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source: branches/VNS/HeuristicLab.Selection/3.3/ProportionalSelector.cs @ 5595

Last change on this file since 5595 was 5445, checked in by swagner, 14 years ago

Updated year of copyrights (#1406)

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1#region License Information
2/* HeuristicLab
3 * Copyright (C) 2002-2011 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 System;
23using System.Collections.Generic;
24using System.Linq;
25using HeuristicLab.Common;
26using HeuristicLab.Core;
27using HeuristicLab.Data;
28using HeuristicLab.Optimization;
29using HeuristicLab.Parameters;
30using HeuristicLab.Persistence.Default.CompositeSerializers.Storable;
31
32namespace HeuristicLab.Selection {
33  /// <summary>
34  /// A quality proportional selection operator which considers a single double quality value for selection.
35  /// </summary>
36  [Item("ProportionalSelector", "A quality proportional selection operator which considers a single double quality value for selection.")]
37  [StorableClass]
38  public sealed class ProportionalSelector : StochasticSingleObjectiveSelector, ISingleObjectiveSelector {
39    private ValueParameter<BoolValue> WindowingParameter {
40      get { return (ValueParameter<BoolValue>)Parameters["Windowing"]; }
41    }
42
43    public BoolValue Windowing {
44      get { return WindowingParameter.Value; }
45      set { WindowingParameter.Value = value; }
46    }
47
48    [StorableConstructor]
49    private ProportionalSelector(bool deserializing) : base(deserializing) { }
50    private ProportionalSelector(ProportionalSelector original, Cloner cloner)
51      : base(original, cloner) {
52    }
53    public override IDeepCloneable Clone(Cloner cloner) {
54      return new ProportionalSelector(this, cloner);
55    }
56    public ProportionalSelector()
57      : base() {
58      Parameters.Add(new ValueParameter<BoolValue>("Windowing", "Apply windowing strategy (selection probability is proportional to the quality differences and not to the total quality).", new BoolValue(true)));
59    }
60
61    protected override IScope[] Select(List<IScope> scopes) {
62      int count = NumberOfSelectedSubScopesParameter.ActualValue.Value;
63      bool copy = CopySelectedParameter.Value.Value;
64      IRandom random = RandomParameter.ActualValue;
65      bool maximization = MaximizationParameter.ActualValue.Value;
66      bool windowing = WindowingParameter.Value.Value;
67      IScope[] selected = new IScope[count];
68
69      // prepare qualities for proportional selection
70      var qualities = QualityParameter.ActualValue.Select(x => x.Value);
71      double minQuality = qualities.Min();
72      double maxQuality = qualities.Max();
73      if (minQuality == maxQuality) {  // all quality values are equal
74        qualities = qualities.Select(x => 1.0);
75      } else {
76        if (windowing) {
77          if (maximization)
78            qualities = qualities.Select(x => x - minQuality);
79          else
80            qualities = qualities.Select(x => maxQuality - x);
81        } else {
82          if (minQuality < 0.0) throw new InvalidOperationException("Proportional selection without windowing does not work with quality values < 0.");
83          if (!maximization) {
84            double limit = Math.Min(maxQuality * 2, double.MaxValue);
85            qualities = qualities.Select(x => limit - x);
86          }
87        }
88      }
89
90      List<double> list = qualities.ToList();
91      double qualitySum = qualities.Sum();
92      for (int i = 0; i < count; i++) {
93        double selectedQuality = random.NextDouble() * qualitySum;
94        int index = 0;
95        double currentQuality = list[index];
96        while (currentQuality < selectedQuality) {
97          index++;
98          currentQuality += list[index];
99        }
100        if (copy)
101          selected[i] = (IScope)scopes[index].Clone();
102        else {
103          selected[i] = scopes[index];
104          scopes.RemoveAt(index);
105          qualitySum -= list[index];
106          list.RemoveAt(index);
107        }
108      }
109      return selected;
110    }
111  }
112}
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