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source: branches/PersistenceOverhaul/HeuristicLab.Algorithms.RAPGA/3.3/RAPGAMainLoop.cs @ 14113

Last change on this file since 14113 was 13368, checked in by ascheibe, 9 years ago

#2520 added guids to storable classes
File size: 24.1 KB
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[13368]1#region License Information
[8313]2/* HeuristicLab
[12012]3 * Copyright (C) 2002-2015 Heuristic and Evolutionary Algorithms Laboratory (HEAL)
[8313]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 HeuristicLab.Common;
23using HeuristicLab.Core;
24using HeuristicLab.Data;
25using HeuristicLab.Operators;
[8379]26using HeuristicLab.Optimization;
[8313]27using HeuristicLab.Optimization.Operators;
28using HeuristicLab.Parameters;
29using HeuristicLab.Persistence.Default.CompositeSerializers.Storable;
30using HeuristicLab.Selection;
31
32namespace HeuristicLab.Algorithms.RAPGA {
33  /// <summary>
34  /// An operator which represents the main loop of a relevant alleles preserving genetic algorithm.
35  /// </summary>
36  [Item("RAPGAMainLoop", "An operator which represents the main loop of a relevant alleles preserving genetic algorithm.")]
[13368]37  [StorableClass("4F237A68-FCA8-4BBB-9095-F51595C57CB9")]
[8313]38  public sealed class RAPGAMainLoop : AlgorithmOperator {
39    #region Parameter properties
40    public ValueLookupParameter<IRandom> RandomParameter {
41      get { return (ValueLookupParameter<IRandom>)Parameters["Random"]; }
42    }
43    public ValueLookupParameter<BoolValue> MaximizationParameter {
44      get { return (ValueLookupParameter<BoolValue>)Parameters["Maximization"]; }
45    }
46    public ScopeTreeLookupParameter<DoubleValue> QualityParameter {
47      get { return (ScopeTreeLookupParameter<DoubleValue>)Parameters["Quality"]; }
48    }
49    public ValueLookupParameter<IOperator> SelectorParameter {
50      get { return (ValueLookupParameter<IOperator>)Parameters["Selector"]; }
51    }
52    public ValueLookupParameter<IOperator> CrossoverParameter {
53      get { return (ValueLookupParameter<IOperator>)Parameters["Crossover"]; }
54    }
55    public ValueLookupParameter<PercentValue> MutationProbabilityParameter {
56      get { return (ValueLookupParameter<PercentValue>)Parameters["MutationProbability"]; }
57    }
58    public ValueLookupParameter<IOperator> MutatorParameter {
59      get { return (ValueLookupParameter<IOperator>)Parameters["Mutator"]; }
60    }
61    public ValueLookupParameter<IOperator> EvaluatorParameter {
62      get { return (ValueLookupParameter<IOperator>)Parameters["Evaluator"]; }
63    }
64    public ValueLookupParameter<IntValue> ElitesParameter {
65      get { return (ValueLookupParameter<IntValue>)Parameters["Elites"]; }
66    }
[9569]67    public IValueLookupParameter<BoolValue> ReevaluateElitesParameter {
68      get { return (IValueLookupParameter<BoolValue>)Parameters["ReevaluateElites"]; }
69    }
[8313]70    public ValueLookupParameter<IntValue> MaximumGenerationsParameter {
71      get { return (ValueLookupParameter<IntValue>)Parameters["MaximumGenerations"]; }
72    }
73    public ValueLookupParameter<VariableCollection> ResultsParameter {
74      get { return (ValueLookupParameter<VariableCollection>)Parameters["Results"]; }
75    }
76    public ValueLookupParameter<IOperator> AnalyzerParameter {
77      get { return (ValueLookupParameter<IOperator>)Parameters["Analyzer"]; }
78    }
79    public ValueLookupParameter<IntValue> EvaluatedSolutionsParameter {
80      get { return (ValueLookupParameter<IntValue>)Parameters["EvaluatedSolutions"]; }
81    }
82    public ValueLookupParameter<IntValue> PopulationSizeParameter {
