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source: stable/HeuristicLab.Problems.VehicleRouting/3.4/Analyzer/ConstraintRelaxation/Capacitated/CapacityRelaxationVRPAnalyzer.cs @ 12005

Last change on this file since 12005 was 12005, checked in by abeham, 9 years ago

#2174, #2282: merged revisions r11961,r11963,r11967,r11970,r11971,r11982,r11984,r11998,r12001,r12002,r12003,r12004,r11939,r11945,r11956,r11958,r11959,r11960,r11983,r11987,r11988,r11990,r11993,r11994,r11996,r11999,r12000 to stable

File size: 6.9 KB
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1#region License Information
2/* HeuristicLab
3 * Copyright (C) 2002-2014 Heuristic and Evolutionary Algorithms Laboratory (HEAL)
4 *
5 * This file is part of HeuristicLab.
6 *
7 * HeuristicLab is free software: you can redistribute it and/or modify
8 * it under the terms of the GNU General Public License as published by
9 * the Free Software Foundation, either version 3 of the License, or
10 * (at your option) any later version.
11 *
12 * HeuristicLab is distributed in the hope that it will be useful,
13 * but WITHOUT ANY WARRANTY; without even the implied warranty of
14 * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
15 * GNU General Public License for more details.
16 *
17 * You should have received a copy of the GNU General Public License
18 * along with HeuristicLab. If not, see <http://www.gnu.org/licenses/>.
19 */
20#endregion
21
22using HeuristicLab.Common;
23using HeuristicLab.Core;
24using HeuristicLab.Data;
25using HeuristicLab.Operators;
26using HeuristicLab.Optimization;
27using HeuristicLab.Parameters;
28using HeuristicLab.Persistence.Default.CompositeSerializers.Storable;
29using HeuristicLab.Problems.VehicleRouting.Interfaces;
30using HeuristicLab.Problems.VehicleRouting.Variants;
31
32namespace HeuristicLab.Problems.VehicleRouting {
33  /// <summary>
34  /// An operator for adaptive constraint relaxation.
35  /// </summary>
36  [Item("CapacityRelaxationVRPAnalyzer", "An operator for adaptively relaxing the capacity constraints.")]
37  [StorableClass]
38  public class CapacityRelaxationVRPAnalyzer : SingleSuccessorOperator, IAnalyzer, ICapacitatedOperator, ISingleObjectiveOperator {
39    public ILookupParameter<IVRPProblemInstance> ProblemInstanceParameter {
40      get { return (ILookupParameter<IVRPProblemInstance>)Parameters["ProblemInstance"]; }
41    }
42    public ScopeTreeLookupParameter<IVRPEncoding> VRPToursParameter {
43      get { return (ScopeTreeLookupParameter<IVRPEncoding>)Parameters["VRPTours"]; }
44    }
45    public ScopeTreeLookupParameter<DoubleValue> QualityParameter {
46      get { return (ScopeTreeLookupParameter<DoubleValue>)Parameters["Quality"]; }
47    }
48
49    public ScopeTreeLookupParameter<DoubleValue> OverloadParameter {
50      get { return (ScopeTreeLookupParameter<DoubleValue>)Parameters["Overload"]; }
51    }
52
53    public IValueParameter<DoubleValue> SigmaParameter {
54      get { return (IValueParameter<DoubleValue>)Parameters["Sigma"]; }
55    }
56    public IValueParameter<DoubleValue> PhiParameter {
57      get { return (IValueParameter<DoubleValue>)Parameters["Phi"]; }
58    }
59    public IValueParameter<DoubleValue> MinPenaltyFactorParameter {
60      get { return (IValueParameter<DoubleValue>)Parameters["MinPenaltyFactor"]; }
61    }
62    public IValueParameter<DoubleValue> MaxPenaltyFactorParameter {
63      get { return (IValueParameter<DoubleValue>)Parameters["MaxPenaltyFactor"]; }
64    }
65
66    public ValueLookupParameter<ResultCollection> ResultsParameter {
67      get { return (ValueLookupParameter<ResultCollection>)Parameters["Results"]; }
68    }
69
70    public bool EnabledByDefault {
71      get { return false; }
72    }
73
74    [StorableConstructor]
75    protected CapacityRelaxationVRPAnalyzer(bool deserializing) : base(deserializing) { }
76
77    public CapacityRelaxationVRPAnalyzer()
78      : base() {
