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source: trunk/sources/HeuristicLab.Algorithms.OffspringSelectionGeneticAlgorithm/3.3/OffspringSelectionGeneticAlgorithm.cs @ 3721

Last change on this file since 3721 was 3689, checked in by abeham, 15 years ago

#893

  • fixed wiring in the algorithms
File size: 21.9 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.Analysis;
26using HeuristicLab.Core;
27using HeuristicLab.Data;
28using HeuristicLab.Optimization;
29using HeuristicLab.Optimization.Operators;
30using HeuristicLab.Parameters;
31using HeuristicLab.Persistence.Default.CompositeSerializers.Storable;
32using HeuristicLab.PluginInfrastructure;
33using HeuristicLab.Random;
34using HeuristicLab.Common;
35
36namespace HeuristicLab.Algorithms.OffspringSelectionGeneticAlgorithm {
37  /// <summary>
38  /// An offspring selection genetic algorithm.
39  /// </summary>
40  [Item("Offspring Selection Genetic Algorithm", "An offspring selection genetic algorithm (Affenzeller, M. et al. 2009. Genetic Algorithms and Genetic Programming - Modern Concepts and Practical Applications. CRC Press).")]
41  [Creatable("Algorithms")]
42  [StorableClass]
43  public sealed class OffspringSelectionGeneticAlgorithm : EngineAlgorithm {
44    #region Problem Properties
45    public override Type ProblemType {
46      get { return typeof(ISingleObjectiveProblem); }
47    }
48    public new ISingleObjectiveProblem Problem {
49      get { return (ISingleObjectiveProblem)base.Problem; }
50      set { base.Problem = value; }
51    }
52    #endregion
53
54    #region Parameter Properties
55    private ValueParameter<IntValue> SeedParameter {
56      get { return (ValueParameter<IntValue>)Parameters["Seed"]; }
57    }
58    private ValueParameter<BoolValue> SetSeedRandomlyParameter {
59      get { return (ValueParameter<BoolValue>)Parameters["SetSeedRandomly"]; }
60    }
61    private ValueParameter<IntValue> PopulationSizeParameter {
62      get { return (ValueParameter<IntValue>)Parameters["PopulationSize"]; }
63    }
64    private ConstrainedValueParameter<ISelector> SelectorParameter {
65      get { return (ConstrainedValueParameter<ISelector>)Parameters["Selector"]; }
66    }
67    private ConstrainedValueParameter<ICrossover> CrossoverParameter {
68      get { return (ConstrainedValueParameter<ICrossover>)Parameters["Crossover"]; }
69    }
70    private ValueParameter<PercentValue> MutationProbabilityParameter {
71      get { return (ValueParameter<PercentValue>)Parameters["MutationProbability"]; }
72    }
73    private OptionalConstrainedValueParameter<IManipulator> MutatorParameter {
74      get { return (OptionalConstrainedValueParameter<IManipulator>)Parameters["Mutator"]; }
75    }
76    private ValueParameter<IntValue> ElitesParameter {
77      get { return (ValueParameter<IntValue>)Parameters["Elites"]; }
78    }
79    private ValueParameter<IntValue> MaximumGenerationsParameter {
80      get { return (ValueParameter<IntValue>)Parameters["MaximumGenerations"]; }
81    }
82    private ValueLookupParameter<DoubleValue> SuccessRatioParameter {
83      get { return (ValueLookupParameter<DoubleValue>)Parameters["SuccessRatio"]; }
84    }
85    private ValueLookupParameter<DoubleValue> ComparisonFactorLowerBoundParameter {
86      get { return (ValueLookupParameter<DoubleValue>)Parameters["ComparisonFactorLowerBound"]; }
87    }
88    private ValueLookupParameter<DoubleValue> ComparisonFactorUpperBoundParameter {
89      get { return (ValueLookupParameter<DoubleValue>)Parameters["ComparisonFactorUpperBound"]; }
90    }
91    private OptionalConstrainedValueParameter<IDiscreteDoubleValueModifier> ComparisonFactorModifierParameter {
92      get { return (OptionalConstrainedValueParameter<IDiscreteDoubleValueModifier>)Parameters["ComparisonFactorModifier"]; }