83      get { return (ValueLookupParameter<IntValue>)Parameters["PopulationSize"]; }
84    }
[8330]85    public IValueLookupParameter<IntValue> MinimumPopulationSizeParameter {
86      get { return (IValueLookupParameter<IntValue>)Parameters["MinimumPopulationSize"]; }
87    }
88    public IValueLookupParameter<IntValue> MaximumPopulationSizeParameter {
89      get { return (IValueLookupParameter<IntValue>)Parameters["MaximumPopulationSize"]; }
90    }
91    public IValueLookupParameter<DoubleValue> ComparisonFactorParameter {
92      get { return (IValueLookupParameter<DoubleValue>)Parameters["ComparisonFactor"]; }
93    }
94    public IValueLookupParameter<IntValue> EffortParameter {
95      get { return (IValueLookupParameter<IntValue>)Parameters["Effort"]; }
96    }
[8379]97    public IValueLookupParameter<IntValue> BatchSizeParameter {
98      get { return (IValueLookupParameter<IntValue>)Parameters["BatchSize"]; }
99    }
100    public IValueLookupParameter<ISolutionSimilarityCalculator> SimilarityCalculatorParameter {
101      get { return (IValueLookupParameter<ISolutionSimilarityCalculator>)Parameters["SimilarityCalculator"]; }
102    }
[8313]103    private ScopeParameter CurrentScopeParameter {
104      get { return (ScopeParameter)Parameters["CurrentScope"]; }
105    }
106
107    public IScope CurrentScope {
108      get { return CurrentScopeParameter.ActualValue; }
109    }
110    #endregion
111
112    [StorableConstructor]
113    private RAPGAMainLoop(bool deserializing) : base(deserializing) { }
114    private RAPGAMainLoop(RAPGAMainLoop original, Cloner cloner) : base(original, cloner) { }
115    public RAPGAMainLoop()
116      : base() {
117      Initialize();
118    }
119    public override IDeepCloneable Clone(Cloner cloner) {
120      return new RAPGAMainLoop(this, cloner);
121    }
122
[9591]123    [StorableHook(HookType.AfterDeserialization)]
124    private void AfterDeserialization() {
[9592]125      // BackwardsCompatibility3.3
[9591]126      #region Backwards compatible code, remove with 3.4
127      if (!Parameters.ContainsKey("ReevaluateElites")) {
128        Parameters.Add(new ValueLookupParameter<BoolValue>("ReevaluateElites", "Flag to determine if elite individuals should be reevaluated (i.e., if stochastic fitness functions are used.)"));
129      }
130      #endregion
131    }
132
[8313]133    private void Initialize() {
134      #region Create parameters
135      Parameters.Add(new ValueLookupParameter<IRandom>("Random", "A pseudo random number generator."));
136      Parameters.Add(new ValueLookupParameter<BoolValue>("Maximization", "True if the problem is a maximization problem, otherwise false."));
137      Parameters.Add(new ScopeTreeLookupParameter<DoubleValue>("Quality", "The value which represents the quality of a solution."));
138      Parameters.Add(new ValueLookupParameter<IOperator>("Selector", "The operator used to select solutions for reproduction."));
139      Parameters.Add(new ValueLookupParameter<IOperator>("Crossover", "The operator used to cross solutions."));
140      Parameters.Add(new ValueLookupParameter<PercentValue>("MutationProbability", "The probability that the mutation operator is applied on a solution."));
141      Parameters.Add(new ValueLookupParameter<IOperator>("Mutator", "The operator used to mutate solutions."));
142      Parameters.Add(new ValueLookupParameter<IOperator>("Evaluator", "The operator used to evaluate solutions. This operator is executed in parallel, if an engine is used which supports parallelization."));
143      Parameters.Add(new ValueLookupParameter<IntValue>("Elites", "The numer of elite solutions which are kept in each generation."));