79      Parameters.Add(new LookupParameter<IVRPProblemInstance>("ProblemInstance", "The problem instance."));
80      Parameters.Add(new ScopeTreeLookupParameter<IVRPEncoding>("VRPTours", "The VRP tours which should be evaluated."));
81      Parameters.Add(new ScopeTreeLookupParameter<DoubleValue>("Quality", "The qualities of the VRP solutions which should be analyzed."));
82
83      Parameters.Add(new ScopeTreeLookupParameter<DoubleValue>("Overload", "The overloads of the VRP solutions which should be analyzed."));
84
85      Parameters.Add(new ValueParameter<DoubleValue>("Sigma", "The sigma applied to the penalty factor.", new DoubleValue(0.5)));
86      Parameters.Add(new ValueParameter<DoubleValue>("Phi", "The phi applied to the penalty factor.", new DoubleValue(0.5)));
87      Parameters.Add(new ValueParameter<DoubleValue>("MinPenaltyFactor", "The minimum penalty factor.", new DoubleValue(0.01)));
88      Parameters.Add(new ValueParameter<DoubleValue>("MaxPenaltyFactor", "The maximum penalty factor.", new DoubleValue(100000)));
89
90      Parameters.Add(new ValueLookupParameter<ResultCollection>("Results", "The result collection where the best VRP solution should be stored."));
91    }
92
93    public override IDeepCloneable Clone(Cloner cloner) {
94      return new CapacityRelaxationVRPAnalyzer(this, cloner);
95    }
96
97    protected CapacityRelaxationVRPAnalyzer(CapacityRelaxationVRPAnalyzer original, Cloner cloner)
98      : base(original, cloner) {
99    }
100
101    [StorableHook(HookType.AfterDeserialization)]
102    private void AfterDeserialization() {
103      // BackwardsCompatibility3.3
104      #region Backwards compatible code, remove with 3.4
105      if (!Parameters.ContainsKey("MaxPenaltyFactor")) {
106        Parameters.Add(new ValueParameter<DoubleValue>("MaxPenaltyFactor", "The maximum penalty factor.", new DoubleValue(100000)));
107      }
108      #endregion
109    }
110
111    public override IOperation Apply() {
112      ICapacitatedProblemInstance cvrp = ProblemInstanceParameter.ActualValue as ICapacitatedProblemInstance;
113      ResultCollection results = ResultsParameter.ActualValue;
114
115      ItemArray<DoubleValue> qualities = QualityParameter.ActualValue;
116      ItemArray<DoubleValue> overloads = OverloadParameter.ActualValue;
117
118      double sigma = SigmaParameter.Value.Value;
119      double phi = PhiParameter.Value.Value;
120      double minPenalty = MinPenaltyFactorParameter.Value.Value;
121      double maxPenalty = MaxPenaltyFactorParameter.Value.Value;
122
123      for (int j = 0; j < qualities.Length; j++) {
124        qualities[j].Value -= overloads[j].Value * cvrp.OverloadPenalty.Value;
125      }
126
127      int validCount = 0;
128      for (int j = 0; j < qualities.Length; j++) {
129        if (overloads[j].Value == 0)
130          validCount++;
131      }
132
133      double factor = 1.0 - ((double)validCount / (double)qualities.Length);
134
135      double min = cvrp.OverloadPenalty.Value / (1 + sigma);
136      double max = cvrp.OverloadPenalty.Value * (1 + phi);
137
138      cvrp.OverloadPenalty = new DoubleValue(min + (max - min) * factor);
139      if (cvrp.OverloadPenalty.Value < minPenalty)
140        cvrp.OverloadPenalty.Value = minPenalty;
141      if (cvrp.OverloadPenalty.Value > maxPenalty)
142        cvrp.OverloadPenalty.Value = maxPenalty;
143
144      for (int j = 0; j < qualities.Length; j++) {
145        qualities[j].Value += overloads[j].Value * cvrp.OverloadPenalty.Value;
146      }
147
148      if (!results.ContainsKey("Current Overload Penalty")) {
149        results.Add(new Result("Current Overload Penalty", new DoubleValue(cvrp.OverloadPenalty.Value)));
150      } else {
151        (results["Current Overload Penalty"].Value as DoubleValue).Value = cvrp.OverloadPenalty.Value;
152      }
153
154      return base.Apply();
155    }
156  }
157}
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