93    }
94    private ValueLookupParameter<DoubleValue> MaximumSelectionPressureParameter {
95      get { return (ValueLookupParameter<DoubleValue>)Parameters["MaximumSelectionPressure"]; }
96    }
97    private ValueLookupParameter<BoolValue> OffspringSelectionBeforeMutationParameter {
98      get { return (ValueLookupParameter<BoolValue>)Parameters["OffspringSelectionBeforeMutation"]; }
99    }
100    private ValueLookupParameter<IntValue> SelectedParentsParameter {
101      get { return (ValueLookupParameter<IntValue>)Parameters["SelectedParents"]; }
102    }
103    private ValueParameter<MultiAnalyzer> AnalyzerParameter {
104      get { return (ValueParameter<MultiAnalyzer>)Parameters["Analyzer"]; }
105    }
106    #endregion
107
108    #region Properties
109    public IntValue Seed {
110      get { return SeedParameter.Value; }
111      set { SeedParameter.Value = value; }
112    }
113    public BoolValue SetSeedRandomly {
114      get { return SetSeedRandomlyParameter.Value; }
115      set { SetSeedRandomlyParameter.Value = value; }
116    }
117    public IntValue PopulationSize {
118      get { return PopulationSizeParameter.Value; }
119      set { PopulationSizeParameter.Value = value; }
120    }
121    public ISelector Selector {
122      get { return SelectorParameter.Value; }
123      set { SelectorParameter.Value = value; }
124    }
125    public ICrossover Crossover {
126      get { return CrossoverParameter.Value; }
127      set { CrossoverParameter.Value = value; }
128    }
129    public PercentValue MutationProbability {
130      get { return MutationProbabilityParameter.Value; }
131      set { MutationProbabilityParameter.Value = value; }
132    }
133    public IManipulator Mutator {
134      get { return MutatorParameter.Value; }
135      set { MutatorParameter.Value = value; }
136    }
137    public IntValue Elites {
138      get { return ElitesParameter.Value; }
139      set { ElitesParameter.Value = value; }
140    }
141    public IntValue MaximumGenerations {
142      get { return MaximumGenerationsParameter.Value; }
143      set { MaximumGenerationsParameter.Value = value; }
144    }
145    public DoubleValue SuccessRatio {
146      get { return SuccessRatioParameter.Value; }
147      set { SuccessRatioParameter.Value = value; }
148    }
149    public DoubleValue ComparisonFactorLowerBound {
150      get { return ComparisonFactorLowerBoundParameter.Value; }
151      set { ComparisonFactorLowerBoundParameter.Value = value; }
152    }
153    public DoubleValue ComparisonFactorUpperBound {
154      get { return ComparisonFactorUpperBoundParameter.Value; }
155      set { ComparisonFactorUpperBoundParameter.Value = value; }
156    }
157    public IDiscreteDoubleValueModifier ComparisonFactorModifier {
158      get { return ComparisonFactorModifierParameter.Value; }
159      set { ComparisonFactorModifierParameter.Value = value; }
160    }
161    public DoubleValue MaximumSelectionPressure {
162      get { return MaximumSelectionPressureParameter.Value; }
163      set { MaximumSelectionPressureParameter.Value = value; }
164    }
165    public BoolValue OffspringSelectionBeforeMutation {
166      get { return OffspringSelectionBeforeMutationParameter.Value; }
167      set { OffspringSelectionBeforeMutationParameter.Value = value; }
168    }
169    public IntValue SelectedParents {
170      get { return SelectedParentsParameter.Value; }
171      set { SelectedParentsParameter.Value = value; }
172    }
173    public MultiAnalyzer Analyzer {
174      get { return AnalyzerParameter.Value; }
175      set { AnalyzerParameter.Value = value; }
176    }
177    private RandomCreator RandomCreator {
178      get { return (RandomCreator)OperatorGraph.InitialOperator; }