[9569]144      Parameters.Add(new ValueLookupParameter<BoolValue>("ReevaluateElites", "Flag to determine if elite individuals should be reevaluated (i.e., if stochastic fitness functions are used.)"));
[8313]145      Parameters.Add(new ValueLookupParameter<IntValue>("MaximumGenerations", "The maximum number of generations which should be processed."));
146      Parameters.Add(new ValueLookupParameter<VariableCollection>("Results", "The variable collection where results should be stored."));
147      Parameters.Add(new ValueLookupParameter<IOperator>("Analyzer", "The operator used to analyze each generation."));
148      Parameters.Add(new ValueLookupParameter<IntValue>("EvaluatedSolutions", "The number of times solutions have been evaluated."));
149      Parameters.Add(new ValueLookupParameter<IntValue>("PopulationSize", "The size of the population."));
[8330]150      Parameters.Add(new ValueLookupParameter<IntValue>("MinimumPopulationSize", "The minimum size of the population of solutions."));
151      Parameters.Add(new ValueLookupParameter<IntValue>("MaximumPopulationSize", "The maximum size of the population of solutions."));
152      Parameters.Add(new ValueLookupParameter<DoubleValue>("ComparisonFactor", "The comparison factor."));
153      Parameters.Add(new ValueLookupParameter<IntValue>("Effort", "The maximum number of offspring created in each generation."));
[8400]154      Parameters.Add(new ValueLookupParameter<IntValue>("BatchSize", "The number of children that should be created during one iteration of the offspring creation process."));
[8379]155      Parameters.Add(new ValueLookupParameter<ISolutionSimilarityCalculator>("SimilarityCalculator", "The operator used to calculate the similarity between two solutions."));
[8313]156      Parameters.Add(new ScopeParameter("CurrentScope", "The current scope which represents a population of solutions on which the genetic algorithm should be applied."));
157      #endregion
158
159      #region Create operators
160      VariableCreator variableCreator = new VariableCreator();
[8377]161      Assigner assigner1 = new Assigner();
[8359]162      ResultsCollector resultsCollector = new ResultsCollector();
[8313]163      Placeholder analyzer1 = new Placeholder();
164      Placeholder selector = new Placeholder();
165      SubScopesProcessor subScopesProcessor1 = new SubScopesProcessor();
166      ChildrenCreator childrenCreator = new ChildrenCreator();
[8377]167      UniformSubScopesProcessor uniformSubScopesProcessor = new UniformSubScopesProcessor();
[8313]168      Placeholder crossover = new Placeholder();
169      StochasticBranch stochasticBranch = new StochasticBranch();
170      Placeholder mutator = new Placeholder();
171      Placeholder evaluator = new Placeholder();
[8377]172      WeightedParentsQualityComparator weightedParentsQualityComparator = new WeightedParentsQualityComparator();
173      SubScopesRemover subScopesRemover = new SubScopesRemover();
174      IntCounter intCounter1 = new IntCounter();
[8385]175      IntCounter intCounter2 = new IntCounter();
[8330]176      ConditionalSelector conditionalSelector = new ConditionalSelector();
177      RightReducer rightReducer1 = new RightReducer();
[8377]178      DuplicatesSelector duplicateSelector = new DuplicatesSelector();
179      LeftReducer leftReducer1 = new LeftReducer();
180      ProgressiveOffspringPreserver progressiveOffspringSelector = new ProgressiveOffspringPreserver();
[8359]181      SubScopesCounter subScopesCounter2 = new SubScopesCounter();
[8642]182      ExpressionCalculator calculator1 = new ExpressionCalculator();
[8622]183      ConditionalBranch conditionalBranch1 = new ConditionalBranch();
[8377]184      Comparator comparator1 = new Comparator();
