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source: branches/ALPS/HeuristicLab.Algorithms.ALPS/3.3/AlpsGeneticAlgorithm.cs @ 11580

Last change on this file since 11580 was 11580, checked in by pfleck, 10 years ago

#2269 Implemented AlpsGeneticAlgorithmMainLoop.

File size: 23.1 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;
34using HeuristicLab.Random;
35using HeuristicLab.Selection;
36
37namespace HeuristicLab.Algorithms.ALPS {
38  [Item("ALPS Genetic Algorithm", "A genetic algorithm with an age-layered population structure.")]
39  [Creatable("Algorithms")]
40  [StorableClass]
41  public class AlpsGeneticAlgorithm : HeuristicOptimizationEngineAlgorithm, IStorableContent {
42    public string Filename { get; set; }
43
44    #region Problem Properties
45    public override Type ProblemType {
46      get { return typeof(ISingleObjectiveHeuristicOptimizationProblem); }
47    }
48    public new ISingleObjectiveHeuristicOptimizationProblem Problem {
49      get { return (ISingleObjectiveHeuristicOptimizationProblem)base.Problem; }
50      set { base.Problem = value; }
51    }
52    #endregion
53
54    #region Parameter Properties
55    private IValueParameter<IntValue> SeedParameter {
56      get { return (IValueParameter<IntValue>)Parameters["Seed"]; }
57    }
58    private IValueParameter<BoolValue> SetSeedRandomlyParameter {
59      get { return (IValueParameter<BoolValue>)Parameters["SetSeedRandomly"]; }
60    }
61    private IValueParameter<MultiAnalyzer> AnalyzerParameter {
62      get { return (IValueParameter<MultiAnalyzer>)Parameters["Analyzer"]; }
63    }
64    private IValueParameter<MultiAnalyzer> LayerAnalyzerParameter {
65      get { return (IValueParameter<MultiAnalyzer>)Parameters["LayerAnalyzer"]; }
66    }
67    private IValueParameter<IntValue> NumberOfLayersParameter {
68      get { return (IValueParameter<IntValue>)Parameters["NumberOfLayers"]; }
69    }
70    private IValueParameter<IntValue> PopulationSizeParameter {
71      get { return (IValueParameter<IntValue>)Parameters["PopulationSize"]; }
72    }
73    private IValueParameter<IntValue> MaximumGenerationsParameter {
74      get { return (IValueParameter<IntValue>)Parameters["MaximumGenerations"]; }
75    }
76    private IValueParameter<AgingScheme> AgingSchemeParameter {
77      get { return (IValueParameter<AgingScheme>)Parameters["AgingScheme"]; }
78    }
79    private IValueParameter<IntValue> AgeGapParameter {
80      get { return (IValueParameter<IntValue>)Parameters["AgeGap"]; }
81    }
82    private IValueParameter<IntArray> AgeLimitsParameter {
83      get { return (IValueParameter<IntArray>)Parameters["AgeLimits"]; }
84    }
85    private IValueParameter<ReductionOperation> AgeInheritanceParameter {
86      get { return (IValueParameter<ReductionOperation>)Parameters["AgeInheritance"]; }
87    }
88    public IConstrainedValueParameter<ISelector> SelectorParameter {
89      get { return (IConstrainedValueParameter<ISelector>)Parameters["Selector"]; }
90    }
91    public IConstrainedValueParameter<ICrossover> CrossoverParameter {
92      get { return (IConstrainedValueParameter<ICrossover>)Parameters["Crossover"]; }
93    }
94    private IValueParameter<PercentValue> MutationProbabilityParameter {
95      get { return (IValueParameter<PercentValue>)Parameters["MutationProbability"]; }
96    }
97    public IConstrainedValueParameter<IManipulator> MutatorParameter {
98      get { return (IConstrainedValueParameter<IManipulator>)Parameters["Mutator"]; }
99    }
100    private IValueParameter<IntValue> ElitesParameter {
101      get { return (IValueParameter<IntValue>)Parameters["Elites"]; }
102    }
103    private IFixedValueParameter<BoolValue> ReevaluateElitesParameter {
104      get { return (IFixedValueParameter<BoolValue>)Parameters["ReevaluateElites"]; }
