Free cookie consent management tool by TermsFeed Policy Generator

source: branches/VOSGA/HeuristicLab.Algorithms.VOffspringSelectionGeneticAlgorithm/Comparators/PopulationDiversityComparator.cs @ 12064

Last change on this file since 12064 was 11845, checked in by ascheibe, 10 years ago

#2267 added another comparator
File size: 13.1 KB
Line 
1#region License Information
2/* HeuristicLab
3 * Copyright (C) 2002-2014 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.Linq;
24using HeuristicLab.Analysis;
25using HeuristicLab.Common;
26using HeuristicLab.Core;
27using HeuristicLab.Data;
28using HeuristicLab.Operators;
29using HeuristicLab.Optimization;
30using HeuristicLab.Optimization.Operators;
31using HeuristicLab.Parameters;
32using HeuristicLab.Persistence.Default.CompositeSerializers.Storable;
33using HeuristicLab.PluginInfrastructure;
34
35namespace HeuristicLab.Algorithms.VOffspringSelectionGeneticAlgorithm {
36  [Item("PopulationDiversityComparator", "Structural comparison of child to population.")]
37  [StorableClass]
38  public class PopulationDiversityComparator : SingleSuccessorOperator, ISubScopesQualityComparatorOperator, ISimilarityBasedOperator {
39    [Storable]
40    public ISolutionSimilarityCalculator SimilarityCalculator { get; set; }
41    public IValueLookupParameter<BoolValue> MaximizationParameter {
42      get { return (IValueLookupParameter<BoolValue>)Parameters["Maximization"]; }
43    }
44    public ILookupParameter<DoubleValue> LeftSideParameter {
45      get { return (ILookupParameter<DoubleValue>)Parameters["LeftSide"]; }
46    }
47    public ILookupParameter<ItemArray<DoubleValue>> RightSideParameter {
48      get { return (ILookupParameter<ItemArray<DoubleValue>>)Parameters["RightSide"]; }
49    }
50    public ILookupParameter<BoolValue> ResultParameter {
51      get { return (ILookupParameter<BoolValue>)Parameters["Result"]; }
52    }
53    public ValueLookupParameter<DoubleValue> ComparisonFactorParameter {
54      get { return (ValueLookupParameter<DoubleValue>)Parameters["ComparisonFactor"]; }
55    }
56    public ValueLookupParameter<DoubleValue> DiversityComparisonFactorParameter {
57      get { return (ValueLookupParameter<DoubleValue>)Parameters["DiversityComparisonFactor"]; }
58    }
59    private ValueLookupParameter<DoubleValue> ComparisonFactorLowerBoundParameter {
60      get { return (ValueLookupParameter<DoubleValue>)Parameters["DiversityComparisonFactorLowerBound"]; }
61    }
62    private ValueLookupParameter<DoubleValue> ComparisonFactorUpperBoundParameter {
63      get { return (ValueLookupParameter<DoubleValue>)Parameters["DiversityComparisonFactorUpperBound"]; }
64    }
65    public IConstrainedValueParameter<IDiscreteDoubleValueModifier> ComparisonFactorModifierParameter {
66      get { return (IConstrainedValueParameter<IDiscreteDoubleValueModifier>)Parameters["ComparisonFactorModifier"]; }
67    }
68    public ValueLookupParameter<ResultCollection> ResultsParameter {
69      get { return (ValueLookupParameter<ResultCollection>)Parameters["Results"]; }
70    }
71    public ILookupParameter<IntValue> GenerationsParameter {
72      get { return (LookupParameter<IntValue>)Parameters["Generations"]; }
73    }
74    public ValueParameter<BoolValue> EnableDivCriteriaParameter {
75      get { return (ValueParameter<BoolValue>)Parameters["EnableDivCriteria"]; }
76    }
77
78    private const string spDetailsParameterName = "SPDetails";
79    private const string divDataRowName = "DiversitySuccessCount";
80    private const string qualityDataRowName = "QualitySuccessCount";
81    private const string divFailDataRowName = "DiversityFailCount";
82    private const string qualityFailDataRowName = "QualityFailCount";
83    private const string overallCountDataRowName = "OverallCount";
84    private const string successCountDataRowName = "SuccessCount";
85
86    [Storable]
87    private int currentGeneration;
88    [Storable]
89    private int divCount;
90    [Storable]
91    private int qualityCount;
92    [Storable]
93    private int badQualityCount;
94    [Storable]
95    private int badDivCount;
96    [Storable]
97    private int overallCount;
98    [Storable]
99    private int successCount;
100
101    [StorableConstructor]
102    protected PopulationDiversityComparator(bool deserializing) : base(deserializing) { }
103    protected PopulationDiversityComparator(PopulationDiversityComparator original, Cloner cloner)
104      : base(original, cloner) {