185      ConditionalBranch conditionalBranch2 = new ConditionalBranch();
186      LeftReducer leftReducer2 = new LeftReducer();
187      SubScopesProcessor subScopesProcessor2 = new SubScopesProcessor();
188      BestSelector bestSelector = new BestSelector();
[8330]189      RightReducer rightReducer2 = new RightReducer();
[8377]190      ScopeCleaner scopeCleaner = new ScopeCleaner();
[8622]191      ScopeRestorer scopeRestorer = new ScopeRestorer();
[8313]192      MergingReducer mergingReducer = new MergingReducer();
[8385]193      IntCounter intCounter3 = new IntCounter();
[8377]194      SubScopesCounter subScopesCounter3 = new SubScopesCounter();
[8642]195      ExpressionCalculator calculator2 = new ExpressionCalculator();
[8622]196      Comparator comparator2 = new Comparator();
197      ConditionalBranch conditionalBranch3 = new ConditionalBranch();
[8385]198      Placeholder analyzer2 = new Placeholder();
[8330]199      Comparator comparator3 = new Comparator();
[8622]200      ConditionalBranch conditionalBranch4 = new ConditionalBranch();
[8330]201      Comparator comparator4 = new Comparator();
[8622]202      ConditionalBranch conditionalBranch5 = new ConditionalBranch();
[8377]203      Assigner assigner3 = new Assigner();
204      Assigner assigner4 = new Assigner();
[8385]205      Assigner assigner5 = new Assigner();
[9569]206      ConditionalBranch reevaluateElitesBranch = new ConditionalBranch();
207      UniformSubScopesProcessor uniformSubScopesProcessor2 = new UniformSubScopesProcessor();
208      Placeholder evaluator2 = new Placeholder();
209      SubScopesCounter subScopesCounter4 = new SubScopesCounter();
[8313]210
[8359]211      variableCreator.CollectedValues.Add(new ValueParameter<IntValue>("Generations", new IntValue(0))); // Class RAPGA expects this to be called Generations
[8330]212      variableCreator.CollectedValues.Add(new ValueParameter<IntValue>("CurrentPopulationSize", new IntValue(0)));
[8377]213      variableCreator.CollectedValues.Add(new ValueParameter<IntValue>("NumberOfCreatedOffspring", new IntValue(0)));
214      variableCreator.CollectedValues.Add(new ValueParameter<IntValue>("NumberOfSuccessfulOffspring", new IntValue(0)));
215      variableCreator.CollectedValues.Add(new ValueParameter<ScopeList>("OffspringList", new ScopeList()));
[8313]216
[8377]217      assigner1.Name = "Initialize CurrentPopulationSize";
218      assigner1.LeftSideParameter.ActualName = "CurrentPopulationSize";
219      assigner1.RightSideParameter.ActualName = PopulationSizeParameter.Name;
[8330]220
[8359]221      resultsCollector.CollectedValues.Add(new LookupParameter<IntValue>("Generations"));
222      resultsCollector.CollectedValues.Add(new LookupParameter<IntValue>("CurrentPopulationSize"));
223      resultsCollector.ResultsParameter.ActualName = "Results";
[8313]224
225      analyzer1.Name = "Analyzer";
226      analyzer1.OperatorParameter.ActualName = "Analyzer";
227
228      selector.Name = "Selector";
229      selector.OperatorParameter.ActualName = "Selector";
230
231      childrenCreator.ParentsPerChild = new IntValue(2);
232
[8377]233      uniformSubScopesProcessor.Parallel.Value = true;
234
[8313]235      crossover.Name = "Crossover";
236      crossover.OperatorParameter.ActualName = "Crossover";
237
238      stochasticBranch.ProbabilityParameter.ActualName = "MutationProbability";
239      stochasticBranch.RandomParameter.ActualName = "Random";
240
241      mutator.Name = "Mutator";
242      mutator.OperatorParameter.ActualName = "Mutator";
243
244      evaluator.Name = "Evaluator";
245      evaluator.OperatorParameter.ActualName = "Evaluator";
246
