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 |
|
---|
22 | using System;
|
---|
23 | using System.Collections.Generic;
|
---|
24 | using System.Linq;
|
---|
25 | using HeuristicLab.Core;
|
---|
26 | using HeuristicLab.Data;
|
---|
27 | using HeuristicLab.Parameters;
|
---|
28 | using HeuristicLab.Persistence.Default.CompositeSerializers.Storable;
|
---|
29 |
|
---|
30 | namespace 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 | [StorableClass]
|
---|
36 | [Creatable("Test")]
|
---|
37 | public sealed class ProportionalSelector : StochasticSingleObjectiveSelector {
|
---|
38 | private ValueParameter<BoolValue> WindowingParameter {
|
---|
39 | get { return (ValueParameter<BoolValue>)Parameters["Windowing"]; }
|
---|
40 | }
|
---|
41 |
|
---|
42 | public BoolValue Windowing {
|
---|
43 | get { return WindowingParameter.Value; }
|
---|
44 | set { WindowingParameter.Value = value; }
|
---|
45 | }
|
---|
46 |
|
---|
47 | public ProportionalSelector()
|
---|
48 | : base() {
|
---|
49 | 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)));
|
---|
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 | }
|
---|