters["TerminateOnOptimalSolution"]; }
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| 82 | }
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[6351] | 83 | #endregion
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| 84 |
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| 85 | #region Properties
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| 86 | public int Seed {
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| 87 | get { return SeedParameter.Value.Value; }
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| 88 | set { SeedParameter.Value.Value = value; }
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| 89 | }
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| 90 | public bool SetSeedRandomly {
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| 91 | get { return SetSeedRandomlyParameter.Value.Value; }
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| 92 | set { SetSeedRandomlyParameter.Value.Value = value; }
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| 93 | }
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| 94 | public int MaximumIterations {
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| 95 | get { return MaximumIterationsParameter.Value.Value; }
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| 96 | set { MaximumIterationsParameter.Value.Value = value; }
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| 97 | }
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| 98 | public int MinimumTabuTenure {
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| 99 | get { return MinimumTabuTenureParameter.Value.Value; }
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| 100 | set { MinimumTabuTenureParameter.Value.Value = value; }
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| 101 | }
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| 102 | public int MaximumTabuTenure {
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| 103 | get { return MaximumTabuTenureParameter.Value.Value; }
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| 104 | set { MaximumTabuTenureParameter.Value.Value = value; }
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| 105 | }
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| 106 | public bool UseAlternativeAspiration {
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| 107 | get { return UseAlternativeAspirationParameter.Value.Value; }
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| 108 | set { UseAlternativeAspirationParameter.Value.Value = value; }
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| 109 | }
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| 110 | public int AlternativeAspirationTenure {
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| 111 | get { return AlternativeAspirationTenureParameter.Value.Value; }
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| 112 | set { AlternativeAspirationTenureParameter.Value.Value = value; }
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| 113 | }
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[6593] | 114 | public bool UseNewTabuTenureAdaptionScheme {
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| 115 | get { return UseNewTabuTenureAdaptionSchemeParameter.Value.Value; }
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| 116 | set { UseNewTabuTenureAdaptionSchemeParameter.Value.Value = value; }
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| 117 | }
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[7040] | 118 | public bool TerminateOnOptimalSolution {
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| 119 | get { return TerminateOnOptimalSolutionParameter.Value.Value; }
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| 120 | set { TerminateOnOptimalSolutionParameter.Value.Value = value; }
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| 121 | }
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[6351] | 122 | #endregion
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| 123 |
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| 124 | [Storable]
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| 125 | private SolutionsCreator solutionsCreator;
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| 126 | [Storable]
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[6586] | 127 | private RobustTabooSeachOperator mainOperator;
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[6351] | 128 | [Storable]
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| 129 | private BestAverageWorstQualityAnalyzer qualityAnalyzer;
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| 130 |
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| 131 | [StorableConstructor]
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[6586] | 132 | private RobustTabooSearch(bool deserializing) : base(deserializing) { }
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| 133 | private RobustTabooSearch(RobustTabooSearch original, Cloner cloner)
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[6351] | 134 | : base(original, cloner) {
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| 135 | solutionsCreator = cloner.Clone(original.solutionsCreator);
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| 136 | mainOperator = cloner.Clone(original.mainOperator);
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| 137 | qualityAnalyzer = cloner.Clone(original.qualityAnalyzer);
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[6586] | 138 | RegisterEventHandlers();
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[6351] | 139 | }
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[6586] | 140 | public RobustTabooSearch() {
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[7040] | 141 | Parameters.Add(new ValueParameter<MultiAnalyzer>("Analyzer", "The analyzers that are applied after each iteration.", new MultiAnalyzer()));
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[6351] | 142 | Parameters.Add(new FixedValueParameter<IntValue>("Seed", "The seed value of the random number generator.", new IntValue(0)));
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| 143 | Parameters.Add(new FixedValueParameter<BoolValue>("SetSeedRandomly", "True whether the seed should be set randomly for each run, false if it should be fixed.", new BoolValue(true)));
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| 144 | Parameters.Add(new FixedValueParameter<IntValue>("MaximumIterations", "The number of iterations that the algorithm should run.", new IntValue(10000)));
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[6593] | 145 | Parameters.Add(new FixedValueParameter<IntValue>("MinimumTabuTenure", "The minimum tabu tenure.", new IntValue(10)));
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| 146 | Parameters.Add(new FixedValueParameter<IntValue>("MaximumTabuTenure", "The maximum tabu tenure.", new IntValue(20)));
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[6351] | 147 | Parameters.Add(new FixedValueParameter<BoolValue>("UseAlternativeAspiration", "True if the alternative aspiration condition should be used that takes moves that have not been made for some time above others.", new BoolValue(false)));
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[6594] | 148 | Parameters.Add(new FixedValueParameter<IntValue>("AlternativeAspirationTenure", "The time t that a move will be remembered for the alternative aspiration condition.", new IntValue(int.MaxValue)));
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[7040] | 149 | Parameters.Add(new FixedValueParameter<BoolValue>("TerminateOnOptimalSolution", "True when the algorithm should stop if it reached a quality equal or smaller to the BestKnownQuality.", new BoolValue(false)));
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[6593] | 150 | Parameters.Add(new FixedValueParameter<BoolValue>("UseNewTabuTenureAdaptionScheme", @"In an updated version of his implementation, Eric Taillard introduced a different way to change the tabu tenure.
