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source: trunk/HeuristicLab.Algorithms.ALPS/3.3/AlpsGeneticAlgorithm.cs @ 17181

Last change on this file since 17181 was 17180, checked in by swagner, 5 years ago

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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 System;
23using System.Collections.Generic;
24using System.Linq;
25using HEAL.Attic;
26using HeuristicLab.Analysis;
27using HeuristicLab.Collections;
28using HeuristicLab.Common;
29using HeuristicLab.Core;
30using HeuristicLab.Data;
31using HeuristicLab.Operators;
32using HeuristicLab.Optimization;
33using HeuristicLab.Optimization.Operators;
34using HeuristicLab.Parameters;
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  [StorableType("4A240A90-EB87-43D1-BD34-99A605B89C4D")]
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(StorableConstructorFlag _) : base(_) { }
250    [StorableHook(HookType.AfterDeserialization)]
251    private void AfterDeserialization() {
252      // BackwardsCompatibility3.3
253      #region Backwards compatible code, remove with 3.4
254      var optionalMutatorParameter = MutatorParameter as OptionalConstrainedValueParameter<IManipulator>;
255      if (optionalMutatorParameter != null) {
256        Parameters.Remove(optionalMutatorParameter);
257        Parameters.Add(new ConstrainedValueParameter<IManipulator>("Mutator", "The operator used to mutate solutions."));
258        foreach (var m in optionalMutatorParameter.ValidValues)
259          MutatorParameter.ValidValues.Add(m);
260        if (optionalMutatorParameter.Value == null) MutationProbability.Value = 0; // to guarantee that the old configuration results in the same behavior
261        else Mutator = optionalMutatorParameter.Value;
262        optionalMutatorParameter.ValidValues.Clear(); // to avoid dangling references to the old parameter its valid values are cleared
263      }
264      #endregion
265      Initialize();
266    }
267    private AlpsGeneticAlgorithm(AlpsGeneticAlgorithm original, Cloner cloner)
268      : base(original, cloner) {
269      qualityAnalyzer = cloner.Clone(original.qualityAnalyzer);
270      layerQualityAnalyzer = cloner.Clone(original.layerQualityAnalyzer);
271      ageAnalyzer = cloner.Clone(original.ageAnalyzer);
272      layerAgeAnalyzer = cloner.Clone(original.layerAgeAnalyzer);
273      ageDistributionAnalyzer = cloner.Clone(original.ageDistributionAnalyzer);
274      layerAgeDistributionAnalyzer = cloner.Clone(original.layerAgeDistributionAnalyzer);
275      generationsTerminator = cloner.Clone(original.generationsTerminator);
276      evaluationsTerminator = cloner.Clone(original.evaluationsTerminator);
277      qualityTerminator = cloner.Clone(original.qualityTerminator);
278      executionTimeTerminator = cloner.Clone(original.executionTimeTerminator);
279      Initialize();
280    }
281    public override IDeepCloneable Clone(Cloner cloner) {
282      return new AlpsGeneticAlgorithm(this, cloner);
283    }
284    public AlpsGeneticAlgorithm()
285      : base() {
286      #region Add parameters
287      Parameters.Add(new ValueParameter<IntValue>("Seed", "The random seed used to initialize the new pseudo random number generator.", new IntValue(0)));
288      Parameters.Add(new ValueParameter<BoolValue>("SetSeedRandomly", "True if the random seed should be set to a random value, otherwise false.", new BoolValue(true)));
289
290      Parameters.Add(new FixedValueParameter<MultiAnalyzer>("Analyzer", "The operator used to analyze all individuals from all layers combined.", new MultiAnalyzer()));
291      Parameters.Add(new FixedValueParameter<MultiAnalyzer>("LayerAnalyzer", "The operator used to analyze each layer.", new MultiAnalyzer()));
292
293      Parameters.Add(new ValueParameter<IntValue>("NumberOfLayers", "The number of layers.", new IntValue(10)));
294      Parameters.Add(new ValueParameter<IntValue>("PopulationSize", "The size of the population of solutions in each layer.", new IntValue(100)));
295