[8377]247      weightedParentsQualityComparator.ComparisonFactorParameter.ActualName = ComparisonFactorParameter.Name;
248      weightedParentsQualityComparator.LeftSideParameter.ActualName = QualityParameter.Name;
249      weightedParentsQualityComparator.MaximizationParameter.ActualName = MaximizationParameter.Name;
250      weightedParentsQualityComparator.RightSideParameter.ActualName = QualityParameter.Name;
251      weightedParentsQualityComparator.ResultParameter.ActualName = "SuccessfulOffspring";
[8313]252
[8377]253      subScopesRemover.RemoveAllSubScopes = true;
[8359]254
[8385]255      intCounter1.Name = "Increment NumberOfCreatedOffspring";
256      intCounter1.ValueParameter.ActualName = "NumberOfCreatedOffspring";
[8377]257      intCounter1.Increment = null;
[8385]258      intCounter1.IncrementParameter.ActualName = BatchSizeParameter.Name;
[8377]259
[8385]260      intCounter2.Name = "Increment EvaluatedSolutions";
261      intCounter2.ValueParameter.ActualName = EvaluatedSolutionsParameter.Name;
262      intCounter2.Increment = null;
263      intCounter2.IncrementParameter.ActualName = BatchSizeParameter.Name;
264
[8330]265      conditionalSelector.ConditionParameter.ActualName = "SuccessfulOffspring";
266      conditionalSelector.ConditionParameter.Depth = 1;
267      conditionalSelector.CopySelected.Value = false;
[8313]268
[8349]269      duplicateSelector.CopySelected.Value = false;
270
[8377]271      progressiveOffspringSelector.OffspringListParameter.ActualName = "OffspringList";
272      progressiveOffspringSelector.ElitesParameter.ActualName = ElitesParameter.Name;
273      progressiveOffspringSelector.MaximumPopulationSizeParameter.ActualName = MaximumPopulationSizeParameter.Name;
[8349]274
[8359]275      subScopesCounter2.Name = "Count Successful Offspring";
276      subScopesCounter2.ValueParameter.ActualName = "NumberOfSuccessfulOffspring";
[8313]277
[8622]278      calculator1.Name = "NumberOfSuccessfulOffspring == MaximumPopulationSize - Elites";
279      calculator1.CollectedValues.Add(new ValueLookupParameter<IntValue>("NumberOfSuccessfulOffspring"));
280      calculator1.CollectedValues.Add(new ValueLookupParameter<IntValue>("MaximumPopulationSize"));
281      calculator1.CollectedValues.Add(new ValueLookupParameter<IntValue>("Elites"));
282      calculator1.ExpressionParameter.Value = new StringValue("NumberOfSuccessfulOffspring MaximumPopulationSize Elites - ==");
283      calculator1.ExpressionResultParameter.ActualName = "Break";
[8330]284
[8377]285      conditionalBranch1.Name = "Break?";
286      conditionalBranch1.ConditionParameter.ActualName = "Break";
[8330]287
[8622]288      comparator1.Name = "NumberOfCreatedOffspring >= Effort";
289      comparator1.Comparison = new Comparison(ComparisonType.GreaterOrEqual);
290      comparator1.LeftSideParameter.ActualName = "NumberOfCreatedOffspring";
291      comparator1.RightSideParameter.ActualName = EffortParameter.Name;
292      comparator1.ResultParameter.ActualName = "Break";
[8330]293
[8377]294      conditionalBranch2.Name = "Break?";
295      conditionalBranch2.ConditionParameter.ActualName = "Break";
[8330]296
[8377]297      bestSelector.CopySelected = new BoolValue(false);
298      bestSelector.MaximizationParameter.ActualName = MaximizationParameter.Name;
299      bestSelector.NumberOfSelectedSubScopesParameter.ActualName = "Elites";
300      bestSelector.QualityParameter.ActualName = QualityParameter.Name;
[8330]301
[8385]302      intCounter3.Name = "Increment Generations";
303      intCounter3.Increment = new IntValue(1);
304      intCounter3.ValueParameter.ActualName = "Generations";
305
306      subScopesCounter3.Name = "Update CurrentPopulationSize";
