Free cookie consent management tool by TermsFeed Policy Generator

source: trunk/sources/HeuristicLab.Algorithms.ALPS/3.3/AlpsGeneticAlgorithm.cs @ 14871

Last change on this file since 14871 was 14774, checked in by pfleck, 8 years ago

#2753: Fixed the missing re-parameterization of the evaluator.
File size: 34.3 KB
Line 
1#region License Information
2/* HeuristicLab
3 * Copyright (C) 2002-2016 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.Collections;
27using HeuristicLab.Common;
28using HeuristicLab.Core;
29using HeuristicLab.Data;
30using HeuristicLab.Operators;
31using HeuristicLab.Optimization;
32using HeuristicLab.Optimization.Operators;
33using HeuristicLab.Parameters;
34using HeuristicLab.Persistence.Default.CompositeSerializers.Storable;
35using HeuristicLab.PluginInfrastructure;
36using HeuristicLab.Random;
37using HeuristicLab.Selection;
38
39namespace HeuristicLab.Algorithms.ALPS {
40  [Item("ALPS Genetic Algorithm", "A genetic algorithm within an age-layered population structure as described in Gregory S. Hornby. 2006. ALPS: the age-layered population structure for reducing the problem of premature convergence. In Proceedings of the 8th annual conference on Genetic and evolutionary computation (GECCO '06). 815-822.")]
41  [Creatable(CreatableAttribute.Categories.PopulationBasedAlgorithms, Priority = 160)]
42  [StorableClass]
43  public sealed class AlpsGeneticAlgorithm : HeuristicOptimizationEngineAlgorithm, IStorableContent {
44    public string Filename { get; set; }
45
46    #region Problem Properties
47    public override Type ProblemType {
48      get { return typeof(ISingleObjectiveHeuristicOptimizationProblem); }
49    }
50    public new ISingleObjectiveHeuristicOptimizationProblem Problem {
51      get { return (ISingleObjectiveHeuristicOptimizationProblem)base.Problem; }
52      set { base.Problem = value; }
53    }
54    #endregion
55
56    #region Parameter Properties
57    private IValueParameter<IntValue> SeedParameter {
58      get { return (IValueParameter<IntValue>)Parameters["Seed"]; }
59    }
60    private IValueParameter<BoolValue> SetSeedRandomlyParameter {
61      get { return (IValueParameter<BoolValue>)Parameters["SetSeedRandomly"]; }
62    }
63
64    private IFixedValueParameter<MultiAnalyzer> AnalyzerParameter {
65      get { return (IFixedValueParameter<MultiAnalyzer>)Parameters["Analyzer"]; }
66    }
67    private IFixedValueParameter<MultiAnalyzer> LayerAnalyzerParameter {
68      get { return (IFixedValueParameter<MultiAnalyzer>)Parameters["LayerAnalyzer"]; }
69    }
70
71    private IValueParameter<IntValue> NumberOfLayersParameter {
72      get { return (IValueParameter<IntValue>)Parameters["NumberOfLayers"]; }
73    }
74    private IValueParameter<IntValue> PopulationSizeParameter {
75      get { return (IValueParameter<IntValue>)Parameters["PopulationSize"]; }
76    }
77
78    public IConstrainedValueParameter<ISelector> SelectorParameter {
79      get { return (IConstrainedValueParameter<ISelector>)Parameters["Selector"]; }
80    }
81    public IConstrainedValueParameter<ICrossover> CrossoverParameter {
82      get { return (IConstrainedValueParameter<ICrossover>)Parameters["Crossover"]; }
83    }
84    public IConstrainedValueParameter<IManipulator> MutatorParameter {
85      get { return (IConstrainedValueParameter<IManipulator>)Parameters["Mutator"]; }
86    }
87    private IValueParameter<PercentValue> MutationProbabilityParameter {
88      get { return (IValueParameter<PercentValue>)Parameters["MutationProbability"]; }
89    }
90    private IValueParameter<IntValue> ElitesParameter {
91      get { return (IValueParameter<IntValue>)Parameters["Elites"]; }
92    }
93    private IFixedValueParameter<BoolValue> ReevaluateElitesParameter {
94      get { return (IFixedValueParameter<BoolValue>)Parameters["ReevaluateElites"]; }
95    }
96    private IValueParameter<BoolValue> PlusSelectionParameter {
97      get { return (IValueParameter<BoolValue>)Parameters["PlusSelection"]; }
98    }
99
100    private IValueParameter<EnumValue<AgingScheme>> AgingSchemeParameter {
101      get { return (IValueParameter<EnumValue<AgingScheme>>)Parameters["AgingScheme"]; }
102    }
103    private IValueParameter<IntValue> AgeGapParameter {
104      get { return (IValueParameter<IntValue>)Parameters["AgeGap"]; }
105    }
106    private IValueParameter<DoubleValue> AgeInheritanceParameter {
107      get { return (IValueParameter<DoubleValue>)Parameters["AgeInheritance"]; }
108    }