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 MultiAnalyzer Analyzer {
118      get { return AnalyzerParameter.Value; }
119      set { AnalyzerParameter.Value = value; }
120    }
121    public MultiAnalyzer LayerAnalyzer {
122      get { return LayerAnalyzerParameter.Value; }
123      set { LayerAnalyzerParameter.Value = value; }
124    }
125    public IntValue NumberOfLayers {
126      get { return NumberOfLayersParameter.Value; }
127      set { NumberOfLayersParameter.Value = value; }
128    }
129
130    public IntValue PopulationSize {
131      get { return PopulationSizeParameter.Value; }
132      set { PopulationSizeParameter.Value = value; }
133    }
134    public IntValue MaximumGenerations {
135      get { return MaximumGenerationsParameter.Value; }
136      set { MaximumGenerationsParameter.Value = value; }
137    }
138    public AgingScheme AgingScheme {
139      get { return AgingSchemeParameter.Value; }
140      set { AgingSchemeParameter.Value = value; }
141    }
142    public IntValue AgeGap {
143      get { return AgeGapParameter.Value; }
144      set { AgeGapParameter.Value = value; }
145    }
146    public IntArray AgeLimits {
147      get { return AgeLimitsParameter.Value; }
148      set { AgeLimitsParameter.Value = value; }
149    }
150    public ReductionOperation AgeInheritance {
151      get { return AgeInheritanceParameter.Value; }
152      set { AgeInheritanceParameter.Value = value; }
153    }
154    public ISelector Selector {
155      get { return SelectorParameter.Value; }
156      set { SelectorParameter.Value = value; }
157    }
158    public ICrossover Crossover {
159      get { return CrossoverParameter.Value; }
160      set { CrossoverParameter.Value = value; }
161    }
162    public PercentValue MutationProbability {
163      get { return MutationProbabilityParameter.Value; }
164      set { MutationProbabilityParameter.Value = value; }
165    }
166    public IManipulator Mutator {
167      get { return MutatorParameter.Value; }
168      set { MutatorParameter.Value = value; }
169    }
170    public IntValue Elites {
171      get { return ElitesParameter.Value; }
172      set { ElitesParameter.Value = value; }
173    }
174    public bool ReevaluteElites {
175      get { return ReevaluateElitesParameter.Value.Value; }
176      set { ReevaluateElitesParameter.Value.Value = value; }
177    }
178
179    private RandomCreator GlobalRandomCreator {
180      get { return (RandomCreator)OperatorGraph.InitialOperator; }
181    }
182    private SolutionsCreator SolutionsCreator {
183      get { return OperatorGraph.Iterate().OfType<SolutionsCreator>().First(); }
184    }
185
186    private AlpsGeneticAlgorithmMainLoop MainLoop {
187      get { return OperatorGraph.Iterate().OfType<AlpsGeneticAlgorithmMainLoop>().First(); }
188    }
189
190    [Storable]
191    private BestAverageWorstQualityAnalyzer qualityAnalyzer;
192    [Storable]
193    private BestAverageWorstQualityAnalyzer layerQualityAnalyzer;
194    #endregion
195
196    [StorableConstructor]
197    private AlpsGeneticAlgorithm(bool deserializing)
198      : base(deserializing) { }
199    private AlpsGeneticAlgorithm(AlpsGeneticAlgorithm original, Cloner cloner)
200      : base(original, cloner) {
201      qualityAnalyzer = cloner.Clone(original.qualityAnalyzer);
202      layerQualityAnalyzer = cloner.Clone(original.layerQualityAnalyzer);
203      Initialize();
204    }
205    public override IDeepCloneable Clone(Cloner cloner) {
206      return new AlpsGeneticAlgorithm(this, cloner);
207    }
208    public AlpsGeneticAlgorithm()
209      : base() {
210      Parameters.Add(new ValueParameter<IntValue>("Seed", "The random seed used to initialize the new pseudo random number generator.", new IntValue(0)));