105      SimilarityCalculator = cloner.Clone(original.SimilarityCalculator);
106      currentGeneration = original.currentGeneration;
107      divCount = original.divCount;
108      qualityCount = original.qualityCount;
109      overallCount = original.overallCount;
110      successCount = original.successCount;
111      badDivCount = original.badDivCount;
112      badQualityCount = original.badQualityCount;
113    }
114    public PopulationDiversityComparator()
115      : base() {
116      Parameters.Add(new ValueLookupParameter<BoolValue>("Maximization", "True if the problem is a maximization problem, false otherwise"));
117      Parameters.Add(new LookupParameter<DoubleValue>("LeftSide", "The quality of the child."));
118      Parameters.Add(new ScopeTreeLookupParameter<DoubleValue>("RightSide", "The qualities of the parents."));
119      Parameters.Add(new LookupParameter<BoolValue>("Result", "The result of the comparison: True means Quality is better, False means it is worse than parents."));
120      Parameters.Add(new ValueLookupParameter<DoubleValue>("ComparisonFactor", "Determines if the quality should be compared to the better parent (1.0), to the worse (0.0) or to any linearly interpolated value between them."));
121      Parameters.Add(new ValueLookupParameter<DoubleValue>("DiversityComparisonFactor", "Determines if the quality should be compared to the better parent (1.0), to the worse (0.0) or to any linearly interpolated value between them.", new DoubleValue(0.0)));
122      Parameters.Add(new ValueLookupParameter<DoubleValue>("DiversityComparisonFactorLowerBound", "The lower bound of the comparison factor (start).", new DoubleValue(0.5)));
123      Parameters.Add(new ValueLookupParameter<DoubleValue>("DiversityComparisonFactorUpperBound", "The upper bound of the comparison factor (end).", new DoubleValue(1.0)));
124      Parameters.Add(new OptionalConstrainedValueParameter<IDiscreteDoubleValueModifier>("ComparisonFactorModifier", "The operator used to modify the comparison factor.", new ItemSet<IDiscreteDoubleValueModifier>(new IDiscreteDoubleValueModifier[] { new LinearDiscreteDoubleValueModifier() }), new LinearDiscreteDoubleValueModifier()));
125      Parameters.Add(new ValueLookupParameter<ResultCollection>("Results", "The result collection where the population diversity analysis results should be stored."));
126      Parameters.Add(new LookupParameter<IntValue>("Generations", "The current number of generations."));
127      Parameters.Add(new ValueParameter<BoolValue>("EnableDivCriteria", "Use diversity as additional offspring selection criteria.", new BoolValue(true)));
128
129      foreach (IDiscreteDoubleValueModifier modifier in ApplicationManager.Manager.GetInstances<IDiscreteDoubleValueModifier>().OrderBy(x => x.Name))
130        ComparisonFactorModifierParameter.ValidValues.Add(modifier);
131      IDiscreteDoubleValueModifier linearModifier = ComparisonFactorModifierParameter.ValidValues.FirstOrDefault(x => x.GetType().Name.Equals("LinearDiscreteDoubleValueModifier"));
132      if (linearModifier != null) ComparisonFactorModifierParameter.Value = linearModifier;
133      ParameterizeComparisonFactorModifiers();
134    }
135
136    public override IDeepCloneable Clone(Cloner cloner) {
137      return new PopulationDiversityComparator(this, cloner);
138    }
139
140    private void ParameterizeComparisonFactorModifiers() {
141      //TODO: does not work if Generations parameter names are changed
142      foreach (IDiscreteDoubleValueModifier modifier in ComparisonFactorModifierParameter.ValidValues) {
143        modifier.IndexParameter.ActualName = "Generations";
144        modifier.EndIndexParameter.ActualName = "MaximumGenerations";
145        modifier.EndValueParameter.ActualName = ComparisonFactorUpperBoundParameter.Name;
146        modifier.StartIndexParameter.Value = new IntValue(0);
147        modifier.StartValueParameter.ActualName = ComparisonFactorLowerBoundParameter.Name;
148        modifier.ValueParameter.ActualName = "DiversityComparisonFactor";
149      }
150    }
151
152    private IScope GetRemainingScope() {
153      var scope = ExecutionContext.Scope;
154
155      while (scope != null) {
156        if (scope.SubScopes.Any(x => x.Name == "Remaining")) {
157          return scope.SubScopes.Single(x => x.Name == "Remaining");
158        }
159        scope = scope.Parent;
160      }
161      return null;
162    }
163
164    public override IOperation Apply() {