179    }
180    private SolutionsCreator SolutionsCreator {
181      get { return (SolutionsCreator)RandomCreator.Successor; }
182    }
183    private OffspringSelectionGeneticAlgorithmMainLoop MainLoop {
184      get { return (OffspringSelectionGeneticAlgorithmMainLoop)SolutionsCreator.Successor; }
185    }
186    [Storable]
187    private BestAverageWorstQualityAnalyzer qualityAnalyzer;
188    [Storable]
189    private ValueAnalyzer selectionPressureAnalyzer;
190    #endregion
191
192    [StorableConstructor]
193    private OffspringSelectionGeneticAlgorithm(bool deserializing) : base(deserializing) { }
194    public OffspringSelectionGeneticAlgorithm()
195      : base() {
196      Parameters.Add(new ValueParameter<IntValue>("Seed", "The random seed used to initialize the new pseudo random number generator.", new IntValue(0)));
197      Parameters.Add(new ValueParameter<BoolValue>("SetSeedRandomly", "True if the random seed should be set to a random value, otherwise false.", new BoolValue(true)));
198      Parameters.Add(new ValueParameter<IntValue>("PopulationSize", "The size of the population of solutions.", new IntValue(100)));
199      Parameters.Add(new ConstrainedValueParameter<ISelector>("Selector", "The operator used to select solutions for reproduction."));
200      Parameters.Add(new ConstrainedValueParameter<ICrossover>("Crossover", "The operator used to cross solutions."));
201      Parameters.Add(new ValueParameter<PercentValue>("MutationProbability", "The probability that the mutation operator is applied on a solution.", new PercentValue(0.05)));
202      Parameters.Add(new OptionalConstrainedValueParameter<IManipulator>("Mutator", "The operator used to mutate solutions."));
203      Parameters.Add(new ValueParameter<IntValue>("Elites", "The numer of elite solutions which are kept in each generation.", new IntValue(1)));
204      Parameters.Add(new ValueParameter<IntValue>("MaximumGenerations", "The maximum number of generations which should be processed.", new IntValue(1000)));
205      Parameters.Add(new ValueLookupParameter<DoubleValue>("SuccessRatio", "The ratio of successful to total children that should be achieved.", new DoubleValue(1)));
206      Parameters.Add(new ValueLookupParameter<DoubleValue>("ComparisonFactorLowerBound", "The lower bound of the comparison factor (start).", new DoubleValue(0)));
207      Parameters.Add(new ValueLookupParameter<DoubleValue>("ComparisonFactorUpperBound", "The upper bound of the comparison factor (end).", new DoubleValue(1)));
208      Parameters.Add(new OptionalConstrainedValueParameter<IDiscreteDoubleValueModifier>("ComparisonFactorModifier", "The operator used to modify the comparison factor.", new ItemSet<IDiscreteDoubleValueModifier>(new IDiscreteDoubleValueModifier[] { new LinearDiscreteDoubleValueModifier() }), new LinearDiscreteDoubleValueModifier()));
209      Parameters.Add(new ValueLookupParameter<DoubleValue>("MaximumSelectionPressure", "The maximum selection pressure that terminates the algorithm.", new DoubleValue(100)));
210      Parameters.Add(new ValueLookupParameter<BoolValue>("OffspringSelectionBeforeMutation", "True if the offspring selection step should be applied before mutation, false if it should be applied after mutation.", new BoolValue(false)));
211      Parameters.Add(new ValueLookupParameter<IntValue>("SelectedParents", "Should be about 2 * PopulationSize, for large problems use a smaller value to decrease memory footprint.", new IntValue(200)));
212      Parameters.Add(new ValueParameter<MultiAnalyzer>("Analyzer", "The operator used to analyze each generation.", new MultiAnalyzer()));
213     
214      RandomCreator randomCreator = new RandomCreator();
