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source: stable/HeuristicLab.Algorithms.ALPS/3.3/AlpsOffspringSelectionGeneticAlgorithmMainLoop.cs @ 17456

Last change on this file since 17456 was 17181, checked in by swagner, 5 years ago

#2875: Merged r17180 from trunk to stable
File size: 28.8 KB
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1#region License Information
2/* HeuristicLab
3 * Copyright (C) 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 HeuristicLab.Common;
23using HeuristicLab.Core;
24using HeuristicLab.Data;
25using HeuristicLab.Operators;
26using HeuristicLab.Optimization;
27using HeuristicLab.Optimization.Operators;
28using HeuristicLab.Parameters;
29using HEAL.Attic;
30using HeuristicLab.Selection;
31
32namespace HeuristicLab.Algorithms.ALPS {
33
34  [Item("AlpsOffspringSelectionGeneticAlgorithmMainLoop", "An ALPS offspring selection genetic algorithm main loop operator.")]
35  [StorableType("C8DF9B75-7008-405D-B38A-15C1C22110B0")]
36  public sealed class AlpsOffspringSelectionGeneticAlgorithmMainLoop : AlgorithmOperator {
37    #region Parameter Properties
38    public IValueLookupParameter<IRandom> GlobalRandomParameter {
39      get { return (IValueLookupParameter<IRandom>)Parameters["GlobalRandom"]; }
40    }
41    public IValueLookupParameter<IRandom> LocalRandomParameter {
42      get { return (IValueLookupParameter<IRandom>)Parameters["LocalRandom"]; }
43    }
44
45    public IValueLookupParameter<IOperator> EvaluatorParameter {
46      get { return (IValueLookupParameter<IOperator>)Parameters["Evaluator"]; }
47    }
48    public IValueLookupParameter<IntValue> EvaluatedSolutionsParameter {
49      get { return (IValueLookupParameter<IntValue>)Parameters["EvaluatedSolutions"]; }
50    }
51    public IScopeTreeLookupParameter<DoubleValue> QualityParameter {
52      get { return (IScopeTreeLookupParameter<DoubleValue>)Parameters["Quality"]; }
53    }
54    public IValueLookupParameter<BoolValue> MaximizationParameter {
55      get { return (IValueLookupParameter<BoolValue>)Parameters["Maximization"]; }
56    }
57
58    public ILookupParameter<IOperator> AnalyzerParameter {
59      get { return (ILookupParameter<IOperator>)Parameters["Analyzer"]; }
60    }
61    public ILookupParameter<IOperator> LayerAnalyzerParameter {
62      get { return (ILookupParameter<IOperator>)Parameters["LayerAnalyzer"]; }
63    }
64
65    public IValueLookupParameter<IntValue> NumberOfLayersParameter {
66      get { return (IValueLookupParameter<IntValue>)Parameters["NumberOfLayers"]; }
67    }
68    public IValueLookupParameter<IntValue> PopulationSizeParameter {
69      get { return (IValueLookupParameter<IntValue>)Parameters["PopulationSize"]; }
70    }
71    public ILookupParameter<IntValue> CurrentPopulationSizeParameter {
72      get { return (ILookupParameter<IntValue>)Parameters["CurrentPopulationSize"]; }
73    }
74
75    public IValueLookupParameter<IOperator> SelectorParameter {
76      get { return (IValueLookupParameter<IOperator>)Parameters["Selector"]; }
77    }
78    public IValueLookupParameter<IOperator> CrossoverParameter {
79      get { return (IValueLookupParameter<IOperator>)Parameters["Crossover"]; }
80    }
81    public IValueLookupParameter<IOperator> MutatorParameter {
82      get { return (IValueLookupParameter<IOperator>)Parameters["Mutator"]; }
83    }
84    public IValueLookupParameter<PercentValue> MutationProbabilityParameter {
85      get { return (IValueLookupParameter<PercentValue>)Parameters["MutationProbability"]; }
86    }
87    public IValueLookupParameter<IntValue> ElitesParameter {
88      get { return (IValueLookupParameter<IntValue>)Parameters["Elites"]; }
89    }