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| 151 | Instead of setting it uniformly between min and max, it will be set between 0 and max according to a right-skewed distribution.
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| 152 | Set this option to false if you want to optimize using the earlier 1991 version, and set to true if you want to optimize using the newer version.
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| 153 | Please note that the MinimumTabuTenure parameter has no effect in the new version.", new BoolValue(true)));
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[6351] | 154 |
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[7040] | 155 | TerminateOnOptimalSolutionParameter.Hidden = true;
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| 156 |
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[6351] | 157 | qualityAnalyzer = new BestAverageWorstQualityAnalyzer();
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| 158 | qualityAnalyzer.ResultsParameter.ActualName = "Results";
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| 159 | AnalyzerParameter.Value.Operators.Add(qualityAnalyzer);
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| 160 |
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| 161 | RandomCreator randomCreator = new RandomCreator();
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| 162 | randomCreator.RandomParameter.ActualName = "Random";
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| 163 | randomCreator.SeedParameter.Value = null;
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| 164 | randomCreator.SeedParameter.ActualName = SeedParameter.Name;
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| 165 | randomCreator.SetSeedRandomlyParameter.Value = null;
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| 166 | randomCreator.SetSeedRandomlyParameter.ActualName = SetSeedRandomlyParameter.Name;
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| 167 |
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| 168 | VariableCreator variableCreator = new VariableCreator();
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| 169 | variableCreator.CollectedValues.Add(new ValueParameter<IntValue>("Iterations", new IntValue(0)));
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| 170 |
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| 171 | ResultsCollector resultsCollector = new ResultsCollector();
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| 172 | resultsCollector.CollectedValues.Add(new LookupParameter<IntValue>("Iterations", "The actual iteration."));
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| 173 |
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| 174 | solutionsCreator = new SolutionsCreator();
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| 175 | solutionsCreator.NumberOfSolutions = new IntValue(1);
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| 176 |
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| 177 | Placeholder analyzer = new Placeholder();
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| 178 | analyzer.Name = "(Analyzer)";
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| 179 | analyzer.OperatorParameter.ActualName = AnalyzerParameter.Name;
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| 180 |
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| 181 | UniformSubScopesProcessor ussp = new UniformSubScopesProcessor();
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| 182 |
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[6586] | 183 | mainOperator = new RobustTabooSeachOperator();
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[6351] | 184 | mainOperator.AlternativeAspirationTenureParameter.ActualName = AlternativeAspirationTenureParameter.Name;
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| 185 | mainOperator.BestQualityParameter.ActualName = "BestSoFarQuality";
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| 186 | mainOperator.IterationsParameter.ActualName = "Iterations";
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[6586] | 187 | mainOperator.LastMoveParameter.ActualName = "LastMove";
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[6351] | 188 | mainOperator.MaximumIterationsParameter.ActualName = MaximumIterationsParameter.Name;
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| 189 | mainOperator.MaximumTabuTenureParameter.ActualName = MaximumTabuTenureParameter.Name;
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| 190 | mainOperator.MinimumTabuTenureParameter.ActualName = MinimumTabuTenureParameter.Name;
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[6586] | 191 | mainOperator.MoveQualityMatrixParameter.ActualName = "MoveQualityMatrix";
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[6351] | 192 | mainOperator.RandomParameter.ActualName = "Random";
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[6586] | 193 | mainOperator.ResultsParameter.ActualName = "Results";
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[6351] | 194 | mainOperator.ShortTermMemoryParameter.ActualName = "ShortTermMemory";
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| 195 | mainOperator.UseAlternativeAspirationParameter.ActualName = UseAlternativeAspirationParameter.Name;
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| 196 |
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[6586] | 197 | ConditionalBranch qualityStopBranch = new ConditionalBranch();
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| 198 | qualityStopBranch.Name = "Terminate on optimal quality?";
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| 199 | qualityStopBranch.ConditionParameter.ActualName = "TerminateOnOptimalSolution";
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| 200 |
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| 201 | Comparator qualityComparator = new Comparator();
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| 202 | qualityComparator.Comparison = new Comparison(ComparisonType.Greater);
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| 203 | qualityComparator.LeftSideParameter.ActualName = "BestQuality";
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| 204 | qualityComparator.RightSideParameter.ActualName = "BestKnownQuality";
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| 205 | qualityComparator.ResultParameter.ActualName = "ContinueByQuality";
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| 206 |
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| 207 | ConditionalBranch continueByQualityBranch = new ConditionalBranch();
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| 208 | continueByQualityBranch.ConditionParameter.ActualName = "ContinueByQuality";