[8377]307      subScopesCounter3.ValueParameter.ActualName = "CurrentPopulationSize";
308      subScopesCounter3.AccumulateParameter.Value = new BoolValue(false);
309
[8622]310      calculator2.Name = "Evaluate ActualSelectionPressure";
311      calculator2.CollectedValues.Add(new ValueLookupParameter<IntValue>("NumberOfCreatedOffspring"));
312      calculator2.CollectedValues.Add(new ValueLookupParameter<IntValue>("Elites"));
313      calculator2.CollectedValues.Add(new ValueLookupParameter<IntValue>("CurrentPopulationSize"));
314      calculator2.ExpressionParameter.Value = new StringValue("NumberOfCreatedOffspring Elites + CurrentPopulationSize /");
315      calculator2.ExpressionResultParameter.ActualName = "ActualSelectionPressure";
[8385]316
[8622]317      comparator2.Name = "CurrentPopulationSize < 1";
318      comparator2.Comparison = new Comparison(ComparisonType.Less);
319      comparator2.LeftSideParameter.ActualName = "CurrentPopulationSize";
320      comparator2.RightSideParameter.Value = new IntValue(1);
321      comparator2.ResultParameter.ActualName = "Terminate";
322
323      conditionalBranch3.Name = "Terminate?";
324      conditionalBranch3.ConditionParameter.ActualName = "Terminate";
325
[8385]326      analyzer2.Name = "Analyzer";
327      analyzer2.OperatorParameter.ActualName = "Analyzer";
328
[8377]329      comparator3.Name = "Generations >= MaximumGenerations";
[8330]330      comparator3.Comparison = new Comparison(ComparisonType.GreaterOrEqual);
331      comparator3.LeftSideParameter.ActualName = "Generations";
332      comparator3.ResultParameter.ActualName = "Terminate";
333      comparator3.RightSideParameter.ActualName = MaximumGenerationsParameter.Name;
334
[8622]335      conditionalBranch4.Name = "Terminate?";
336      conditionalBranch4.ConditionParameter.ActualName = "Terminate";
[8330]337
[8377]338      comparator4.Name = "CurrentPopulationSize < MinimumPopulationSize";
[8330]339      comparator4.Comparison = new Comparison(ComparisonType.Less);
340      comparator4.LeftSideParameter.ActualName = "CurrentPopulationSize";
341      comparator4.RightSideParameter.ActualName = MinimumPopulationSizeParameter.Name;
342      comparator4.ResultParameter.ActualName = "Terminate";
343
[8622]344      conditionalBranch5.Name = "Terminate?";
345      conditionalBranch5.ConditionParameter.ActualName = "Terminate";
[8377]346
[8385]347      assigner3.Name = "Reset NumberOfCreatedOffspring";
348      assigner3.LeftSideParameter.ActualName = "NumberOfCreatedOffspring";
[8377]349      assigner3.RightSideParameter.Value = new IntValue(0);
350
[8385]351      assigner4.Name = "Reset NumberOfSuccessfulOffspring";
352      assigner4.LeftSideParameter.ActualName = "NumberOfSuccessfulOffspring";
353      assigner4.RightSideParameter.Value = new IntValue(0);
354
355      assigner5.Name = "Reset OffspringList";
356      assigner5.LeftSideParameter.ActualName = "OffspringList";
357      assigner5.RightSideParameter.Value = new ScopeList();
[9569]358
359      reevaluateElitesBranch.ConditionParameter.ActualName = "ReevaluateElites";
360      reevaluateElitesBranch.Name = "Reevaluate elites ?";
361
362      uniformSubScopesProcessor2.Parallel.Value = true;
363
364      evaluator2.Name = "Evaluator (placeholder)";
365      evaluator2.OperatorParameter.ActualName = EvaluatorParameter.Name;
366
367      subScopesCounter4.Name = "Increment EvaluatedSolutions";
368      subScopesCounter4.ValueParameter.ActualName = EvaluatedSolutionsParameter.Name;
[8313]369      #endregion
370
371      #region Create operator graph
372      OperatorGraph.InitialOperator = variableCreator;
[8377]373      variableCreator.Successor = assigner1;
374      assigner1.Successor = resultsCollector;
