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source: branches/ALPS/HeuristicLab.Algorithms.ALPS.SteadyState/3.3/AlpsSsMover.cs @ 12220

Last change on this file since 12220 was 12220, checked in by pfleck, 8 years ago

#2350

  • Implemented elitism by sorting the layer and restricting the random target index.
  • Renamed Layers in LayersScope.
File size: 7.5 KB
Line 
1#region License Information
2/* HeuristicLab
3 * Copyright (C) 2002-2015 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.Linq;
23using HeuristicLab.Common;
24using HeuristicLab.Core;
25using HeuristicLab.Data;
26using HeuristicLab.Operators;
27using HeuristicLab.Optimization;
28using HeuristicLab.Parameters;
29using HeuristicLab.Persistence.Default.CompositeSerializers.Storable;
30using HeuristicLab.Random;
31
32namespace HeuristicLab.Algorithms.ALPS.SteadyState {
33  [Item("AlpsSsMover", "")]
34  [StorableClass]
35  public class AlpsSsMover : SingleSuccessorOperator, IStochasticOperator {
36    #region Parameter Properties
37    private ILookupParameter<IntValue> LayerParameter {
38      get { return (ILookupParameter<IntValue>)Parameters["Layer"]; }
39    }
40    private ILookupParameter<IntValue> TargetIndexParameter {
41      get { return (ILookupParameter<IntValue>)Parameters["TargetIndex"]; }
42    }
43    private ILookupParameter<IntValue> LayerSizeParameter {
44      get { return (ILookupParameter<IntValue>)Parameters["LayerSize"]; }
45    }
46    private ILookupParameter<IntValue> NumberOfLayersParameter {
47      get { return (ILookupParameter<IntValue>)Parameters["NumberOfLayers"]; }
48    }
49    private ILookupParameter<IScope> WorkingScopeParameter {
50      get { return (ILookupParameter<IScope>)Parameters["WorkingScope"]; }
51    }
52    private ILookupParameter<IScope> LayersScopeParameter {
53      get { return (ILookupParameter<IScope>)Parameters["LayersScope"]; }
54    }
55    public ILookupParameter<IRandom> RandomParameter {
56      get { return (ILookupParameter<IRandom>)Parameters["Random"]; }
57    }
58    public IScopeTreeLookupParameter<DoubleValue> QualityParameter {
59      get { return (IScopeTreeLookupParameter<DoubleValue>)Parameters["Quality"]; }
60    }
61    public ValueLookupParameter<BoolValue> MaximizationParameter {
62      get { return (ValueLookupParameter<BoolValue>)Parameters["Maximization"]; }
63    }
64    public IScopeTreeLookupParameter<IntValue> EvalsCreatedParameter {
65      get { return (IScopeTreeLookupParameter<IntValue>)Parameters["EvalsCreated"]; }
66    }
67    public IScopeTreeLookupParameter<IntValue> EvalsMovedQualityParameter {
68      get { return (IScopeTreeLookupParameter<IntValue>)Parameters["EvalsMoved"]; }
69    }
70    private ILookupParameter<IntValue> EvaluatedSolutionsParameter {
71      get { return (ILookupParameter<IntValue>)Parameters["EvaluatedSolutions"]; }
72    }
73    private ILookupParameter<IntArray> AgeLimitsParameter {
74      get { return (ILookupParameter<IntArray>)Parameters["AgeLimits"]; }
75    }
76    #endregion
77
78    [StorableConstructor]
79    private AlpsSsMover(bool deserializing)
80      : base(deserializing) { }
81    private AlpsSsMover(AlpsSsMover original, Cloner cloner)
82      : base(original, cloner) { }
83    public override IDeepCloneable Clone(Cloner cloner) {
84      return new AlpsSsMover(this, cloner);
85    }
86
87    public AlpsSsMover()
88      : base() {
89      Parameters.Add(new LookupParameter<IntValue>("Layer"));
90      Parameters.Add(new LookupParameter<IntValue>("TargetIndex"));
91      Parameters.Add(new LookupParameter<IntValue>("LayerSize"));
92      Parameters.Add(new LookupParameter<IntValue>("NumberOfLayers"));
93      Parameters.Add(new LookupParameter<IScope>("WorkingScope"));
94      Parameters.Add(new LookupParameter<IScope>("LayersScope"));