211      Parameters.Add(new ValueParameter<BoolValue>("SetSeedRandomly", "True if the random seed should be set to a random value, otherwise false.", new BoolValue(true)));
212      Parameters.Add(new ValueParameter<MultiAnalyzer>("Analyzer", "The operator used to analyze the islands.", new MultiAnalyzer()));
213      Parameters.Add(new ValueParameter<MultiAnalyzer>("LayerAnalyzer", "The operator used to analyze each layer.", new MultiAnalyzer()));
214      Parameters.Add(new ValueParameter<IntValue>("NumberOfLayers", "The number of layers.", new IntValue(5)));
215      Parameters.Add(new ValueParameter<IntValue>("PopulationSize", "The size of the population of solutions each layer.", new IntValue(20)));
216      Parameters.Add(new ValueParameter<IntValue>("MaximumGenerations", "The maximum number of generations that should be processed.", new IntValue(1000)));
217      Parameters.Add(new ValueParameter<AgingScheme>("AgingScheme", "The aging scheme for setting the age-limits for the layers.", new AgingScheme(AgingSchemes.Polynomial)));
218      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(5)));
219      Parameters.Add(new ValueParameter<IntArray>("AgeLimits", new IntArray(new[] { 1, 20, 45, 80, 125 })) { Hidden = true });
220      Parameters.Add(new ValueParameter<ReductionOperation>("AgeInheritance", "The operator for determining the age of an offspring based the parents' age.", new ReductionOperation(ReductionOperations.Max)) { Hidden = true });
221      Parameters.Add(new ConstrainedValueParameter<ISelector>("Selector", "The operator used to select solutions for reproduction."));
222      Parameters.Add(new ConstrainedValueParameter<ICrossover>("Crossover", "The operator used to cross solutions."));
223      Parameters.Add(new ValueParameter<PercentValue>("MutationProbability", "The probability that the mutation operator is applied on a solution.", new PercentValue(0.05)));
224      Parameters.Add(new OptionalConstrainedValueParameter<IManipulator>("Mutator", "The operator used to mutate solutions."));
225      Parameters.Add(new ValueParameter<IntValue>("Elites", "The numer of elite solutions which are kept in each generation.", new IntValue(1)));
226      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 });
227
228      var globalRandomCreator = new RandomCreator();
229      var layer0Creator = new SubScopesCreator() { Name = "Create Layer Zero" };
230      var layer0Processor = new SubScopesProcessor();
231      var localRandomCreator = new LocalRandomCreator();
232      var layerSolutionsCreator = new SolutionsCreator();
233      var initializeAgeProcessor = new UniformSubScopesProcessor();
234      var initializeAge = new VariableCreator() { Name = "Initialize Age" };
235      var initializeLocalEvaluatedSolutions = new SubScopesCounter();
236      var initializeGlobalEvaluatedSolutions = new DataReducer() { Name = "Initialize EvaluatedSolutions" };
237      var resultsCollector = new ResultsCollector();
238      var mainLoop = new AlpsGeneticAlgorithmMainLoop();
239
240      OperatorGraph.InitialOperator = globalRandomCreator;
241
242      globalRandomCreator.RandomParameter.ActualName = "GlobalRandom";
243      globalRandomCreator.SeedParameter.Value = null;
244      globalRandomCreator.SetSeedRandomlyParameter.Value = null;
245      globalRandomCreator.Successor = layer0Creator;
246
247      layer0Creator.NumberOfSubScopesParameter.Value = new IntValue(1);
248      layer0Creator.Successor = layer0Processor;
249
250      layer0Processor.Operators.Add(localRandomCreator);
251      layer0Processor.Successor = initializeGlobalEvaluatedSolutions;
252
253      localRandomCreator.Successor = layerSolutionsCreator;
254
255      layerSolutionsCreator.NumberOfSolutionsParameter.ActualName = PopulationSizeParameter.Name;
256      layerSolutionsCreator.Successor = initializeAgeProcessor;
257
258      initializeAgeProcessor.Operator = initializeAge;