90    public IValueLookupParameter<BoolValue> ReevaluateElitesParameter {
91      get { return (IValueLookupParameter<BoolValue>)Parameters["ReevaluateElites"]; }
92    }
93
94    public IValueLookupParameter<DoubleValue> SuccessRatioParameter {
95      get { return (IValueLookupParameter<DoubleValue>)Parameters["SuccessRatio"]; }
96    }
97    public ILookupParameter<DoubleValue> ComparisonFactorParameter {
98      get { return (ILookupParameter<DoubleValue>)Parameters["ComparisonFactor"]; }
99    }
100    public IValueLookupParameter<DoubleValue> MaximumSelectionPressureParameter {
101      get { return (IValueLookupParameter<DoubleValue>)Parameters["MaximumSelectionPressure"]; }
102    }
103    public IValueLookupParameter<BoolValue> OffspringSelectionBeforeMutationParameter {
104      get { return (IValueLookupParameter<BoolValue>)Parameters["OffspringSelectionBeforeMutation"]; }
105    }
106    public IValueLookupParameter<BoolValue> FillPopulationWithParentsParameter {
107      get { return (IValueLookupParameter<BoolValue>)Parameters["FillPopulationWithParents"]; }
108    }
109
110    public IScopeTreeLookupParameter<DoubleValue> AgeParameter {
111      get { return (IScopeTreeLookupParameter<DoubleValue>)Parameters["Age"]; }
112    }
113    public IValueLookupParameter<IntValue> AgeGapParameter {
114      get { return (IValueLookupParameter<IntValue>)Parameters["AgeGap"]; }
115    }
116    public IValueLookupParameter<DoubleValue> AgeInheritanceParameter {
117      get { return (IValueLookupParameter<DoubleValue>)Parameters["AgeInheritance"]; }
118    }
119    public IValueLookupParameter<IntArray> AgeLimitsParameter {
120      get { return (IValueLookupParameter<IntArray>)Parameters["AgeLimits"]; }
121    }
122
123    public IValueLookupParameter<IntValue> MatingPoolRangeParameter {
124      get { return (IValueLookupParameter<IntValue>)Parameters["MatingPoolRange"]; }
125    }
126    public IValueLookupParameter<BoolValue> ReduceToPopulationSizeParameter {
127      get { return (IValueLookupParameter<BoolValue>)Parameters["ReduceToPopulationSize"]; }
128    }
129
130    public IValueLookupParameter<IOperator> TerminatorParameter {
131      get { return (IValueLookupParameter<IOperator>)Parameters["Terminator"]; }
132    }
133    #endregion
134
135    [StorableConstructor]
136    private AlpsOffspringSelectionGeneticAlgorithmMainLoop(StorableConstructorFlag _) : base(_) { }
137    private AlpsOffspringSelectionGeneticAlgorithmMainLoop(AlpsOffspringSelectionGeneticAlgorithmMainLoop original, Cloner cloner)
138      : base(original, cloner) { }
139    public override IDeepCloneable Clone(Cloner cloner) {
140      return new AlpsOffspringSelectionGeneticAlgorithmMainLoop(this, cloner);
141    }
142    public AlpsOffspringSelectionGeneticAlgorithmMainLoop()
143      : base() {
144      Parameters.Add(new ValueLookupParameter<IRandom>("GlobalRandom", "A pseudo random number generator."));
145      Parameters.Add(new ValueLookupParameter<IRandom>("LocalRandom", "A pseudo random number generator."));
146
147      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."));
148      Parameters.Add(new ValueLookupParameter<IntValue>("EvaluatedSolutions", "The number of times solutions have been evaluated."));
149      Parameters.Add(new ScopeTreeLookupParameter<DoubleValue>("Quality", "The value which represents the quality of a solution."));
150      Parameters.Add(new ValueLookupParameter<BoolValue>("Maximization", "True if the problem is a maximization problem, otherwise false."));
151
152      Parameters.Add(new ValueLookupParameter<IOperator>("Analyzer", "The operator used to analyze all individuals from all layers combined."));