[8359]375      resultsCollector.Successor = analyzer1;
[8313]376      analyzer1.Successor = selector;
377      selector.Successor = subScopesProcessor1;
378      subScopesProcessor1.Operators.Add(new EmptyOperator());
379      subScopesProcessor1.Operators.Add(childrenCreator);
[8622]380      subScopesProcessor1.Successor = calculator1;
[8377]381      childrenCreator.Successor = uniformSubScopesProcessor;
382      uniformSubScopesProcessor.Operator = crossover;
[8385]383      uniformSubScopesProcessor.Successor = intCounter1;
[8313]384      crossover.Successor = stochasticBranch;
385      stochasticBranch.FirstBranch = mutator;
386      stochasticBranch.SecondBranch = null;
387      mutator.Successor = null;
[8377]388      stochasticBranch.Successor = evaluator;
389      evaluator.Successor = weightedParentsQualityComparator;
390      weightedParentsQualityComparator.Successor = subScopesRemover;
[8385]391      intCounter1.Successor = intCounter2;
392      intCounter2.Successor = conditionalSelector;
[8330]393      conditionalSelector.Successor = rightReducer1;
[8377]394      rightReducer1.Successor = duplicateSelector;
395      duplicateSelector.Successor = leftReducer1;
396      leftReducer1.Successor = progressiveOffspringSelector;
397      progressiveOffspringSelector.Successor = subScopesCounter2;
[8622]398      calculator1.Successor = conditionalBranch1;
399      conditionalBranch1.FalseBranch = comparator1;
[8377]400      conditionalBranch1.TrueBranch = subScopesProcessor2;
[8622]401      comparator1.Successor = conditionalBranch2;
[8377]402      conditionalBranch2.FalseBranch = leftReducer2;
403      conditionalBranch2.TrueBranch = subScopesProcessor2;
404      leftReducer2.Successor = selector;
405      subScopesProcessor2.Operators.Add(bestSelector);
406      subScopesProcessor2.Operators.Add(scopeCleaner);
[8313]407      subScopesProcessor2.Successor = mergingReducer;
[8377]408      bestSelector.Successor = rightReducer2;
[9569]409      rightReducer2.Successor = reevaluateElitesBranch;
410      reevaluateElitesBranch.TrueBranch = uniformSubScopesProcessor2;
411      uniformSubScopesProcessor2.Operator = evaluator2;
412      uniformSubScopesProcessor2.Successor = subScopesCounter4;
413      evaluator2.Successor = null;
414      subScopesCounter4.Successor = null;
415      reevaluateElitesBranch.FalseBranch = null;
416      reevaluateElitesBranch.Successor = null;
[8622]417      scopeCleaner.Successor = scopeRestorer;
418      mergingReducer.Successor = intCounter3;
[8385]419      intCounter3.Successor = subScopesCounter3;
[8622]420      subScopesCounter3.Successor = calculator2;
421      calculator2.Successor = comparator2;
422      comparator2.Successor = conditionalBranch3;
423      conditionalBranch3.FalseBranch = analyzer2;
424      conditionalBranch3.TrueBranch = null;
[8377]425      analyzer2.Successor = comparator3;
[8622]426      comparator3.Successor = conditionalBranch4;
427      conditionalBranch4.FalseBranch = comparator4;
[8377]428      conditionalBranch4.TrueBranch = null;
429      conditionalBranch4.Successor = null;
[8622]430      comparator4.Successor = conditionalBranch5;
431      conditionalBranch5.FalseBranch = assigner3;
432      conditionalBranch5.TrueBranch = null;
433      conditionalBranch5.Successor = null;
[8377]434      assigner3.Successor = assigner4;
[8385]435      assigner4.Successor = assigner5;
436      assigner5.Successor = selector;
[8377]437
[8313]438      #endregion
439    }
440
441    public override IOperation Apply() {
442      if (CrossoverParameter.ActualName == null)
443        return null;
444      return base.Apply();
445    }
446  }
447}
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