165      ItemArray<DoubleValue> rightQualities = RightSideParameter.ActualValue;
166      if (rightQualities.Length < 1) throw new InvalidOperationException(Name + ": No subscopes found.");
167      double compFact = ComparisonFactorParameter.ActualValue.Value;
168      double diversityComFact = DiversityComparisonFactorParameter.ActualValue.Value;
169      bool maximization = MaximizationParameter.ActualValue.Value;
170      double leftQuality = LeftSideParameter.ActualValue.Value;
171      bool resultDiversity;
172      double threshold = 0;
173
174      DataTable spDetailsTable;
175      if (ResultsParameter.ActualValue.ContainsKey(spDetailsParameterName)) {
176        spDetailsTable = (DataTable)ResultsParameter.ActualValue[spDetailsParameterName].Value;
177      } else {
178        spDetailsTable = new DataTable(spDetailsParameterName);
179        spDetailsTable.Rows.Add(new DataRow(divDataRowName));
180        spDetailsTable.Rows.Add(new DataRow(qualityDataRowName));
181        spDetailsTable.Rows.Add(new DataRow(overallCountDataRowName));
182        spDetailsTable.Rows.Add(new DataRow(successCountDataRowName));
183        spDetailsTable.Rows.Add(new DataRow(divFailDataRowName));
184        spDetailsTable.Rows.Add(new DataRow(qualityFailDataRowName));
185        ResultsParameter.ActualValue.Add(new Result(spDetailsParameterName, spDetailsTable));
186      }
187
188      if (GenerationsParameter.ActualValue.Value != currentGeneration) {
189        spDetailsTable.Rows[divDataRowName].Values.Add(divCount);
190        divCount = 0;
191        spDetailsTable.Rows[qualityDataRowName].Values.Add(qualityCount);
192        qualityCount = 0;
193        spDetailsTable.Rows[overallCountDataRowName].Values.Add(overallCount);
194        overallCount = 0;
195        spDetailsTable.Rows[successCountDataRowName].Values.Add(successCount);
196        successCount = 0;
197        spDetailsTable.Rows[qualityFailDataRowName].Values.Add(badQualityCount);
198        badQualityCount = 0;
199        spDetailsTable.Rows[divFailDataRowName].Values.Add(badDivCount);
200        badDivCount = 0;
201        currentGeneration = GenerationsParameter.ActualValue.Value;
202      }
203
204      #region Calculate threshold
205      if (rightQualities.Length == 2) {
206        var remainingScope = GetRemainingScope();
207        Scope fakeScope = new Scope();
208        fakeScope.SubScopes.Add((IScope)ExecutionContext.Scope.Clone());
209        var similarities = SimilarityCalculator.CalculateSolutionCrowdSimilarity(fakeScope, remainingScope);
210        double averageSimilarity = similarities[0].Average();
211        resultDiversity = averageSimilarity < diversityComFact;
212
213        double minQuality = Math.Min(rightQualities[0].Value, rightQualities[1].Value);
214        double maxQuality = Math.Max(rightQualities[0].Value, rightQualities[1].Value);
215        if (maximization)
216          threshold = minQuality + (maxQuality - minQuality) * compFact;
217        else
218          threshold = maxQuality - (maxQuality - minQuality) * compFact;
219      } else {
220        throw new NotImplementedException("Only 2 parents are supported.");
221      }
222      #endregion
223
224      bool result = maximization && leftQuality > threshold || !maximization && leftQuality < threshold;
225
226      //collect statistics
227      if (result) {
228        qualityCount++;
229      } else {
230        badQualityCount++;
231      }
232      if (resultDiversity) {
233        divCount++;
234      } else {
235        badDivCount++;
236      }
237      if (result && resultDiversity) {
238        successCount++;
239      }
240      overallCount++;
241
242      //use diveristiy criteria or not
243      if (EnableDivCriteriaParameter.Value.Value) {
244        result = result && resultDiversity;
245      }
246
247      BoolValue resultValue = ResultParameter.ActualValue;
248      if (resultValue == null) {
249        ResultParameter.ActualValue = new BoolValue(result);
250      } else {
251        resultValue.Value = result;
252      }
253
254      //like the placeholder, though we create child operations
255      OperationCollection next = new OperationCollection(base.Apply());
256      IOperator op = ComparisonFactorModifierParameter.Value;
257      if (op != null)
258        next.Insert(0, ExecutionContext.CreateChildOperation(op));
259      return next;
260    }
261  }
262}
Note: See TracBrowser for help on using the repository browser.