153      Parameters.Add(new ValueLookupParameter<IOperator>("LayerAnalyzer", "The operator used to analyze each layer."));
154
155      Parameters.Add(new ValueLookupParameter<IntValue>("NumberOfLayers", "The number of layers."));
156      Parameters.Add(new ValueLookupParameter<IntValue>("PopulationSize", "The size of the population of solutions in each layer."));
157      Parameters.Add(new LookupParameter<IntValue>("CurrentPopulationSize", "The current size of the population."));
158
159      Parameters.Add(new ValueLookupParameter<IOperator>("Selector", "The operator used to select solutions for reproduction."));
160      Parameters.Add(new ValueLookupParameter<IOperator>("Crossover", "The operator used to cross solutions."));
161      Parameters.Add(new ValueLookupParameter<IOperator>("Mutator", "The operator used to mutate solutions."));
162      Parameters.Add(new ValueLookupParameter<PercentValue>("MutationProbability", "The probability that the mutation operator is applied on a solution."));
163      Parameters.Add(new ValueLookupParameter<IntValue>("Elites", "The numer of elite solutions which are kept in each generation."));
164      Parameters.Add(new ValueLookupParameter<BoolValue>("ReevaluateElites", "Flag to determine if elite individuals should be reevaluated (i.e., if stochastic fitness functions are used.)"));
165
166      Parameters.Add(new ValueLookupParameter<DoubleValue>("SuccessRatio", "The ratio of successful to total children that should be achieved."));
167      Parameters.Add(new ValueLookupParameter<DoubleValue>("ComparisonFactor", "The comparison factor is used to determine whether the offspring should be compared to the better parent, the worse parent or a quality value linearly interpolated between them. It is in the range [0;1]."));
168      Parameters.Add(new ValueLookupParameter<DoubleValue>("MaximumSelectionPressure", "The maximum selection pressure that terminates the algorithm."));
169      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."));
170      Parameters.Add(new ValueLookupParameter<BoolValue>("FillPopulationWithParents", "True if the population should be filled with parent individual or false if worse children should be used when the maximum selection pressure is exceeded."));
171
172      Parameters.Add(new ScopeTreeLookupParameter<DoubleValue>("Age", "The age of individuals."));
173      Parameters.Add(new ValueLookupParameter<IntValue>("AgeGap", "The frequency of reseeding the lowest layer and scaling factor for the age-limits for the layers."));
174      Parameters.Add(new ValueLookupParameter<DoubleValue>("AgeInheritance", "A weight that determines the age of a child after crossover based on the older (1.0) and younger (0.0) parent."));
175      Parameters.Add(new ValueLookupParameter<IntArray>("AgeLimits", "The maximum age an individual is allowed to reach in a certain layer."));
176
177      Parameters.Add(new ValueLookupParameter<IntValue>("MatingPoolRange", "The range of sub - populations used for creating a mating pool. (1 = current + previous sub-population)"));
178      Parameters.Add(new ValueLookupParameter<BoolValue>("ReduceToPopulationSize", "Reduce the CurrentPopulationSize after elder migration to PopulationSize"));
179
180      Parameters.Add(new ValueLookupParameter<IOperator>("Terminator", "The termination criteria that defines if the algorithm should continue or stop"));
181
182
183      var variableCreator = new VariableCreator() { Name = "Initialize" };
184      var initLayerAnalyzerProcessor = new SubScopesProcessor();
185      var layerVariableCreator = new VariableCreator() { Name = "Initialize Layer" };
186      var initLayerAnalyzerPlaceholder = new Placeholder() { Name = "LayerAnalyzer (Placeholder)" };