259      initializeAgeProcessor.Successor = initializeLocalEvaluatedSolutions;
260
261      initializeAge.CollectedValues.Add(new ValueParameter<IntValue>("Age", new IntValue(0)));
262      initializeAge.Successor = null;
263
264      initializeLocalEvaluatedSolutions.ValueParameter.ActualName = "EvaluatedSolutions";
265      initializeLocalEvaluatedSolutions.Successor = null;
266
267      initializeGlobalEvaluatedSolutions.ReductionOperation.Value.Value = ReductionOperations.Sum;
268      initializeGlobalEvaluatedSolutions.TargetOperation.Value.Value = ReductionOperations.Assign;
269      initializeGlobalEvaluatedSolutions.ParameterToReduce.ActualName = "EvaluatedSolutions";
270      initializeGlobalEvaluatedSolutions.TargetParameter.ActualName = "EvaluatedSolutions";
271      initializeGlobalEvaluatedSolutions.Successor = resultsCollector;
272
273      resultsCollector.CollectedValues.Add(new LookupParameter<IntValue>("EvaluatedSolutions"));
274      resultsCollector.Successor = mainLoop;
275
276      foreach (var selector in ApplicationManager.Manager.GetInstances<ISelector>().Where(s => !(s is IMultiObjectiveSelector)).OrderBy(s => Name))
277        SelectorParameter.ValidValues.Add(selector);
278      var porportionalSelector = SelectorParameter.ValidValues.FirstOrDefault(s => s is ProportionalSelector);
279      if (porportionalSelector != null) SelectorParameter.Value = porportionalSelector;
280
281      ParameterizeSelectors();
282
283      qualityAnalyzer = new BestAverageWorstQualityAnalyzer();
284      layerQualityAnalyzer = new BestAverageWorstQualityAnalyzer();
285      ParameterizeAnalyzers();
286      UpdateAnalyzers();
287
288      Initialize();
289    }
290
291    public override void Prepare() {
292      if (Problem != null)
293        base.Prepare();
294    }
295
296    #region Events
297    protected override void OnProblemChanged() {
298      ParameterizeStochasticOperator(Problem.SolutionCreator);
299      ParameterizeStochasticOperatorForLayer(Problem.Evaluator);
300      foreach (var @operator in Problem.Operators.OfType<IOperator>())
301        ParameterizeStochasticOperator(@operator);
302      ParameterizeSolutionsCreator();
303      ParameterizeMainLoop();
304      ParameterizeSelectors();
305      ParameterizeAnalyzers();
306      ParameterizeIterationBasedOperators();
307      UpdateCrossovers();
308      UpdateMutators();
309      UpdateAnalyzers();
310      Problem.Evaluator.QualityParameter.ActualNameChanged += Evaluator_QualityParameter_ActualNameChanged;
311      base.OnProblemChanged();
312    }
313
314    protected override void Problem_SolutionCreatorChanged(object sender, EventArgs e) {
315      ParameterizeStochasticOperator(Problem.SolutionCreator);
316      ParameterizeSolutionsCreator();
317      base.Problem_SolutionCreatorChanged(sender, e);
318    }
319    protected override void Problem_EvaluatorChanged(object sender, EventArgs e) {
320      ParameterizeStochasticOperatorForLayer(Problem.Evaluator);
321      ParameterizeSolutionsCreator();
322      ParameterizeMainLoop();
323      ParameterizeSelectors();
324      ParameterizeAnalyzers();
325      Problem.Evaluator.QualityParameter.ActualNameChanged += Evaluator_QualityParameter_ActualNameChanged;
326      base.Problem_EvaluatorChanged(sender, e);
327    }
328    protected override void Problem_OperatorsChanged(object sender, EventArgs e) {
329      foreach (var @operator in Problem.Operators.OfType<IOperator>())
330        ParameterizeStochasticOperator(@operator);
331      ParameterizeIterationBasedOperators();
332      UpdateCrossovers();
333      UpdateMutators();
334      UpdateAnalyzers();
335      base.Problem_OperatorsChanged(sender, e);
336    }
337    private void Evaluator_QualityParameter_ActualNameChanged(object sender, EventArgs e) {