215      SolutionsCreator solutionsCreator = new SolutionsCreator();
216      OffspringSelectionGeneticAlgorithmMainLoop mainLoop = new OffspringSelectionGeneticAlgorithmMainLoop();
217      OperatorGraph.InitialOperator = randomCreator;
218
219      randomCreator.RandomParameter.ActualName = "Random";
220      randomCreator.SeedParameter.ActualName = SeedParameter.Name;
221      randomCreator.SeedParameter.Value = null;
222      randomCreator.SetSeedRandomlyParameter.ActualName = SetSeedRandomlyParameter.Name;
223      randomCreator.SetSeedRandomlyParameter.Value = null;
224      randomCreator.Successor = solutionsCreator;
225
226      solutionsCreator.NumberOfSolutionsParameter.ActualName = PopulationSizeParameter.Name;
227      solutionsCreator.Successor = mainLoop;
228
229      mainLoop.SelectorParameter.ActualName = SelectorParameter.Name;
230      mainLoop.CrossoverParameter.ActualName = CrossoverParameter.Name;
231      mainLoop.ElitesParameter.ActualName = ElitesParameter.Name;
232      mainLoop.MaximumGenerationsParameter.ActualName = MaximumGenerationsParameter.Name;
233      mainLoop.MutatorParameter.ActualName = MutatorParameter.Name;
234      mainLoop.MutationProbabilityParameter.ActualName = MutationProbabilityParameter.Name;
235      mainLoop.RandomParameter.ActualName = RandomCreator.RandomParameter.ActualName;
236      mainLoop.ResultsParameter.ActualName = "Results";
237
238      foreach (ISelector selector in ApplicationManager.Manager.GetInstances<ISelector>().Where(x => !(x is IMultiObjectiveSelector)).OrderBy(x => x.Name))
239        SelectorParameter.ValidValues.Add(selector);
240      ISelector proportionalSelector = SelectorParameter.ValidValues.FirstOrDefault(x => x.GetType().Name.Equals("ProportionalSelector"));
241      if (proportionalSelector != null) SelectorParameter.Value = proportionalSelector;
242      ParameterizeSelectors();
243
244      foreach (IDiscreteDoubleValueModifier modifier in ApplicationManager.Manager.GetInstances<IDiscreteDoubleValueModifier>().OrderBy(x => x.Name))
245        ComparisonFactorModifierParameter.ValidValues.Add(modifier);
246      IDiscreteDoubleValueModifier linearModifier = ComparisonFactorModifierParameter.ValidValues.FirstOrDefault(x => x.GetType().Name.Equals("LinearDiscreteDoubleValueModifier"));
247      if (linearModifier != null) ComparisonFactorModifierParameter.Value = linearModifier;
248      ParameterizeComparisonFactorModifiers();
249
250      qualityAnalyzer = new BestAverageWorstQualityAnalyzer();
251      selectionPressureAnalyzer = new ValueAnalyzer();
252      ParameterizeAnalyzers();
253      UpdateAnalyzers();
254
255      Initialize();
256    }
257
258    public override IDeepCloneable Clone(Cloner cloner) {
259      OffspringSelectionGeneticAlgorithm clone = (OffspringSelectionGeneticAlgorithm)base.Clone(cloner);
260      clone.qualityAnalyzer = (BestAverageWorstQualityAnalyzer)cloner.Clone(qualityAnalyzer);
261      clone.selectionPressureAnalyzer = (ValueAnalyzer)cloner.Clone(selectionPressureAnalyzer);
262      clone.Initialize();
263      return clone;
264    }
265
266    public override void Prepare() {
267      if (Problem != null) base.Prepare();
268    }
269
270    #region Events
271    protected override void OnProblemChanged() {
272      ParameterizeStochasticOperator(Problem.SolutionCreator);
273      ParameterizeStochasticOperator(Problem.Evaluator);
274      foreach (IOperator op in Problem.Operators) ParameterizeStochasticOperator(op);
275      ParameterizeSolutionsCreator();
276      ParameterizMainLoop();
277      ParameterizeSelectors();
278      ParameterizeAnalyzers();
279      UpdateCrossovers();
280      UpdateMutators();
281      UpdateAnalyzers();
282      Problem.Evaluator.QualityParameter.ActualNameChanged += new EventHandler(Evaluator_QualityParameter_ActualNameChanged);