187      var layerResultCollector = new ResultsCollector() { Name = "Collect layer results" };
188      var initAnalyzerPlaceholder = new Placeholder() { Name = "Analyzer (Placeholder)" };
189      var resultsCollector = new ResultsCollector();
190      var matingPoolCreator = new MatingPoolCreator() { Name = "Create Mating Pools" };
191      var matingPoolProcessor = new UniformSubScopesProcessor() { Name = "Process Mating Pools" };
192      var initializeLayer = new Assigner() { Name = "Reset LayerEvaluatedSolutions" };
193      var mainOperator = new AlpsOffspringSelectionGeneticAlgorithmMainOperator();
194      var generationsIcrementor = new IntCounter() { Name = "Increment Generations" };
195      var evaluatedSolutionsReducer = new DataReducer() { Name = "Increment EvaluatedSolutions" };
196      var eldersEmigrator = CreateEldersEmigrator();
197      var layerOpener = CreateLayerOpener();
198      var layerReseeder = CreateReseeder();
199      var layerAnalyzerProcessor = new UniformSubScopesProcessor();
200      var layerAnalyzerPlaceholder = new Placeholder() { Name = "LayerAnalyzer (Placeholder)" };
201      var analyzerPlaceholder = new Placeholder() { Name = "Analyzer (Placeholder)" };
202      var termination = new TerminationOperator();
203
204      OperatorGraph.InitialOperator = variableCreator;
205
206      variableCreator.CollectedValues.Add(new ValueParameter<IntValue>("Generations", new IntValue(0)));
207      variableCreator.CollectedValues.Add(new ValueParameter<IntValue>("OpenLayers", new IntValue(1)));
208      variableCreator.Successor = initLayerAnalyzerProcessor;
209
210      initLayerAnalyzerProcessor.Operators.Add(layerVariableCreator);
211      initLayerAnalyzerProcessor.Successor = initAnalyzerPlaceholder;
212
213      layerVariableCreator.CollectedValues.Add(new ValueParameter<IntValue>("Layer", new IntValue(0)));
214      layerVariableCreator.CollectedValues.Add(new ValueParameter<ResultCollection>("LayerResults"));
215      layerVariableCreator.CollectedValues.Add(new ValueParameter<DoubleValue>("SelectionPressure", new DoubleValue(0)));
216      layerVariableCreator.CollectedValues.Add(new ValueParameter<DoubleValue>("CurrentSuccessRatio", new DoubleValue(0)));
217      layerVariableCreator.Successor = initLayerAnalyzerPlaceholder;
218
219      initLayerAnalyzerPlaceholder.OperatorParameter.ActualName = LayerAnalyzerParameter.Name;
220      initLayerAnalyzerPlaceholder.Successor = layerResultCollector;
221
222      layerResultCollector.ResultsParameter.ActualName = "LayerResults";
223      layerResultCollector.CollectedValues.Add(new LookupParameter<DoubleValue>("Current Selection Pressure", "Displays the rising selection pressure during a generation.", "SelectionPressure"));
224      layerResultCollector.CollectedValues.Add(new LookupParameter<DoubleValue>("Current Success Ratio", "Indicates how many successful children were already found during a generation (relative to the population size).", "CurrentSuccessRatio"));
225      layerResultCollector.Successor = null;
226
227      initAnalyzerPlaceholder.OperatorParameter.ActualName = AnalyzerParameter.Name;
228      initAnalyzerPlaceholder.Successor = resultsCollector;
229
230      resultsCollector.CollectedValues.Add(new LookupParameter<IntValue>("Generations"));
231      resultsCollector.CollectedValues.Add(new ScopeTreeLookupParameter<ResultCollection>("LayerResults", "Result set for each Layer", "LayerResults"));
232      resultsCollector.CollectedValues.Add(new LookupParameter<IntValue>("OpenLayers"));
233      resultsCollector.CopyValue = new BoolValue(false);
234      resultsCollector.Successor = matingPoolCreator;
235