109    private IValueParameter<IntArray> AgeLimitsParameter {
110      get { return (IValueParameter<IntArray>)Parameters["AgeLimits"]; }
111    }
112
113    private IValueParameter<IntValue> MatingPoolRangeParameter {
114      get { return (IValueParameter<IntValue>)Parameters["MatingPoolRange"]; }
115    }
116    private IValueParameter<BoolValue> ReduceToPopulationSizeParameter {
117      get { return (IValueParameter<BoolValue>)Parameters["ReduceToPopulationSize"]; }
118    }
119
120    private IValueParameter<MultiTerminator> TerminatorParameter {
121      get { return (IValueParameter<MultiTerminator>)Parameters["Terminator"]; }
122    }
123    #endregion
124
125    #region Properties
126    public IntValue Seed {
127      get { return SeedParameter.Value; }
128      set { SeedParameter.Value = value; }
129    }
130    public BoolValue SetSeedRandomly {
131      get { return SetSeedRandomlyParameter.Value; }
132      set { SetSeedRandomlyParameter.Value = value; }
133    }
134
135    public MultiAnalyzer Analyzer {
136      get { return AnalyzerParameter.Value; }
137    }
138    public MultiAnalyzer LayerAnalyzer {
139      get { return LayerAnalyzerParameter.Value; }
140    }
141
142    public IntValue NumberOfLayers {
143      get { return NumberOfLayersParameter.Value; }
144      set { NumberOfLayersParameter.Value = value; }
145    }
146    public IntValue PopulationSize {
147      get { return PopulationSizeParameter.Value; }
148      set { PopulationSizeParameter.Value = value; }
149    }
150
151    public ISelector Selector {
152      get { return SelectorParameter.Value; }
153      set { SelectorParameter.Value = value; }
154    }
155    public ICrossover Crossover {
156      get { return CrossoverParameter.Value; }
157      set { CrossoverParameter.Value = value; }
158    }
159    public IManipulator Mutator {
160      get { return MutatorParameter.Value; }
161      set { MutatorParameter.Value = value; }
162    }
163    public PercentValue MutationProbability {
164      get { return MutationProbabilityParameter.Value; }
165      set { MutationProbabilityParameter.Value = value; }
166    }
167    public IntValue Elites {
168      get { return ElitesParameter.Value; }
169      set { ElitesParameter.Value = value; }
170    }
171    public bool ReevaluteElites {
172      get { return ReevaluateElitesParameter.Value.Value; }
173      set { ReevaluateElitesParameter.Value.Value = value; }
174    }
175    public bool PlusSelection {
176      get { return PlusSelectionParameter.Value.Value; }
177      set { PlusSelectionParameter.Value.Value = value; }
178    }
179
180    public EnumValue<AgingScheme> AgingScheme {
181      get { return AgingSchemeParameter.Value; }
182      set { AgingSchemeParameter.Value = value; }
183    }
184    public IntValue AgeGap {
185      get { return AgeGapParameter.Value; }
186      set { AgeGapParameter.Value = value; }
187    }
188    public DoubleValue AgeInheritance {
189      get { return AgeInheritanceParameter.Value; }
190      set { AgeInheritanceParameter.Value = value; }
191    }
192    public IntArray AgeLimits {
193      get { return AgeLimitsParameter.Value; }
194      set { AgeLimitsParameter.Value = value; }
195    }
196
197    public IntValue MatingPoolRange {
198      get { return MatingPoolRangeParameter.Value; }
199      set { MatingPoolRangeParameter.Value = value; }
200    }
201
202    public MultiTerminator Terminators {
203      get { return TerminatorParameter.Value; }
204    }
205
206    public int MaximumGenerations {
207      get { return generationsTerminator.Threshold.Value; }
208      set { generationsTerminator.Threshold.Value = value; }
209    }
210    #endregion
211
212    #region Helper Properties
213    private SolutionsCreator SolutionsCreator {
214      get { return OperatorGraph.Iterate().OfType<SolutionsCreator>().First(); }
215    }
216    private AlpsGeneticAlgorithmMainLoop MainLoop {
217      get { return OperatorGraph.Iterate().OfType<AlpsGeneticAlgorithmMainLoop>().First(); }
218    }
219    #endregion
220
221    #region Preconfigured Analyzers
222    [Storable]
223    private BestAverageWorstQualityAnalyzer qualityAnalyzer;
224    [Storable]
225    private BestAverageWorstQualityAnalyzer layerQualityAnalyzer;
226    [Storable]
227    private OldestAverageYoungestAgeAnalyzer ageAnalyzer;
228    [Storable]
229    private OldestAverageYoungestAgeAnalyzer layerAgeAnalyzer;
230    [Storable]
231    private AgeDistributionAnalyzer ageDistributionAnalyzer;