95      Parameters.Add(new LookupParameter<IRandom>("Random", "The random number generator to use."));
96      Parameters.Add(new ScopeTreeLookupParameter<DoubleValue>("Quality"));
97      Parameters.Add(new ValueLookupParameter<BoolValue>("Maximization", "True if the problem is a maximization problem, otherwise false."));
98      Parameters.Add(new ScopeTreeLookupParameter<IntValue>("EvalsCreated"));
99      Parameters.Add(new ScopeTreeLookupParameter<IntValue>("EvalsMoved"));
100      Parameters.Add(new LookupParameter<IntValue>("EvaluatedSolutions"));
101      Parameters.Add(new LookupParameter<IntArray>("AgeLimits"));
102    }
103
104    private int n;
105    private int m;
106    private int evals;
107    private int popSize;
108    private IScope layers;
109    private IRandom rand;
110    private string qualityVariableName;
111    private IntArray ageLimits;
112    private bool maximization;
113    public override IOperation Apply() {
114      int i = LayerParameter.ActualValue.Value;
115      int j = TargetIndexParameter.ActualValue.Value;
116      n = NumberOfLayersParameter.ActualValue.Value;
117      m = LayerSizeParameter.ActualValue.Value;
118      evals = EvaluatedSolutionsParameter.ActualValue.Value;
119      popSize = n * m;
120      rand = RandomParameter.ActualValue;
121      qualityVariableName = QualityParameter.TranslatedName;
122      ageLimits = AgeLimitsParameter.ActualValue;
123      maximization = MaximizationParameter.ActualValue.Value;
124
125      layers = LayersScopeParameter.ActualValue;
126      var newIndividual = (IScope)WorkingScopeParameter.ActualValue.Clone();
127      newIndividual.Name = j.ToString();
128
129      TryMoveUp(i, j);
130      var currentLayer = layers.SubScopes[i];
131      currentLayer.SubScopes[j] = newIndividual;
132
133      return base.Apply();
134    }
135    private void TryMoveUp(int i, int j) {
136      var currentLayer = layers.SubScopes[i];
137      var currentIndividual = currentLayer.SubScopes[j];
138      if (i < n - 1) {
139        var nextLayer = layers.SubScopes[i + 1];
140        int? k = FindReplaceable(nextLayer, currentIndividual);
141
142        if (k.HasValue) {
143          TryMoveUp(i + 1, k.Value);
144          nextLayer.SubScopes[k.Value] = currentIndividual;
145        }
146      }
147    }
148    private int? FindReplaceable(IScope layer, IScope individualToReplace) {
149      int layerNumber = ((IntValue)layer.Variables["Layer"].Value).Value;
150
151      var individuals = (
152        from individual in layer.SubScopes
153        let quality = ((DoubleValue)individual.Variables[qualityVariableName].Value).Value
154        let evalsCreated = ((IntValue)individual.Variables["EvalsCreated"].Value).Value
155        let age = (evals - evalsCreated) / popSize
156        select new { individual, quality, age }
157        ).Select((x, index) => new { index, x.individual, x.quality, x.age })
158        .ToList();
159
160      var ageLimit = layerNumber < n - 1 ? ageLimits[layerNumber] : int.MaxValue;
161
162      var toOldIndividual = individuals.FirstOrDefault(x => x.age >= ageLimit);
163      if (toOldIndividual != null)
164        return toOldIndividual.index;
165
166      double replaceQuality = ((DoubleValue)individualToReplace.Variables[qualityVariableName].Value).Value;
167      var sortedIndividuals = maximization ? individuals.OrderBy(x => x.quality) : individuals.OrderByDescending(x => x.quality);
168      var worstIndividual = sortedIndividuals.FirstOrDefault(x => maximization ? x.quality < replaceQuality : x.quality > replaceQuality);
169      if (worstIndividual != null)
170        return worstIndividual.index;
171
172      return Enumerable.Range(0, layer.SubScopes.Count).SampleRandom(rand);
173    }
174  }
175}
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