236      matingPoolCreator.MatingPoolRangeParameter.Value = null;
237      matingPoolCreator.MatingPoolRangeParameter.ActualName = MatingPoolRangeParameter.Name;
238      matingPoolCreator.Successor = matingPoolProcessor;
239
240      matingPoolProcessor.Parallel.Value = true;
241      matingPoolProcessor.Operator = initializeLayer;
242      matingPoolProcessor.Successor = generationsIcrementor;
243
244      initializeLayer.LeftSideParameter.ActualName = "LayerEvaluatedSolutions";
245      initializeLayer.RightSideParameter.Value = new IntValue(0);
246      initializeLayer.Successor = mainOperator;
247
248      mainOperator.RandomParameter.ActualName = LocalRandomParameter.Name;
249      mainOperator.EvaluatorParameter.ActualName = EvaluatorParameter.Name;
250      mainOperator.EvaluatedSolutionsParameter.ActualName = "LayerEvaluatedSolutions";
251      mainOperator.QualityParameter.ActualName = QualityParameter.Name;
252      mainOperator.MaximizationParameter.ActualName = MaximizationParameter.Name;
253      mainOperator.PopulationSizeParameter.ActualName = PopulationSizeParameter.Name;
254      mainOperator.SelectorParameter.ActualName = SelectorParameter.Name;
255      mainOperator.CrossoverParameter.ActualName = CrossoverParameter.Name;
256      mainOperator.MutatorParameter.ActualName = MutatorParameter.ActualName;
257      mainOperator.MutationProbabilityParameter.ActualName = MutationProbabilityParameter.Name;
258      mainOperator.ElitesParameter.ActualName = ElitesParameter.Name;
259      mainOperator.ReevaluateElitesParameter.ActualName = ReevaluateElitesParameter.Name;
260      mainOperator.ComparisonFactorParameter.ActualName = ComparisonFactorParameter.Name;
261      mainOperator.SuccessRatioParameter.ActualName = SuccessRatioParameter.Name;
262      mainOperator.CurrentSuccessRatioParameter.ActualName = "CurrentSuccessRatio";
263      mainOperator.SelectionPressureParameter.ActualName = "SelectionPressure";
264      mainOperator.MaximumSelectionPressureParameter.ActualName = MaximumSelectionPressureParameter.Name;
265      mainOperator.OffspringSelectionBeforeMutationParameter.ActualName = OffspringSelectionBeforeMutationParameter.Name;
266      mainOperator.FillPopulationWithParentsParameter.ActualName = FillPopulationWithParentsParameter.Name;
267      mainOperator.AgeParameter.ActualName = AgeParameter.Name;
268      mainOperator.AgeInheritanceParameter.ActualName = AgeInheritanceParameter.Name;
269      mainOperator.AgeIncrementParameter.Value = new DoubleValue(1.0);
270      mainOperator.Successor = null;
271
272      generationsIcrementor.ValueParameter.ActualName = "Generations";
273      generationsIcrementor.Increment = new IntValue(1);
274      generationsIcrementor.Successor = evaluatedSolutionsReducer;
275
276      evaluatedSolutionsReducer.ParameterToReduce.ActualName = "LayerEvaluatedSolutions";
277      evaluatedSolutionsReducer.TargetParameter.ActualName = EvaluatedSolutionsParameter.Name;
278      evaluatedSolutionsReducer.ReductionOperation.Value = new ReductionOperation(ReductionOperations.Sum);
279      evaluatedSolutionsReducer.TargetOperation.Value = new ReductionOperation(ReductionOperations.Sum);
280      evaluatedSolutionsReducer.Successor = eldersEmigrator;
281
282      eldersEmigrator.Successor = layerOpener;
283
284      layerOpener.Successor = layerReseeder;
285
286      layerReseeder.Successor = layerAnalyzerProcessor;
287
288      layerAnalyzerProcessor.Operator = layerAnalyzerPlaceholder;
289      layerAnalyzerProcessor.Successor = analyzerPlaceholder;
290
291      layerAnalyzerPlaceholder.OperatorParameter.ActualName = LayerAnalyzerParameter.Name;
292
293      analyzerPlaceholder.OperatorParameter.ActualName = AnalyzerParameter.Name;