232    [Storable]
233    private AgeDistributionAnalyzer layerAgeDistributionAnalyzer;
234    #endregion
235
236    #region Preconfigured Terminators
237    [Storable]
238    private ComparisonTerminator<IntValue> generationsTerminator;
239    [Storable]
240    private ComparisonTerminator<IntValue> evaluationsTerminator;
241    [Storable]
242    private SingleObjectiveQualityTerminator qualityTerminator;
243    [Storable]
244    private ExecutionTimeTerminator executionTimeTerminator;
245    #endregion
246
247    #region Constructors
248    [StorableConstructor]
249    private AlpsGeneticAlgorithm(bool deserializing)
250      : base(deserializing) { }
251    [StorableHook(HookType.AfterDeserialization)]
252    private void AfterDeserialization() {
253      Initialize();
254    }
255    private AlpsGeneticAlgorithm(AlpsGeneticAlgorithm original, Cloner cloner)
256      : base(original, cloner) {
257      qualityAnalyzer = cloner.Clone(original.qualityAnalyzer);
258      layerQualityAnalyzer = cloner.Clone(original.layerQualityAnalyzer);
259      ageAnalyzer = cloner.Clone(original.ageAnalyzer);
260      layerAgeAnalyzer = cloner.Clone(original.layerAgeAnalyzer);
261      ageDistributionAnalyzer = cloner.Clone(original.ageDistributionAnalyzer);
262      layerAgeDistributionAnalyzer = cloner.Clone(original.layerAgeDistributionAnalyzer);
263      generationsTerminator = cloner.Clone(original.generationsTerminator);
264      evaluationsTerminator = cloner.Clone(original.evaluationsTerminator);
265      qualityTerminator = cloner.Clone(original.qualityTerminator);
266      executionTimeTerminator = cloner.Clone(original.executionTimeTerminator);
267      Initialize();
268    }
269    public override IDeepCloneable Clone(Cloner cloner) {
270      return new AlpsGeneticAlgorithm(this, cloner);
271    }
272    public AlpsGeneticAlgorithm()
273      : base() {
274      #region Add parameters
275      Parameters.Add(new ValueParameter<IntValue>("Seed", "The random seed used to initialize the new pseudo random number generator.", new IntValue(0)));
276      Parameters.Add(new ValueParameter<BoolValue>("SetSeedRandomly", "True if the random seed should be set to a random value, otherwise false.", new BoolValue(true)));
277
278      Parameters.Add(new FixedValueParameter<MultiAnalyzer>("Analyzer", "The operator used to analyze all individuals from all layers combined.", new MultiAnalyzer()));
279      Parameters.Add(new FixedValueParameter<MultiAnalyzer>("LayerAnalyzer", "The operator used to analyze each layer.", new MultiAnalyzer()));
280
281      Parameters.Add(new ValueParameter<IntValue>("NumberOfLayers", "The number of layers.", new IntValue(10)));
282      Parameters.Add(new ValueParameter<IntValue>("PopulationSize", "The size of the population of solutions in each layer.", new IntValue(100)));
283
284      Parameters.Add(new ConstrainedValueParameter<ISelector>("Selector", "The operator used to select solutions for reproduction."));
285      Parameters.Add(new ConstrainedValueParameter<ICrossover>("Crossover", "The operator used to cross solutions."));
286      Parameters.Add(new OptionalConstrainedValueParameter<IManipulator>("Mutator", "The operator used to mutate solutions."));
287      Parameters.Add(new ValueParameter<PercentValue>("MutationProbability", "The probability that the mutation operator is applied on a solution.", new PercentValue(0.05)));
288      Parameters.Add(new ValueParameter<IntValue>("Elites", "The numer of elite solutions which are kept in each generation.", new IntValue(1)));
289      Parameters.Add(new FixedValueParameter<BoolValue>("ReevaluateElites", "Flag to determine if elite individuals should be reevaluated (i.e., if stochastic fitness functions are used.)", new BoolValue(false)) { Hidden = true });
290      Parameters.Add(new ValueParameter<BoolValue>("PlusSelection", "Include the parents in the selection of the invividuals for the next generation.", new BoolValue(false)));
291
292      Parameters.Add(new ValueParameter<EnumValue<AgingScheme>>("AgingScheme", "The aging scheme for setting the age-limits for the layers.", new EnumValue<AgingScheme>(ALPS.AgingScheme.Polynomial)));
293      Parameters.Add(new ValueParameter<IntValue>("AgeGap", "The frequency of reseeding the lowest layer and scaling factor for the age-limits for the layers.", new IntValue(20)));