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| 209 |
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[6351] | 210 | IntCounter iterationsCounter = new IntCounter();
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| 211 | iterationsCounter.ValueParameter.ActualName = "Iterations";
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| 212 | iterationsCounter.Increment = new IntValue(1);
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| 213 |
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| 214 | Comparator comparator = new Comparator();
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| 215 | comparator.Name = "Iterations < MaximumIterations ?";
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| 216 | comparator.LeftSideParameter.ActualName = "Iterations";
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| 217 | comparator.RightSideParameter.ActualName = MaximumIterationsParameter.Name;
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| 218 | comparator.Comparison = new Comparison(ComparisonType.Less);
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| 219 | comparator.ResultParameter.ActualName = "ContinueByIteration";
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[6586] | 220 |
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| 221 | ConditionalBranch continueByIterationBranch = new ConditionalBranch();
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| 222 | continueByIterationBranch.ConditionParameter.ActualName = "ContinueByIteration";
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| 223 |
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| 224 | OperatorGraph.InitialOperator = randomCreator;
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| 225 | randomCreator.Successor = variableCreator;
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| 226 | variableCreator.Successor = resultsCollector;
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| 227 | resultsCollector.Successor = solutionsCreator;
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| 228 | solutionsCreator.Successor = analyzer;
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| 229 | analyzer.Successor = ussp;
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| 230 | ussp.Operator = mainOperator;
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| 231 | ussp.Successor = qualityStopBranch;
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| 232 | qualityStopBranch.FalseBranch = iterationsCounter;
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| 233 | qualityStopBranch.TrueBranch = qualityComparator;
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| 234 | qualityStopBranch.Successor = null;
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| 235 | qualityComparator.Successor = continueByQualityBranch;
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| 236 | continueByQualityBranch.TrueBranch = iterationsCounter;
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| 237 | continueByQualityBranch.FalseBranch = null;
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| 238 | continueByQualityBranch.Successor = null;
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[6351] | 239 | iterationsCounter.Successor = comparator;
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[6586] | 240 | comparator.Successor = continueByIterationBranch;
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| 241 | continueByIterationBranch.TrueBranch = analyzer;
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| 242 | continueByIterationBranch.FalseBranch = null;
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| 243 | continueByIterationBranch.Successor = null;
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[6351] | 244 |
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| 245 | RegisterEventHandlers();
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[8112] | 246 | Problem = new QuadraticAssignmentProblem();
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[6351] | 247 | }
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| 248 |
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| 249 | public override IDeepCloneable Clone(Cloner cloner) {
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[6586] | 250 | return new RobustTabooSearch(this, cloner);
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[6351] | 251 | }
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| 252 |
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[6593] | 253 | #region Event Handlers
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[6351] | 254 | protected override void OnProblemChanged() {
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| 255 | base.OnProblemChanged();
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| 256 | UpdateProblemSpecificParameters();
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| 257 | ParameterizeOperators();
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| 258 | UpdateAnalyzers();
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| 259 | }
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| 260 |
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| 261 | protected override void Problem_EvaluatorChanged(object sender, EventArgs e) {
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| 262 | base.Problem_EvaluatorChanged(sender, e);
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| 263 | ParameterizeOperators();
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| 264 | Problem.Evaluator.QualityParameter.ActualNameChanged += new EventHandler(Evaluator_QualityParameter_ActualNameChanged);
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| 265 | }
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| 266 |
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| 267 | protected override void Problem_OperatorsChanged(object sender, EventArgs e) {
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| 268 | base.Problem_OperatorsChanged(sender, e);
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| 269 | UpdateAnalyzers();
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| 270 | }
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| 271 |
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| 272 | private void Evaluator_QualityParameter_ActualNameChanged(object sender, EventArgs e) {
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| 273 | ParameterizeOperators();
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| 274 | }
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| 275 |
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[6586] | 276 | private void UseAlternativeAspirationParameter_ValueChanged(object sender, EventArgs e) {
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| 277 | UpdateAlternativeAspirationTenure();