294      analyzerPlaceholder.Successor = termination;
295
296      termination.TerminatorParameter.ActualName = TerminatorParameter.Name;
297      termination.ContinueBranch = matingPoolCreator;
298    }
299
300    private CombinedOperator CreateEldersEmigrator() {
301      var eldersEmigrator = new CombinedOperator() { Name = "Emigrate Elders" };
302      var selectorProsessor = new UniformSubScopesProcessor();
303      var eldersSelector = new EldersSelector();
304      var shiftToRightMigrator = new UnidirectionalRingMigrator() { Name = "Shift elders to next layer" };
305      var mergingProsessor = new UniformSubScopesProcessor();
306      var mergingReducer = new MergingReducer();
307      var subScopesCounter = new SubScopesCounter();
308      var reduceToPopulationSizeBranch = new ConditionalBranch() { Name = "ReduceToPopulationSize?" };
309      var countCalculator = new ExpressionCalculator() { Name = "CurrentPopulationSize = Min(CurrentPopulationSize, PopulationSize)" };
310      var bestSelector = new BestSelector();
311      var rightReducer = new RightReducer();
312
313      eldersEmigrator.OperatorGraph.InitialOperator = selectorProsessor;
314
315      selectorProsessor.Operator = eldersSelector;
316      selectorProsessor.Successor = shiftToRightMigrator;
317
318      eldersSelector.AgeParameter.ActualName = AgeParameter.Name;
319      eldersSelector.AgeLimitsParameter.ActualName = AgeLimitsParameter.Name;
320      eldersSelector.NumberOfLayersParameter.ActualName = NumberOfLayersParameter.Name;
321      eldersSelector.LayerParameter.ActualName = "Layer";
322      eldersSelector.Successor = null;
323
324      shiftToRightMigrator.ClockwiseMigrationParameter.Value = new BoolValue(true);
325      shiftToRightMigrator.Successor = mergingProsessor;
326
327      mergingProsessor.Operator = mergingReducer;
328
329      mergingReducer.Successor = subScopesCounter;
330
331      subScopesCounter.ValueParameter.ActualName = CurrentPopulationSizeParameter.Name;
332      subScopesCounter.AccumulateParameter.Value = new BoolValue(false);
333      subScopesCounter.Successor = reduceToPopulationSizeBranch;
334
335      reduceToPopulationSizeBranch.ConditionParameter.ActualName = ReduceToPopulationSizeParameter.Name;
336      reduceToPopulationSizeBranch.TrueBranch = countCalculator;
337
338      countCalculator.CollectedValues.Add(new LookupParameter<IntValue>(PopulationSizeParameter.Name));
339      countCalculator.CollectedValues.Add(new LookupParameter<IntValue>(CurrentPopulationSizeParameter.Name));
340      countCalculator.ExpressionParameter.Value = new StringValue("CurrentPopulationSize PopulationSize CurrentPopulationSize PopulationSize < if toint");
341      countCalculator.ExpressionResultParameter.ActualName = CurrentPopulationSizeParameter.Name;
342      countCalculator.Successor = bestSelector;
343
344      bestSelector.NumberOfSelectedSubScopesParameter.ActualName = CurrentPopulationSizeParameter.Name;
345      bestSelector.CopySelected = new BoolValue(false);
346      bestSelector.Successor = rightReducer;
347
348      return eldersEmigrator;
349    }
350
351    private CombinedOperator CreateLayerOpener() {
352      var layerOpener = new CombinedOperator() { Name = "Open new Layer if needed" };
353      var maxLayerReached = new Comparator() { Name = "MaxLayersReached = OpenLayers >= NumberOfLayers" };
354      var maxLayerReachedBranch = new ConditionalBranch() { Name = "MaxLayersReached?" };
355      var openNewLayerCalculator = new ExpressionCalculator() { Name = "OpenNewLayer = Generations >= AgeLimits[OpenLayers - 1]" };
356      var openNewLayerBranch = new ConditionalBranch() { Name = "OpenNewLayer?" };