294      Parameters.Add(new ValueParameter<DoubleValue>("AgeInheritance", "A weight that determines the age of a child after crossover based on the older (1.0) and younger (0.0) parent.", new DoubleValue(1.0)) { Hidden = true });
295      Parameters.Add(new ValueParameter<IntArray>("AgeLimits", "The maximum age an individual is allowed to reach in a certain layer.", new IntArray(new int[0])) { Hidden = true });
296
297      Parameters.Add(new ValueParameter<IntValue>("MatingPoolRange", "The range of layers used for creating a mating pool. (1 = current + previous layer)", new IntValue(1)) { Hidden = true });
298      Parameters.Add(new ValueParameter<BoolValue>("ReduceToPopulationSize", "Reduce the CurrentPopulationSize after elder migration to PopulationSize", new BoolValue(true)) { Hidden = true });
299
300      Parameters.Add(new ValueParameter<MultiTerminator>("Terminator", "The termination criteria that defines if the algorithm should continue or stop.", new MultiTerminator()));
301      #endregion
302
303      #region Create operators
304      var globalRandomCreator = new RandomCreator();
305      var layer0Creator = new SubScopesCreator() { Name = "Create Layer Zero" };
306      var layer0Processor = new SubScopesProcessor();
307      var localRandomCreator = new LocalRandomCreator();
308      var layerSolutionsCreator = new SolutionsCreator();
309      var initializeAgeProcessor = new UniformSubScopesProcessor();
310      var initializeAge = new VariableCreator() { Name = "Initialize Age" };
311      var initializeCurrentPopulationSize = new SubScopesCounter() { Name = "Initialize CurrentPopulationCounter" };
312      var initializeLocalEvaluatedSolutions = new Assigner() { Name = "Initialize LayerEvaluatedSolutions" };
313      var initializeGlobalEvaluatedSolutions = new DataReducer() { Name = "Initialize EvaluatedSolutions" };
314      var resultsCollector = new ResultsCollector();
315      var mainLoop = new AlpsGeneticAlgorithmMainLoop();
316      #endregion
317
318      #region Create and parameterize operator graph
319      OperatorGraph.InitialOperator = globalRandomCreator;
320
321      globalRandomCreator.RandomParameter.ActualName = "GlobalRandom";
322      globalRandomCreator.SeedParameter.Value = null;
323      globalRandomCreator.SeedParameter.ActualName = SeedParameter.Name;
324      globalRandomCreator.SetSeedRandomlyParameter.Value = null;
325      globalRandomCreator.SetSeedRandomlyParameter.ActualName = SetSeedRandomlyParameter.Name;
326      globalRandomCreator.Successor = layer0Creator;
327
328      layer0Creator.NumberOfSubScopesParameter.Value = new IntValue(1);
329      layer0Creator.Successor = layer0Processor;
330
331      layer0Processor.Operators.Add(localRandomCreator);
332      layer0Processor.Successor = initializeGlobalEvaluatedSolutions;
333
334      localRandomCreator.Successor = layerSolutionsCreator;
335
336      layerSolutionsCreator.NumberOfSolutionsParameter.ActualName = PopulationSizeParameter.Name;
337      layerSolutionsCreator.Successor = initializeAgeProcessor;
338
339      initializeAgeProcessor.Operator = initializeAge;
340      initializeAgeProcessor.Successor = initializeCurrentPopulationSize;
341
342      initializeCurrentPopulationSize.ValueParameter.ActualName = "CurrentPopulationSize";
343      initializeCurrentPopulationSize.Successor = initializeLocalEvaluatedSolutions;
344
345      initializeAge.CollectedValues.Add(new ValueParameter<DoubleValue>("Age", new DoubleValue(0)));
346      initializeAge.Successor = null;
347
348      initializeLocalEvaluatedSolutions.LeftSideParameter.ActualName = "LayerEvaluatedSolutions";
349      initializeLocalEvaluatedSolutions.RightSideParameter.ActualName = "CurrentPopulationSize";
350      initializeLocalEvaluatedSolutions.Successor = null;
351
352      initializeGlobalEvaluatedSolutions.ReductionOperation.Value.Value = ReductionOperations.Sum;
353      initializeGlobalEvaluatedSolutions.TargetOperation.Value.Value = ReductionOperations.Assign;
354      initializeGlobalEvaluatedSolutions.ParameterToReduce.ActualName = "LayerEvaluatedSolutions";
355      initializeGlobalEvaluatedSolutions.TargetParameter.ActualName = "EvaluatedSolutions";
356      initializeGlobalEvaluatedSolutions.Successor = resultsCollector;
357
358      resultsCollector.CollectedValues.Add(new LookupParameter<IntValue>("Evaluated Solutions", null, "EvaluatedSolutions"));
359      resultsCollector.Successor = mainLoop;
360
361      mainLoop.GlobalRandomParameter.ActualName = "GlobalRandom";
362      mainLoop.LocalRandomParameter.ActualName = localRandomCreator.LocalRandomParameter.Name;
