[2] | 1 | #region License Information
|
---|
| 2 | /* HeuristicLab
|
---|
[9456] | 3 | * Copyright (C) 2002-2013 Heuristic and Evolutionary Algorithms Laboratory (HEAL)
|
---|
[2] | 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 |
|
---|
[7995] | 22 | using System;
|
---|
[2] | 23 | using System.Collections.Generic;
|
---|
[2818] | 24 | using System.Linq;
|
---|
[4722] | 25 | using HeuristicLab.Common;
|
---|
[2] | 26 | using HeuristicLab.Core;
|
---|
| 27 | using HeuristicLab.Data;
|
---|
[3138] | 28 | using HeuristicLab.Optimization;
|
---|
[2805] | 29 | using HeuristicLab.Parameters;
|
---|
| 30 | using HeuristicLab.Persistence.Default.CompositeSerializers.Storable;
|
---|
[2] | 31 |
|
---|
| 32 | namespace HeuristicLab.Selection {
|
---|
[817] | 33 | /// <summary>
|
---|
[2805] | 34 | /// A tournament selection operator which considers a single double quality value for selection.
|
---|
[817] | 35 | /// </summary>
|
---|
[2805] | 36 | [Item("TournamentSelector", "A tournament selection operator which considers a single double quality value for selection.")]
|
---|
[3017] | 37 | [StorableClass]
|
---|
[3138] | 38 | public sealed class TournamentSelector : StochasticSingleObjectiveSelector, ISingleObjectiveSelector {
|
---|
[3048] | 39 | public ValueLookupParameter<IntValue> GroupSizeParameter {
|
---|
| 40 | get { return (ValueLookupParameter<IntValue>)Parameters["GroupSize"]; }
|
---|
[2] | 41 | }
|
---|
| 42 |
|
---|
[4722] | 43 | [StorableConstructor]
|
---|
| 44 | private TournamentSelector(bool deserializing) : base(deserializing) { }
|
---|
| 45 | private TournamentSelector(TournamentSelector original, Cloner cloner) : base(original, cloner) { }
|
---|
| 46 | public override IDeepCloneable Clone(Cloner cloner) {
|
---|
| 47 | return new TournamentSelector(this, cloner);
|
---|
| 48 | }
|
---|
| 49 |
|
---|
[4068] | 50 | public TournamentSelector()
|
---|
| 51 | : base() {
|
---|
[3048] | 52 | Parameters.Add(new ValueLookupParameter<IntValue>("GroupSize", "The size of the tournament group.", new IntValue(2)));
|
---|
[2] | 53 | }
|
---|
| 54 |
|
---|
[2830] | 55 | protected override IScope[] Select(List<IScope> scopes) {
|
---|
[2805] | 56 | int count = NumberOfSelectedSubScopesParameter.ActualValue.Value;
|
---|
| 57 | bool copy = CopySelectedParameter.Value.Value;
|
---|
| 58 | IRandom random = RandomParameter.ActualValue;
|
---|
| 59 | bool maximization = MaximizationParameter.ActualValue.Value;
|
---|
[7995] | 60 | List<double> qualities = QualityParameter.ActualValue.Where(x => IsValidQuality(x.Value)).Select(x => x.Value).ToList();
|
---|
[2805] | 61 | int groupSize = GroupSizeParameter.ActualValue.Value;
|
---|
[2830] | 62 | IScope[] selected = new IScope[count];
|
---|
[2] | 63 |
|
---|
[7995] | 64 | //check if list with indexes is as long as the original scope list
|
---|
| 65 | //otherwise invalid quality values were filtered
|
---|
| 66 | if (qualities.Count != scopes.Count) {
|
---|
| 67 | throw new ArgumentException("The scopes contain invalid quality values (either infinity or double.NaN) on which the selector cannot operate.");
|
---|
| 68 | }
|
---|
| 69 |
|
---|
[2805] | 70 | for (int i = 0; i < count; i++) {
|
---|
[2817] | 71 | int best = random.Next(scopes.Count);
|
---|
[2805] | 72 | int index;
|
---|
[1063] | 73 | for (int j = 1; j < groupSize; j++) {
|
---|
[2817] | 74 | index = random.Next(scopes.Count);
|
---|
[2818] | 75 | if (((maximization) && (qualities[index] > qualities[best])) ||
|
---|
| 76 | ((!maximization) && (qualities[index] < qualities[best]))) {
|
---|
[2805] | 77 | best = index;
|
---|
[2] | 78 | }
|
---|
| 79 | }
|
---|
| 80 |
|
---|
[9943] | 81 | if (copy) {
|
---|
[2830] | 82 | selected[i] = (IScope)scopes[best].Clone();
|
---|
[9943] | 83 | var original = scopes[best].Variables.First().Value;
|
---|
| 84 | var clone = selected[i].Variables.First().Value;
|
---|
| 85 | GlobalCloneMap.Add(clone, original);
|
---|
| 86 | } else {
|
---|
[2830] | 87 | selected[i] = scopes[best];
|
---|
[2817] | 88 | scopes.RemoveAt(best);
|
---|
[2805] | 89 | qualities.RemoveAt(best);
|
---|
[2] | 90 | }
|
---|
| 91 | }
|
---|
[2817] | 92 | return selected;
|
---|
[2] | 93 | }
|
---|
| 94 | }
|
---|
| 95 | }
|
---|