357      var layerCreator = new LastLayerCloner() { Name = "Create Layer" };
358      var updateLayerNumber = new Assigner() { Name = "Layer = OpenLayers" };
359      var historyWiper = new ResultsHistoryWiper() { Name = "Clear History in Results" };
360      var createChildrenViaCrossover = new AlpsOffspringSelectionGeneticAlgorithmMainOperator();
361      var incrEvaluatedSolutionsForNewLayer = new SubScopesCounter() { Name = "Update EvaluatedSolutions" };
362      var incrOpenLayers = new IntCounter() { Name = "Incr. OpenLayers" };
363      var newLayerResultsCollector = new ResultsCollector() { Name = "Collect new Layer Results" };
364
365      layerOpener.OperatorGraph.InitialOperator = maxLayerReached;
366
367      maxLayerReached.LeftSideParameter.ActualName = "OpenLayers";
368      maxLayerReached.RightSideParameter.ActualName = NumberOfLayersParameter.Name;
369      maxLayerReached.ResultParameter.ActualName = "MaxLayerReached";
370      maxLayerReached.Comparison = new Comparison(ComparisonType.GreaterOrEqual);
371      maxLayerReached.Successor = maxLayerReachedBranch;
372
373      maxLayerReachedBranch.ConditionParameter.ActualName = "MaxLayerReached";
374      maxLayerReachedBranch.FalseBranch = openNewLayerCalculator;
375
376      openNewLayerCalculator.CollectedValues.Add(new LookupParameter<IntArray>(AgeLimitsParameter.Name));
377      openNewLayerCalculator.CollectedValues.Add(new LookupParameter<IntValue>("Generations"));
378      openNewLayerCalculator.CollectedValues.Add(new LookupParameter<IntValue>(NumberOfLayersParameter.Name));
379      openNewLayerCalculator.CollectedValues.Add(new LookupParameter<IntValue>("OpenLayers"));
380      openNewLayerCalculator.ExpressionResultParameter.ActualName = "OpenNewLayer";
381      openNewLayerCalculator.ExpressionParameter.Value = new StringValue("Generations 1 + AgeLimits OpenLayers 1 - [] >");
382      openNewLayerCalculator.Successor = openNewLayerBranch;
383
384      openNewLayerBranch.ConditionParameter.ActualName = "OpenNewLayer";
385      openNewLayerBranch.TrueBranch = layerCreator;
386
387      layerCreator.NewLayerOperator = updateLayerNumber;
388      layerCreator.Successor = incrOpenLayers;
389
390      updateLayerNumber.LeftSideParameter.ActualName = "Layer";
391      updateLayerNumber.RightSideParameter.ActualName = "OpenLayers";
392      updateLayerNumber.Successor = historyWiper;
393
394      historyWiper.ResultsParameter.ActualName = "LayerResults";
395      historyWiper.Successor = createChildrenViaCrossover;
396
397      // Maybe use only crossover and no elitism instead of "default operator"
398      createChildrenViaCrossover.RandomParameter.ActualName = LocalRandomParameter.Name;
399      createChildrenViaCrossover.EvaluatorParameter.ActualName = EvaluatorParameter.Name;
400      createChildrenViaCrossover.EvaluatedSolutionsParameter.ActualName = "LayerEvaluatedSolutions";
401      createChildrenViaCrossover.QualityParameter.ActualName = QualityParameter.Name;
402      createChildrenViaCrossover.MaximizationParameter.ActualName = MaximizationParameter.Name;
403      createChildrenViaCrossover.PopulationSizeParameter.ActualName = PopulationSizeParameter.Name;
404      createChildrenViaCrossover.SelectorParameter.ActualName = SelectorParameter.Name;
405      createChildrenViaCrossover.CrossoverParameter.ActualName = CrossoverParameter.Name;
406      createChildrenViaCrossover.MutatorParameter.ActualName = MutatorParameter.ActualName;
407      createChildrenViaCrossover.MutationProbabilityParameter.ActualName = MutationProbabilityParameter.Name;
408      createChildrenViaCrossover.ElitesParameter.ActualName = ElitesParameter.Name;