283      base.OnProblemChanged();
284    }
285
286    protected override void Problem_SolutionCreatorChanged(object sender, EventArgs e) {
287      ParameterizeStochasticOperator(Problem.SolutionCreator);
288      ParameterizeSolutionsCreator();
289      base.Problem_SolutionCreatorChanged(sender, e);
290    }
291    protected override void Problem_EvaluatorChanged(object sender, EventArgs e) {
292      ParameterizeStochasticOperator(Problem.Evaluator);
293      ParameterizeSolutionsCreator();
294      ParameterizMainLoop();
295      ParameterizeSelectors();
296      ParameterizeAnalyzers();
297      Problem.Evaluator.QualityParameter.ActualNameChanged += new EventHandler(Evaluator_QualityParameter_ActualNameChanged);
298      base.Problem_EvaluatorChanged(sender, e);
299    }
300    protected override void Problem_OperatorsChanged(object sender, EventArgs e) {
301      foreach (IOperator op in Problem.Operators) ParameterizeStochasticOperator(op);
302      UpdateCrossovers();
303      UpdateMutators();
304      UpdateAnalyzers();
305      base.Problem_OperatorsChanged(sender, e);
306    }
307    private void ElitesParameter_ValueChanged(object sender, EventArgs e) {
308      Elites.ValueChanged += new EventHandler(Elites_ValueChanged);
309      ParameterizeSelectors();
310    }
311    private void Elites_ValueChanged(object sender, EventArgs e) {
312      ParameterizeSelectors();
313    }
314    private void PopulationSizeParameter_ValueChanged(object sender, EventArgs e) {
315      PopulationSize.ValueChanged += new EventHandler(PopulationSize_ValueChanged);
316      ParameterizeSelectors();
317    }
318    private void PopulationSize_ValueChanged(object sender, EventArgs e) {
319      ParameterizeSelectors();
320    }
321    private void Evaluator_QualityParameter_ActualNameChanged(object sender, EventArgs e) {
322      ParameterizMainLoop();
323      ParameterizeSelectors();
324      ParameterizeAnalyzers();
325    }
326    #endregion
327
328    #region Helpers
329    [StorableHook(HookType.AfterDeserialization)]
330    private void Initialize() {
331      PopulationSizeParameter.ValueChanged += new EventHandler(PopulationSizeParameter_ValueChanged);
332      PopulationSize.ValueChanged += new EventHandler(PopulationSize_ValueChanged);
333      ElitesParameter.ValueChanged += new EventHandler(ElitesParameter_ValueChanged);
334      Elites.ValueChanged += new EventHandler(Elites_ValueChanged);
335      if (Problem != null) {
336        Problem.Evaluator.QualityParameter.ActualNameChanged += new EventHandler(Evaluator_QualityParameter_ActualNameChanged);
337      }
338    }
339    private void ParameterizeSolutionsCreator() {
340      SolutionsCreator.EvaluatorParameter.ActualName = Problem.EvaluatorParameter.Name;
341      SolutionsCreator.SolutionCreatorParameter.ActualName = Problem.SolutionCreatorParameter.Name;
342    }
343    private void ParameterizMainLoop() {
344      MainLoop.EvaluatorParameter.ActualName = Problem.EvaluatorParameter.Name;
345      MainLoop.MaximizationParameter.ActualName = Problem.MaximizationParameter.Name;
346      MainLoop.QualityParameter.ActualName = Problem.Evaluator.QualityParameter.ActualName;
347    }
348    private void ParameterizeStochasticOperator(IOperator op) {
349      if (op is IStochasticOperator)
350        ((IStochasticOperator)op).RandomParameter.ActualName = RandomCreator.RandomParameter.ActualName;
351    }
352    private void ParameterizeSelectors() {
353      foreach (ISelector selector in SelectorParameter.ValidValues) {
354        selector.CopySelected = new BoolValue(true);
355        selector.NumberOfSelectedSubScopesParameter.Value = null;