363      mainLoop.EvaluatedSolutionsParameter.ActualName = "EvaluatedSolutions";
364      mainLoop.AnalyzerParameter.ActualName = AnalyzerParameter.Name;
365      mainLoop.LayerAnalyzerParameter.ActualName = LayerAnalyzerParameter.Name;
366      mainLoop.NumberOfLayersParameter.ActualName = NumberOfLayersParameter.Name;
367      mainLoop.PopulationSizeParameter.ActualName = PopulationSizeParameter.Name;
368      mainLoop.CurrentPopulationSizeParameter.ActualName = "CurrentPopulationSize";
369      mainLoop.SelectorParameter.ActualName = SelectorParameter.Name;
370      mainLoop.CrossoverParameter.ActualName = CrossoverParameter.Name;
371      mainLoop.MutatorParameter.ActualName = MutatorParameter.Name;
372      mainLoop.MutationProbabilityParameter.ActualName = MutationProbabilityParameter.Name;
373      mainLoop.ElitesParameter.ActualName = ElitesParameter.Name;
374      mainLoop.ReevaluateElitesParameter.ActualName = ReevaluateElitesParameter.Name;
375      mainLoop.PlusSelectionParameter.ActualName = PlusSelectionParameter.Name;
376      mainLoop.AgeParameter.ActualName = "Age";
377      mainLoop.AgeGapParameter.ActualName = AgeGapParameter.Name;
378      mainLoop.AgeInheritanceParameter.ActualName = AgeInheritanceParameter.Name;
379      mainLoop.AgeLimitsParameter.ActualName = AgeLimitsParameter.Name;
380      mainLoop.MatingPoolRangeParameter.ActualName = MatingPoolRangeParameter.Name;
381      mainLoop.ReduceToPopulationSizeParameter.ActualName = ReduceToPopulationSizeParameter.Name;
382      mainLoop.TerminatorParameter.ActualName = TerminatorParameter.Name;
383      #endregion
384
385      #region Set selectors
386      foreach (var selector in ApplicationManager.Manager.GetInstances<ISelector>().Where(s => !(s is IMultiObjectiveSelector)).OrderBy(s => Name))
387        SelectorParameter.ValidValues.Add(selector);
388      var defaultSelector = SelectorParameter.ValidValues.OfType<GeneralizedRankSelector>().FirstOrDefault();
389      if (defaultSelector != null) {
390        defaultSelector.PressureParameter.Value = new DoubleValue(4.0);
391        SelectorParameter.Value = defaultSelector;
392      }
393      #endregion
394
395      #region Create analyzers
396      qualityAnalyzer = new BestAverageWorstQualityAnalyzer();
397      layerQualityAnalyzer = new BestAverageWorstQualityAnalyzer();
398      ageAnalyzer = new OldestAverageYoungestAgeAnalyzer();
399      layerAgeAnalyzer = new OldestAverageYoungestAgeAnalyzer();
400      ageDistributionAnalyzer = new AgeDistributionAnalyzer();
401      layerAgeDistributionAnalyzer = new AgeDistributionAnalyzer();
402      #endregion
403
404      #region Create terminators
405      generationsTerminator = new ComparisonTerminator<IntValue>("Generations", ComparisonType.Less, new IntValue(1000)) { Name = "Generations" };
406      evaluationsTerminator = new ComparisonTerminator<IntValue>("EvaluatedSolutions", ComparisonType.Less, new IntValue(int.MaxValue)) { Name = "Evaluations" };
407      qualityTerminator = new SingleObjectiveQualityTerminator() { Name = "Quality" };
408      executionTimeTerminator = new ExecutionTimeTerminator(this, new TimeSpanValue(TimeSpan.FromMinutes(5)));
409      #endregion
410
411      #region Parameterize
412      UpdateAnalyzers();
413      ParameterizeAnalyzers();
414
415      ParameterizeSelectors();
416
417      UpdateTerminators();
418
419      ParameterizeAgeLimits();
420      #endregion
421
422      Initialize();
423    }
424    #endregion
425
426    #region Events
427    public override void Prepare() {
428      if (Problem != null)
429        base.Prepare();
430    }
431    protected override void OnProblemChanged() {
432      base.OnProblemChanged();
433      ParameterizeStochasticOperator(Problem.SolutionCreator);
434      ParameterizeStochasticOperatorForLayer(Problem.Evaluator);
435      foreach (var @operator in Problem.Operators.OfType<IOperator>())
436        ParameterizeStochasticOperator(@operator);
437
438      ParameterizeIterationBasedOperators();
439
440      ParameterizeSolutionsCreator();
441      ParameterizeMainLoop();
442      ParameterizeAnalyzers();
443      ParameterizeSelectors();
444      ParameterizeTerminators();
445
446      Problem.Evaluator.QualityParameter.ActualNameChanged += Evaluator_QualityParameter_ActualNameChanged;
447
448      UpdateAnalyzers();
449      UpdateCrossovers();
450      UpdateMutators();
451      UpdateTerminators();
452    }
453