338      ParameterizeMainLoop();
339      ParameterizeSelectors();
340      ParameterizeAnalyzers();
341    }
342
343    void PopulationSizeParameter_ValueChanged(object sender, EventArgs e) {
344      PopulationSizeParameter.ValueChanged += PopulationSize_ValueChanged;
345      ParameterizeSelectors();
346    }
347    void PopulationSize_ValueChanged(object sender, EventArgs e) {
348      ParameterizeSelectors();
349    }
350    void ElitesParameter_ValueChanged(object sender, EventArgs e) {
351      Elites.ValueChanged += ElitesParameter_ValueChanged;
352      ParameterizeSelectors();
353    }
354    void Elites_ValueChanged(object sender, EventArgs e) {
355      ParameterizeSelectors();
356    }
357    #endregion
358
359    #region Parameterization
360    private void Initialize() {
361      PopulationSizeParameter.ValueChanged += PopulationSizeParameter_ValueChanged;
362      PopulationSize.ValueChanged += PopulationSize_ValueChanged;
363      ElitesParameter.ValueChanged += ElitesParameter_ValueChanged;
364      Elites.ValueChanged += Elites_ValueChanged;
365      if (Problem != null)
366        Problem.Evaluator.QualityParameter.ActualNameChanged += Evaluator_QualityParameter_ActualNameChanged;
367    }
368    private void ParameterizeSolutionsCreator() {
369      SolutionsCreator.EvaluatorParameter.ActualName = Problem.EvaluatorParameter.Name;
370      SolutionsCreator.SolutionCreatorParameter.ActualName = Problem.SolutionCreatorParameter.Name;
371    }
372    private void ParameterizeMainLoop() {
373      MainLoop.BestKnownQualityParameter.ActualName = Problem.BestKnownQualityParameter.Name;
374      MainLoop.EvaluatorParameter.ActualName = Problem.EvaluatorParameter.Name;
375      MainLoop.MaximizationParameter.ActualName = Problem.MaximizationParameter.Name;
376      MainLoop.BestKnownQualityParameter.ActualName = Problem.Evaluator.QualityParameter.ActualName;
377    }
378    private void ParameterizeSelectors() {
379      foreach (var selector in SelectorParameter.ValidValues) {
380        selector.CopySelected = new BoolValue(true);
381        selector.NumberOfSelectedSubScopesParameter.Value = new IntValue(2 * (PopulationSize.Value - Elites.Value));
382        selector.NumberOfSelectedSubScopesParameter.Hidden = true;
383        ParameterizeStochasticOperatorForLayer(selector);
384      }
385      if (Problem != null) {
386        foreach (var selector in SelectorParameter.ValidValues.OfType<ISingleObjectiveSelector>()) {
387          selector.MaximizationParameter.ActualName = Problem.MaximizationParameter.Name;
388          selector.MaximizationParameter.Hidden = true;
389          selector.QualityParameter.ActualName = Problem.Evaluator.QualityParameter.ActualName;
390          selector.QualityParameter.Hidden = true;
391        }
392      }
393    }
394    private void ParameterizeAnalyzers() {
395      qualityAnalyzer.ResultsParameter.ActualName = "Results";
396      qualityAnalyzer.ResultsParameter.Hidden = true;
397      qualityAnalyzer.QualityParameter.Depth = 2;
398      layerQualityAnalyzer.ResultsParameter.ActualName = "Results";
399      layerQualityAnalyzer.ResultsParameter.Hidden = true;
400      layerQualityAnalyzer.QualityParameter.Depth = 1;
401      if (Problem != null) {
402        qualityAnalyzer.MaximizationParameter.ActualName = Problem.MaximizationParameter.Name;
403        qualityAnalyzer.MaximizationParameter.Hidden = true;
404        qualityAnalyzer.QualityParameter.ActualName = Problem.Evaluator.QualityParameter.ActualName;
405        qualityAnalyzer.QualityParameter.Hidden = true;
406        qualityAnalyzer.BestKnownQualityParameter.ActualName = Problem.BestKnownQualityParameter.Name;
407        qualityAnalyzer.BestKnownQualityParameter.Hidden = true;
408        layerQualityAnalyzer.MaximizationParameter.ActualName = Problem.MaximizationParameter.Name;