356        selector.NumberOfSelectedSubScopesParameter.ActualName = SelectedParentsParameter.Name;
357        ParameterizeStochasticOperator(selector);
358      }
359      if (Problem != null) {
360        foreach (ISingleObjectiveSelector selector in SelectorParameter.ValidValues.OfType<ISingleObjectiveSelector>()) {
361          selector.MaximizationParameter.ActualName = Problem.MaximizationParameter.Name;
362          selector.QualityParameter.ActualName = Problem.Evaluator.QualityParameter.ActualName;
363        }
364      }
365    }
366    private void ParameterizeAnalyzers() {
367      qualityAnalyzer.ResultsParameter.ActualName = "Results";
368      selectionPressureAnalyzer.Name = "SelectionPressure Analyzer";
369      selectionPressureAnalyzer.ResultsParameter.ActualName = "Results";
370      selectionPressureAnalyzer.ValueParameter.ActualName = "SelectionPressure";
371      selectionPressureAnalyzer.ValueParameter.Depth = 0;
372      selectionPressureAnalyzer.ValuesParameter.ActualName = "Selection Pressure History";
373      if (Problem != null) {
374        qualityAnalyzer.MaximizationParameter.ActualName = Problem.MaximizationParameter.Name;
375        qualityAnalyzer.QualityParameter.ActualName = Problem.Evaluator.QualityParameter.ActualName;
376        qualityAnalyzer.BestKnownQualityParameter.ActualName = Problem.BestKnownQualityParameter.Name;
377      }
378    }
379    private void ParameterizeComparisonFactorModifiers() {
380      foreach (IDiscreteDoubleValueModifier modifier in ComparisonFactorModifierParameter.ValidValues) {
381        modifier.IndexParameter.ActualName = "Generations";
382        modifier.EndIndexParameter.ActualName = MaximumGenerationsParameter.Name;
383        modifier.EndValueParameter.ActualName = ComparisonFactorUpperBoundParameter.Name;
384        modifier.StartIndexParameter.Value = new IntValue(0);
385        modifier.StartValueParameter.ActualName = ComparisonFactorLowerBoundParameter.Name;
386        modifier.ValueParameter.ActualName = "ComparisonFactor";
387      }
388    }
389    private void UpdateCrossovers() {
390      ICrossover oldCrossover = CrossoverParameter.Value;
391      CrossoverParameter.ValidValues.Clear();
392      foreach (ICrossover crossover in Problem.Operators.OfType<ICrossover>().OrderBy(x => x.Name))
393        CrossoverParameter.ValidValues.Add(crossover);
394      if (oldCrossover != null) {
395        ICrossover crossover = CrossoverParameter.ValidValues.FirstOrDefault(x => x.GetType() == oldCrossover.GetType());
396        if (crossover != null) CrossoverParameter.Value = crossover;
397      }
398    }
399    private void UpdateMutators() {
400      IManipulator oldMutator = MutatorParameter.Value;
401      MutatorParameter.ValidValues.Clear();
402      foreach (IManipulator mutator in Problem.Operators.OfType<IManipulator>().OrderBy(x => x.Name))
403        MutatorParameter.ValidValues.Add(mutator);
404      if (oldMutator != null) {
405        IManipulator mutator = MutatorParameter.ValidValues.FirstOrDefault(x => x.GetType() == oldMutator.GetType());
406        if (mutator != null) MutatorParameter.Value = mutator;
407      }
408    }
409    private void UpdateAnalyzers() {
410      Analyzer.Operators.Clear();
411      Analyzer.Operators.Add(qualityAnalyzer);
412      Analyzer.Operators.Add(selectionPressureAnalyzer);
413      if (Problem != null) {
414        foreach (IAnalyzer analyzer in Problem.Operators.OfType<IAnalyzer>().OrderBy(x => x.Name)) {
415          foreach (IScopeTreeLookupParameter param in analyzer.Parameters.OfType<IScopeTreeLookupParameter>())
416            param.Depth = 1;
417          Analyzer.Operators.Add(analyzer);
418        }
419      }
420    }
421    #endregion
422  }
423}
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