454    protected override void RegisterProblemEvents() {
455      base.RegisterProblemEvents();
456      var maximizationParameter = (IValueParameter<BoolValue>)Problem.MaximizationParameter;
457      if (maximizationParameter != null) maximizationParameter.ValueChanged += new EventHandler(MaximizationParameter_ValueChanged);
458    }
459    protected override void DeregisterProblemEvents() {
460      var maximizationParameter = (IValueParameter<BoolValue>)Problem.MaximizationParameter;
461      if (maximizationParameter != null) maximizationParameter.ValueChanged -= new EventHandler(MaximizationParameter_ValueChanged);
462      base.DeregisterProblemEvents();
463    }
464
465    protected override void Problem_SolutionCreatorChanged(object sender, EventArgs e) {
466      base.Problem_SolutionCreatorChanged(sender, e);
467      ParameterizeStochasticOperator(Problem.SolutionCreator);
468      ParameterizeStochasticOperatorForLayer(Problem.Evaluator);
469
470      Problem.Evaluator.QualityParameter.ActualNameChanged += Evaluator_QualityParameter_ActualNameChanged;
471
472      ParameterizeSolutionsCreator();
473      ParameterizeAnalyzers();
474    }
475    protected override void Problem_EvaluatorChanged(object sender, EventArgs e) {
476      base.Problem_EvaluatorChanged(sender, e);
477
478      ParameterizeStochasticOperatorForLayer(Problem.Evaluator);
479
480      foreach (var @operator in Problem.Operators.OfType<IOperator>())
481        ParameterizeStochasticOperator(@operator);
482
483      UpdateAnalyzers();
484
485      ParameterizeSolutionsCreator();
486      ParameterizeMainLoop();
487      ParameterizeSelectors();
488    }
489    protected override void Problem_OperatorsChanged(object sender, EventArgs e) {
490      base.Problem_OperatorsChanged(sender, e);
491      ParameterizeIterationBasedOperators();
492      UpdateCrossovers();
493      UpdateMutators();
494      UpdateTerminators();
495    }
496    private void Evaluator_QualityParameter_ActualNameChanged(object sender, EventArgs e) {
497      ParameterizeMainLoop();
498      ParameterizeAnalyzers();
499      ParameterizeSelectors();
500    }
501    private void MaximizationParameter_ValueChanged(object sender, EventArgs e) {
502      ParameterizeTerminators();
503    }
504    private void QualityAnalyzer_CurrentBestQualityParameter_NameChanged(object sender, EventArgs e) {
505      ParameterizeTerminators();
506    }
507
508    private void AgeGapParameter_ValueChanged(object sender, EventArgs e) {
509      AgeGap.ValueChanged += AgeGap_ValueChanged;
510      ParameterizeAgeLimits();
511    }
512    private void AgeGap_ValueChanged(object sender, EventArgs e) {
513      ParameterizeAgeLimits();
514    }
515    private void AgingSchemeParameter_ValueChanged(object sender, EventArgs e) {
516      AgingScheme.ValueChanged += AgingScheme_ValueChanged;
517      ParameterizeAgeLimits();
518    }
519    private void AgingScheme_ValueChanged(object sender, EventArgs e) {
520      ParameterizeAgeLimits();
521    }
522    private void NumberOfLayersParameter_ValueChanged(object sender, EventArgs e) {
523      NumberOfLayers.ValueChanged += NumberOfLayers_ValueChanged;
524      ParameterizeAgeLimits();
525    }
526    private void NumberOfLayers_ValueChanged(object sender, EventArgs e) {
527      ParameterizeAgeLimits();
528    }
529
530    private void AnalyzerOperators_ItemsAdded(object sender, CollectionItemsChangedEventArgs<IndexedItem<IAnalyzer>> e) {
531      foreach (var analyzer in e.Items) {
532        foreach (var parameter in analyzer.Value.Parameters.OfType<IScopeTreeLookupParameter>()) {
533          parameter.Depth = 2;
534        }
535      }
536    }
537    private void LayerAnalyzerOperators_ItemsAdded(object sender, CollectionItemsChangedEventArgs<IndexedItem<IAnalyzer>> e) {
538      foreach (var analyzer in e.Items) {
539        IParameter resultParameter;
540        if (analyzer.Value.Parameters.TryGetValue("Results", out resultParameter)) {
541          var lookupParameter = resultParameter as ILookupParameter;
542          if (lookupParameter != null)
543            lookupParameter.ActualName = "LayerResults";
544        }
545        foreach (var parameter in analyzer.Value.Parameters.OfType<IScopeTreeLookupParameter>()) {
546          parameter.Depth = 1;
547        }
548      }
549    }
550    #endregion
551
552    #region Parameterization
553    private void Initialize() {
554      if (Problem != null)
