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source: trunk/sources/HeuristicLab.Selection/3.3/ProportionalSelector.cs @ 2830

Last change on this file since 2830 was 2830, checked in by swagner, 14 years ago

Operator architecture refactoring (#95)

  • worked on operators and SGA
  • improved performance
File size: 4.0 KB
Line 
1#region License Information
2/* HeuristicLab
3 * Copyright (C) 2002-2010 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.Core;
26using HeuristicLab.Data;
27using HeuristicLab.Parameters;
28using HeuristicLab.Persistence.Default.CompositeSerializers.Storable;
29
30namespace HeuristicLab.Selection {
31  /// <summary>
32  /// A quality proportional selection operator which considers a single double quality value for selection.
33  /// </summary>
34  [Item("ProportionalSelector", "A quality proportional selection operator which considers a single double quality value for selection.")]
35  [EmptyStorableClass]
36  [Creatable("Test")]
37  public sealed class ProportionalSelector : StochasticSingleObjectiveSelector {
38    private ValueParameter<BoolData> WindowingParameter {
39      get { return (ValueParameter<BoolData>)Parameters["Windowing"]; }
40    }
41
42    public BoolData Windowing {
43      get { return WindowingParameter.Value; }
44      set { WindowingParameter.Value = value; }
45    }
46
47    public ProportionalSelector()
48      : base() {
49      Parameters.Add(new ValueParameter<BoolData>("Windowing", "Apply windowing strategy (selection probability is proportional to the quality differences and not to the total quality).", new BoolData(true)));
50      CopySelected.Value = true;
51    }
52
53    protected override IScope[] Select(List<IScope> scopes) {
54      int count = NumberOfSelectedSubScopesParameter.ActualValue.Value;
55      bool copy = CopySelectedParameter.Value.Value;
56      IRandom random = RandomParameter.ActualValue;
57      bool maximization = MaximizationParameter.ActualValue.Value;
58      bool windowing = WindowingParameter.Value.Value;
59      IScope[] selected = new IScope[count];
60
61      // prepare qualities for proportional selection
62      var qualities = QualityParameter.ActualValue.Select(x => x.Value);
63      double minQuality = qualities.Min();
64      double maxQuality = qualities.Max();
65      if (minQuality == maxQuality) {  // all quality values are equal
66        qualities = qualities.Select(x => 1.0);
67      } else {
68        if (windowing) {
69          if (maximization)
70            qualities = qualities.Select(x => x - minQuality);
71          else
72            qualities = qualities.Select(x => maxQuality - x);
73        } else {
74          if (minQuality < 0.0) throw new InvalidOperationException("Proportional selection without windowing does not work with quality values < 0.");
75          if (!maximization) {
76            double limit = Math.Min(maxQuality * 2, double.MaxValue);
77            qualities = qualities.Select(x => limit - x);
78          }
79        }
80      }
81
82      List<double> list = qualities.ToList();
83      double qualitySum = qualities.Sum();
84      for (int i = 0; i < count; i++) {
85        double selectedQuality = random.NextDouble() * qualitySum;
86        int index = 0;
87        double currentQuality = list[index];
88        while (currentQuality < selectedQuality) {
89          index++;
90          currentQuality += list[index];
91        }
92        if (copy)
93          selected[i] = (IScope)scopes[index].Clone();
94        else {
95          selected[i] = scopes[index];
96          scopes.RemoveAt(index);
97          qualitySum -= list[index];
98          list.RemoveAt(index);
99        }
100      }
101      return selected;
102    }
103  }
104}
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