409        layerQualityAnalyzer.MaximizationParameter.Hidden = true;
410        layerQualityAnalyzer.QualityParameter.ActualName = Problem.Evaluator.QualityParameter.ActualName;
411        layerQualityAnalyzer.QualityParameter.Hidden = true;
412        layerQualityAnalyzer.BestKnownQualityParameter.ActualName = Problem.BestKnownQualityParameter.Name;
413        layerQualityAnalyzer.BestKnownQualityParameter.Hidden = true;
414      }
415    }
416    private void ParameterizeIterationBasedOperators() {
417      if (Problem != null) {
418        foreach (var @operator in Problem.Operators.OfType<IIterationBasedOperator>()) {
419          @operator.IterationsParameter.ActualName = "Generations";
420          @operator.IterationsParameter.Hidden = true;
421          @operator.MaximumIterationsParameter.ActualName = "MaximumGenerations";
422          @operator.MaximumIterationsParameter.Hidden = true;
423        }
424      }
425    }
426    private void ParameterizeStochasticOperator(IOperator @operator) {
427      var stochasticOperator = @operator as IStochasticOperator;
428      if (stochasticOperator != null) {
429        stochasticOperator.RandomParameter.ActualName = GlobalRandomCreator.RandomParameter.ActualName;
430        stochasticOperator.RandomParameter.Hidden = true;
431      }
432    }
433    private void ParameterizeStochasticOperatorForLayer(IOperator @operator) {
434      var stochasticOperator = @operator as IStochasticOperator;
435      if (stochasticOperator != null) {
436        stochasticOperator.RandomParameter.ActualName = "LocalRandom";
437        stochasticOperator.RandomParameter.Hidden = true;
438      }
439    }
440
441    #endregion
442
443    #region Updates
444    private void UpdateCrossovers() {
445      var oldCrossover = CrossoverParameter.Value;
446      var defaultCrossover = Problem.Operators.OfType<ICrossover>().FirstOrDefault();
447      CrossoverParameter.ValidValues.Clear();
448      foreach (var crossover in Problem.Operators.OfType<ICrossover>().OrderBy(c => c.Name)) {
449        ParameterizeStochasticOperatorForLayer(crossover);
450        CrossoverParameter.ValidValues.Add(crossover);
451      }
452      if (oldCrossover != null) {
453        var crossover = CrossoverParameter.ValidValues.FirstOrDefault(c => c.GetType() == oldCrossover.GetType());
454        CrossoverParameter.Value = crossover;
455      }
456      if (oldCrossover == null && defaultCrossover != null)
457        CrossoverParameter.Value = defaultCrossover;
458    }
459    private void UpdateMutators() {
460      var oldMutator = MutatorParameter.Value;
461      MutatorParameter.ValidValues.Clear();
462      foreach (var mutator in Problem.Operators.OfType<IManipulator>().OrderBy(m => m.Name)) {
463        ParameterizeStochasticOperatorForLayer(mutator);
464        MutatorParameter.ValidValues.Add(mutator);
465      }
466      if (oldMutator != null) {
467        var mutator = MutatorParameter.ValidValues.FirstOrDefault(m => m.GetType() == oldMutator.GetType());
468        MutatorParameter.Value = mutator;
469      }
470    }
471    private void UpdateAnalyzers() {
472      Analyzer.Operators.Clear();
473      LayerAnalyzer.Operators.Clear();
474
475      Analyzer.Operators.Add(qualityAnalyzer, qualityAnalyzer.EnabledByDefault);
476      LayerAnalyzer.Operators.Add(layerQualityAnalyzer, layerQualityAnalyzer.EnabledByDefault);
477
478      if (Problem != null) {
479        foreach (var analyzer in Problem.Operators.OfType<IAnalyzer>()) {
480          foreach (var parameter in analyzer.Parameters.OfType<IScopeTreeLookupParameter>())
481            parameter.Depth = 2;
482          Analyzer.Operators.Add(analyzer, analyzer.EnabledByDefault);
483        }
484      }
485    }
486    #endregion
487  }
488}
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