555        Problem.Evaluator.QualityParameter.ActualNameChanged += Evaluator_QualityParameter_ActualNameChanged;
556
557      NumberOfLayersParameter.ValueChanged += NumberOfLayersParameter_ValueChanged;
558      NumberOfLayers.ValueChanged += NumberOfLayers_ValueChanged;
559
560      Analyzer.Operators.ItemsAdded += AnalyzerOperators_ItemsAdded;
561      LayerAnalyzer.Operators.ItemsAdded += LayerAnalyzerOperators_ItemsAdded;
562
563      AgeGapParameter.ValueChanged += AgeGapParameter_ValueChanged;
564      AgeGap.ValueChanged += AgeGap_ValueChanged;
565      AgingSchemeParameter.ValueChanged += AgingSchemeParameter_ValueChanged;
566      AgingScheme.ValueChanged += AgingScheme_ValueChanged;
567
568      qualityAnalyzer.CurrentBestQualityParameter.NameChanged += new EventHandler(QualityAnalyzer_CurrentBestQualityParameter_NameChanged);
569    }
570    private void ParameterizeSolutionsCreator() {
571      SolutionsCreator.EvaluatorParameter.ActualName = Problem.EvaluatorParameter.Name;
572      SolutionsCreator.SolutionCreatorParameter.ActualName = Problem.SolutionCreatorParameter.Name;
573    }
574    private void ParameterizeMainLoop() {
575      MainLoop.EvaluatorParameter.ActualName = Problem.EvaluatorParameter.Name;
576      MainLoop.QualityParameter.ActualName = Problem.Evaluator.QualityParameter.ActualName;
577      MainLoop.MaximizationParameter.ActualName = Problem.MaximizationParameter.Name;
578    }
579    private void ParameterizeAnalyzers() {
580      qualityAnalyzer.ResultsParameter.ActualName = "Results";
581      qualityAnalyzer.ResultsParameter.Hidden = true;
582      qualityAnalyzer.QualityParameter.Depth = 2;
583      layerQualityAnalyzer.ResultsParameter.ActualName = "LayerResults";
584      layerQualityAnalyzer.ResultsParameter.Hidden = true;
585      layerQualityAnalyzer.QualityParameter.Depth = 1;
586      if (Problem != null) {
587        qualityAnalyzer.MaximizationParameter.ActualName = Problem.MaximizationParameter.Name;
588        qualityAnalyzer.MaximizationParameter.Hidden = true;
589        qualityAnalyzer.QualityParameter.ActualName = Problem.Evaluator.QualityParameter.ActualName;
590        qualityAnalyzer.QualityParameter.Hidden = true;
591        qualityAnalyzer.BestKnownQualityParameter.ActualName = Problem.BestKnownQualityParameter.Name;
592        qualityAnalyzer.BestKnownQualityParameter.Hidden = true;
593        layerQualityAnalyzer.MaximizationParameter.ActualName = Problem.MaximizationParameter.Name;
594        layerQualityAnalyzer.MaximizationParameter.Hidden = true;
595        layerQualityAnalyzer.QualityParameter.ActualName = Problem.Evaluator.QualityParameter.ActualName;
596        layerQualityAnalyzer.QualityParameter.Hidden = true;
597        layerQualityAnalyzer.BestKnownQualityParameter.ActualName = Problem.BestKnownQualityParameter.Name;
598        layerQualityAnalyzer.BestKnownQualityParameter.Hidden = true;
599      }
600    }
601    private void ParameterizeSelectors() {
602      foreach (var selector in SelectorParameter.ValidValues) {
603        selector.CopySelected = new BoolValue(true);
604        selector.NumberOfSelectedSubScopesParameter.Hidden = true;
605        ParameterizeStochasticOperatorForLayer(selector);
606      }
607      if (Problem != null) {
608        foreach (var selector in SelectorParameter.ValidValues.OfType<ISingleObjectiveSelector>()) {
609          selector.MaximizationParameter.ActualName = Problem.MaximizationParameter.Name;
610          selector.MaximizationParameter.Hidden = true;
611          selector.QualityParameter.ActualName = Problem.Evaluator.QualityParameter.ActualName;
612          selector.QualityParameter.Hidden = true;
613        }
614      }
615    }
616    private void ParameterizeTerminators() {
617      qualityTerminator.Parameterize(qualityAnalyzer.CurrentBestQualityParameter, Problem);
618    }
619    private void ParameterizeIterationBasedOperators() {
620      if (Problem != null) {
621        foreach (var @operator in Problem.Operators.OfType<IIterationBasedOperator>()) {
622          @operator.IterationsParameter.ActualName = "Generations";
623          @operator.IterationsParameter.Hidden = true;
624          @operator.MaximumIterationsParameter.ActualName = generationsTerminator.ThresholdParameter.Name;
625          @operator.MaximumIterationsParameter.Hidden = true;
626        }
627      }
628    }
629    private void ParameterizeAgeLimits() {
630      var scheme = AgingScheme.Value;
631      int ageGap = AgeGap.Value;
632      int numberOfLayers = NumberOfLayers.Value;