409      createChildrenViaCrossover.ReevaluateElitesParameter.ActualName = ReevaluateElitesParameter.Name;
410      createChildrenViaCrossover.ComparisonFactorParameter.ActualName = ComparisonFactorParameter.Name;
411      createChildrenViaCrossover.SuccessRatioParameter.ActualName = SuccessRatioParameter.Name;
412      createChildrenViaCrossover.CurrentSuccessRatioParameter.ActualName = "CurrentSuccessRatio";
413      createChildrenViaCrossover.SelectionPressureParameter.ActualName = "SelectionPressure";
414      createChildrenViaCrossover.MaximumSelectionPressureParameter.ActualName = MaximumSelectionPressureParameter.Name;
415      createChildrenViaCrossover.OffspringSelectionBeforeMutationParameter.ActualName = OffspringSelectionBeforeMutationParameter.Name;
416      createChildrenViaCrossover.FillPopulationWithParentsParameter.ActualName = FillPopulationWithParentsParameter.Name;
417      createChildrenViaCrossover.AgeParameter.ActualName = AgeParameter.Name;
418      createChildrenViaCrossover.AgeInheritanceParameter.ActualName = AgeInheritanceParameter.Name;
419      createChildrenViaCrossover.AgeIncrementParameter.Value = new DoubleValue(0.0);
420      createChildrenViaCrossover.Successor = incrEvaluatedSolutionsForNewLayer;
421
422      incrEvaluatedSolutionsForNewLayer.ValueParameter.ActualName = EvaluatedSolutionsParameter.Name;
423      incrEvaluatedSolutionsForNewLayer.AccumulateParameter.Value = new BoolValue(true);
424
425      incrOpenLayers.ValueParameter.ActualName = "OpenLayers";
426      incrOpenLayers.Increment = new IntValue(1);
427      incrOpenLayers.Successor = newLayerResultsCollector;
428
429      newLayerResultsCollector.CollectedValues.Add(new ScopeTreeLookupParameter<ResultCollection>("LayerResults", "Result set for each layer", "LayerResults"));
430      newLayerResultsCollector.CopyValue = new BoolValue(false);
431      newLayerResultsCollector.Successor = null;
432
433      return layerOpener;
434    }
435
436    private CombinedOperator CreateReseeder() {
437      var reseeder = new CombinedOperator() { Name = "Reseed Layer Zero if needed" };
438      var reseedingController = new ReseedingController() { Name = "Reseeding needed (Generation % AgeGap == 0)?" };
439      var removeIndividuals = new SubScopesRemover();
440      var createIndividuals = new SolutionsCreator();
441      var initializeAgeProsessor = new UniformSubScopesProcessor();
442      var initializeAge = new VariableCreator() { Name = "Initialize Age" };
443      var incrEvaluatedSolutionsAfterReseeding = new SubScopesCounter() { Name = "Update EvaluatedSolutions" };
444
445      reseeder.OperatorGraph.InitialOperator = reseedingController;
446
447      reseedingController.GenerationsParameter.ActualName = "Generations";
448      reseedingController.AgeGapParameter.ActualName = AgeGapParameter.Name;
449      reseedingController.FirstLayerOperator = removeIndividuals;
450      reseedingController.Successor = null;
451
452      removeIndividuals.Successor = createIndividuals;
453
454      createIndividuals.NumberOfSolutionsParameter.ActualName = PopulationSizeParameter.Name;
455      createIndividuals.Successor = initializeAgeProsessor;
456
457      initializeAgeProsessor.Operator = initializeAge;
458      initializeAgeProsessor.Successor = incrEvaluatedSolutionsAfterReseeding;
459
460      initializeAge.CollectedValues.Add(new ValueParameter<DoubleValue>(AgeParameter.Name, new DoubleValue(0)));
461
462      incrEvaluatedSolutionsAfterReseeding.ValueParameter.ActualName = EvaluatedSolutionsParameter.Name;
463      incrEvaluatedSolutionsAfterReseeding.AccumulateParameter.Value = new BoolValue(true);
464
465      return reseeder;
466    }
467  }
468}
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