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| 278 | }
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| 279 |
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| 280 | private void AlternativeAspirationTenureParameter_ValueChanged(object sender, EventArgs e) {
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[6593] | 281 | if (AlternativeAspirationTenure < MaximumIterations && !UseAlternativeAspiration) {
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| 282 | SetSilentlyUseAlternativeAspirationParameter(true);
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| 283 | } else if (AlternativeAspirationTenure >= MaximumIterations && UseAlternativeAspiration) {
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| 284 | SetSilentlyUseAlternativeAspirationParameter(false);
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[6351] | 285 | }
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| 286 | }
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| 287 |
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[6593] | 288 | private void MaximumIterationsParameter_ValueChanged(object sender, EventArgs e) {
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[6594] | 289 | if (MaximumIterations < AlternativeAspirationTenure && UseAlternativeAspiration) {
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[6593] | 290 | SetSilentlyUseAlternativeAspirationParameter(false);
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[6594] | 291 | } else if (MaximumIterations >= AlternativeAspirationTenure && !UseAlternativeAspiration) {
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[6593] | 292 | SetSilentlyUseAlternativeAspirationParameter(true);
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| 293 | }
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| 294 | }
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| 295 |
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| 296 | private void UseNewTabuTenureAdaptionSchemeParameter_ValueChanged(object sender, EventArgs e) {
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| 297 | UpdateProblemSpecificParameters();
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| 298 | }
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| 299 | #endregion
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| 300 |
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[6586] | 301 | [StorableHook(HookType.AfterDeserialization)]
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| 302 | private void AfterDeserialization() {
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[7040] | 303 | // BackwardsCompatibility3.3
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| 304 | #region Backwards compatible code, remove with 3.4
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| 305 | if (Parameters["Analyzer"] is FixedValueParameter<MultiAnalyzer>) {
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| 306 | MultiAnalyzer analyzer = AnalyzerParameter.Value;
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| 307 | Parameters.Remove("Analyzer");
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| 308 | Parameters.Add(new ValueParameter<MultiAnalyzer>("Analyzer", "The analyzers that are applied after each iteration.", analyzer));
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| 309 | }
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| 310 | #endregion
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[6586] | 311 | RegisterEventHandlers();
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| 312 | }
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| 313 |
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| 314 | private void RegisterEventHandlers() {
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| 315 | UseAlternativeAspirationParameter.Value.ValueChanged += new EventHandler(UseAlternativeAspirationParameter_ValueChanged);
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| 316 | AlternativeAspirationTenureParameter.Value.ValueChanged += new EventHandler(AlternativeAspirationTenureParameter_ValueChanged);
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[6593] | 317 | MaximumIterationsParameter.Value.ValueChanged += new EventHandler(MaximumIterationsParameter_ValueChanged);
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| 318 | UseNewTabuTenureAdaptionSchemeParameter.Value.ValueChanged += new EventHandler(UseNewTabuTenureAdaptionSchemeParameter_ValueChanged);
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[6586] | 319 | }
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| 320 |
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| 321 | protected override void RegisterProblemEvents() {
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| 322 | base.RegisterProblemEvents();
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| 323 | Problem.Evaluator.QualityParameter.ActualNameChanged += new EventHandler(Evaluator_QualityParameter_ActualNameChanged);
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| 324 | }
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| 325 |
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| 326 | protected override void DeregisterProblemEvents() {
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| 327 | Problem.Evaluator.QualityParameter.ActualNameChanged -= new EventHandler(Evaluator_QualityParameter_ActualNameChanged);
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| 328 | base.DeregisterProblemEvents();
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| 329 | }
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| 330 |
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[7209] | 331 | public override void Prepare() {
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| 332 | if (Problem != null) base.Prepare();
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| 333 | }
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| 334 |
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[6351] | 335 | public override void Start() {
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| 336 | if (ExecutionState == ExecutionState.Prepared) {
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[6586] | 337 | int dim = Problem.Weights.Rows;
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| 338 | IntMatrix shortTermMemory = new IntMatrix(dim, dim);
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| 339 | for (int i = 0; i < dim; i++)
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| 340 | for (int j = 0; j < dim; j++) {
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| 341 | shortTermMemory[i, j] = -(dim * (i + 1) + j + 1);
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[6351] | 342 | }
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| 343 |