633      AgeLimits = scheme.CalculateAgeLimits(ageGap, numberOfLayers);
634    }
635
636    private void ParameterizeStochasticOperator(IOperator @operator) {
637      var stochasticOperator = @operator as IStochasticOperator;
638      if (stochasticOperator != null) {
639        stochasticOperator.RandomParameter.ActualName = "GlobalRandom";
640        stochasticOperator.RandomParameter.Hidden = true;
641      }
642    }
643
644    private void ParameterizeStochasticOperatorForLayer(IOperator @operator) {
645      var stochasticOperator = @operator as IStochasticOperator;
646      if (stochasticOperator != null) {
647        stochasticOperator.RandomParameter.ActualName = "LocalRandom";
648        stochasticOperator.RandomParameter.Hidden = true;
649      }
650    }
651
652    #endregion
653
654    #region Updates
655    private void UpdateAnalyzers() {
656      Analyzer.Operators.Clear();
657      LayerAnalyzer.Operators.Clear();
658
659      Analyzer.Operators.Add(qualityAnalyzer, qualityAnalyzer.EnabledByDefault);
660      Analyzer.Operators.Add(ageAnalyzer, ageAnalyzer.EnabledByDefault);
661      Analyzer.Operators.Add(ageDistributionAnalyzer, ageDistributionAnalyzer.EnabledByDefault);
662      LayerAnalyzer.Operators.Add(layerQualityAnalyzer, false);
663      LayerAnalyzer.Operators.Add(layerAgeAnalyzer, false);
664      LayerAnalyzer.Operators.Add(layerAgeDistributionAnalyzer, false);
665
666      if (Problem != null) {
667        foreach (var analyzer in Problem.Operators.OfType<IAnalyzer>()) {
668          Analyzer.Operators.Add(analyzer, analyzer.EnabledByDefault);
669          LayerAnalyzer.Operators.Add((IAnalyzer)analyzer.Clone(), false);
670        }
671      }
672    }
673    private void UpdateCrossovers() {
674      var oldCrossover = CrossoverParameter.Value;
675      var defaultCrossover = Problem.Operators.OfType<ICrossover>().FirstOrDefault();
676      CrossoverParameter.ValidValues.Clear();
677      foreach (var crossover in Problem.Operators.OfType<ICrossover>().OrderBy(c => c.Name)) {
678        ParameterizeStochasticOperatorForLayer(crossover);
679        CrossoverParameter.ValidValues.Add(crossover);
680      }
681      if (oldCrossover != null) {
682        var crossover = CrossoverParameter.ValidValues.FirstOrDefault(c => c.GetType() == oldCrossover.GetType());
683        if (crossover != null)
684          CrossoverParameter.Value = crossover;
685        else
686          oldCrossover = null;
687      }
688      if (oldCrossover == null && defaultCrossover != null)
689        CrossoverParameter.Value = defaultCrossover;
690    }
691    private void UpdateMutators() {
692      var oldMutator = MutatorParameter.Value;
693      MutatorParameter.ValidValues.Clear();
694      foreach (var mutator in Problem.Operators.OfType<IManipulator>().OrderBy(m => m.Name)) {
695        ParameterizeStochasticOperatorForLayer(mutator);
696        MutatorParameter.ValidValues.Add(mutator);
697      }
698      if (oldMutator != null) {
699        var mutator = MutatorParameter.ValidValues.FirstOrDefault(m => m.GetType() == oldMutator.GetType());
700        if (mutator != null)
701          MutatorParameter.Value = mutator;
702      }
703    }
704    private void UpdateTerminators() {
705      var newTerminators = new Dictionary<ITerminator, bool> {
706        {generationsTerminator, !Terminators.Operators.Contains(generationsTerminator) || Terminators.Operators.ItemChecked(generationsTerminator)},
707        {evaluationsTerminator, Terminators.Operators.Contains(evaluationsTerminator) && Terminators.Operators.ItemChecked(evaluationsTerminator)},
708        {qualityTerminator, Terminators.Operators.Contains(qualityTerminator) && Terminators.Operators.ItemChecked(qualityTerminator) },
709        {executionTimeTerminator, Terminators.Operators.Contains(executionTimeTerminator) && Terminators.Operators.ItemChecked(executionTimeTerminator)}
710      };
711      if (Problem != null) {
712        foreach (var terminator in Problem.Operators.OfType<ITerminator>())
713          newTerminators.Add(terminator, !Terminators.Operators.Contains(terminator) || Terminators.Operators.ItemChecked(terminator));
714      }
715
716      Terminators.Operators.Clear();
717
718      foreach (var newTerminator in newTerminators)
719        Terminators.Operators.Add(newTerminator.Key, newTerminator.Value);
720    }
721    #endregion
722  }
723}
Note: See TracBrowser for help on using the repository browser.