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| 344 | GlobalScope.Variables.Add(new Variable("ShortTermMemory", shortTermMemory));
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[6586] | 345 | GlobalScope.Variables.Add(new Variable("MoveQualityMatrix", new DoubleMatrix(dim, dim)));
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[6351] | 346 | }
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| 347 | base.Start();
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| 348 | }
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| 349 |
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| 350 | private void UpdateProblemSpecificParameters() {
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[6593] | 351 | UpdateTabuTenure();
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[6586] | 352 | UpdateAlternativeAspirationTenure();
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[6351] | 353 | }
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| 354 |
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[6593] | 355 | private void UpdateTabuTenure() {
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| 356 | if (UseNewTabuTenureAdaptionScheme) {
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| 357 | MinimumTabuTenure = 0;
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| 358 | MaximumTabuTenure = 8 * Problem.Weights.Rows;
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| 359 | } else {
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| 360 | MinimumTabuTenure = (int)(0.9 * Problem.Weights.Rows);
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| 361 | MaximumTabuTenure = (int)(1.1 * Problem.Weights.Rows);
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| 362 | }
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| 363 | }
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| 364 |
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[6586] | 365 | private void UpdateAlternativeAspirationTenure() {
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| 366 | if (UseAlternativeAspiration) {
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[6593] | 367 | int n = Problem.Weights.Rows;
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| 368 | // Taillard has given two formulas for calculating default values: n^2 / 2 and later n^2 * 5
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| 369 | // However these do not really model the values he used in his original publication though
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| 370 | // The following formula is a linear regression model on the problem size and parameters
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| 371 | // given in Table 3 in Taillard1991 and was lower-bounded artificially by 100
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| 372 | AlternativeAspirationTenure = Math.Max(203 * n - 2274, 100);
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[6586] | 373 | } else {
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| 374 | AlternativeAspirationTenure = int.MaxValue;
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| 375 | }
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| 376 | }
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| 377 |
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[6351] | 378 | private void UpdateAnalyzers() {
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| 379 | AnalyzerParameter.Value.Operators.Clear();
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| 380 | if (Problem != null) {
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[6586] | 381 | foreach (IAnalyzer analyzer in ((IProblem)Problem).Operators.OfType<IAnalyzer>()) {
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[7172] | 382 | AnalyzerParameter.Value.Operators.Add(analyzer, analyzer.EnabledByDefault);
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[6586] | 383 | if (!(analyzer is BestQAPSolutionAnalyzer))
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| 384 | AnalyzerParameter.Value.Operators.SetItemCheckedState(analyzer, false);
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| 385 | }
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[6351] | 386 | }
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[7172] | 387 | AnalyzerParameter.Value.Operators.Add(qualityAnalyzer, qualityAnalyzer.EnabledByDefault);
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[6351] | 388 | }
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| 389 |
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| 390 | private void ParameterizeOperators() {
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| 391 | if (Problem != null) {
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| 392 | solutionsCreator.SolutionCreatorParameter.ActualName = Problem.SolutionCreatorParameter.Name;
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| 393 | solutionsCreator.EvaluatorParameter.ActualName = Problem.EvaluatorParameter.Name;
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| 394 |
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| 395 | qualityAnalyzer.QualityParameter.ActualName = Problem.Evaluator.QualityParameter.Name;
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| 396 |
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| 397 | mainOperator.DistancesParameter.ActualName = Problem.DistancesParameter.Name;
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| 398 | mainOperator.PermutationParameter.ActualName = Problem.SolutionCreator.PermutationParameter.ActualName;
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| 399 | mainOperator.QualityParameter.ActualName = Problem.Evaluator.QualityParameter.ActualName;
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| 400 | mainOperator.WeightsParameter.ActualName = Problem.WeightsParameter.Name;
|
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| 401 | }
|
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| 402 | }
|
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[6593] | 403 |
|
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| 404 | private void SetSilentlyUseAlternativeAspirationParameter(bool value) {
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| 405 | UseAlternativeAspirationParameter.Value.ValueChanged -= new EventHandler(UseAlternativeAspirationParameter_ValueChanged);
|
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| 406 | UseAlternativeAspiration = value;
|
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| 407 | UseAlternativeAspirationParameter.Value.ValueChanged += new EventHandler(UseAlternativeAspirationParameter_ValueChanged);
|
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| 408 | }
|
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[6351] | 409 | }
|
---|
| 410 | }
|
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