296      Parameters.Add(new ConstrainedValueParameter<ISelector>("Selector", "The operator used to select solutions for reproduction."));
297      Parameters.Add(new ConstrainedValueParameter<ICrossover>("Crossover", "The operator used to cross solutions."));
298      Parameters.Add(new ConstrainedValueParameter<IManipulator>("Mutator", "The operator used to mutate solutions."));
299      Parameters.Add(new ValueParameter<PercentValue>("MutationProbability", "The probability that the mutation operator is applied on a solution.", new PercentValue(0.05)));
300      Parameters.Add(new ValueParameter<IntValue>("Elites", "The numer of elite solutions which are kept in each generation.", new IntValue(1)));
301      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 });
302      Parameters.Add(new ValueParameter<BoolValue>("PlusSelection", "Include the parents in the selection of the invividuals for the next generation.", new BoolValue(false)));
303
304      Parameters.Add(new ValueParameter<EnumValue<AgingScheme>>("AgingScheme", "The aging scheme for setting the age-limits for the layers.", new EnumValue<AgingScheme>(ALPS.AgingScheme.Polynomial)));
305      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)));
306      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 });
307      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 });
308
309      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 });
310      Parameters.Add(new ValueParameter<BoolValue>("ReduceToPopulationSize", "Reduce the CurrentPopulationSize after elder migration to PopulationSize", new BoolValue(true)) { Hidden = true });
311
312      Parameters.Add(new ValueParameter<MultiTerminator>("Terminator", "The termination criteria that defines if the algorithm should continue or stop.", new MultiTerminator()));
313      #endregion
314
315      #region Create operators
316      var globalRandomCreator = new RandomCreator();
317      var layer0Creator = new SubScopesCreator() { Name = "Create Layer Zero" };
318      var layer0Processor = new SubScopesProcessor();
319      var localRandomCreator = new LocalRandomCreator();
320      var layerSolutionsCreator = new SolutionsCreator();
321      var initializeAgeProcessor = new UniformSubScopesProcessor();
322      var initializeAge = new VariableCreator() { Name = "Initialize Age" };
323      var initializeCurrentPopulationSize = new SubScopesCounter() { Name = "Initialize CurrentPopulationCounter" };
324      var initializeLocalEvaluatedSolutions = new Assigner() { Name = "Initialize LayerEvaluatedSolutions" };
325      var initializeGlobalEvaluatedSolutions = new DataReducer() { Name = "Initialize EvaluatedSolutions" };
326      var resultsCollector = new ResultsCollector();
327      var mainLoop = new AlpsGeneticAlgorithmMainLoop();
328      #endregion
329
330      #region Create and parameterize operator graph
331      OperatorGraph.InitialOperator = globalRandomCreator;
332
333      globalRandomCreator.RandomParameter.ActualName = "GlobalRandom";
334      globalRandomCreator.SeedParameter.Value = null;
335      globalRandomCreator.SeedParameter.ActualName = SeedParameter.Name;
336      globalRandomCreator.SetSeedRandomlyParameter.Value = null;
337      globalRandomCreator.SetSeedRandomlyParameter.ActualName = SetSeedRandomlyParameter.Name;
338      globalRandomCreator.Successor = layer0Creator;
339
340      layer0Creator.NumberOfSubScopesParameter.Value = new IntValue(1);
341      layer0Creator.Successor = layer0Processor;
342
343      layer0Processor.Operators.Add(localRandomCreator);
344      layer0Processor.Successor = initializeGlobalEvaluatedSolutions;
345
346      localRandomCreator.Successor = layerSolutionsCreator;
347
348      layerSolutionsCreator.NumberOfSolutionsParameter.ActualName = PopulationSizeParameter.Name;
349      layerSolutionsCreator.Successor = initializeAgeProcessor;
350
351      initializeAgeProcessor.Operator = initializeAge;
352      initializeAgeProcessor.Successor = initializeCurrentPopulationSize;
353
354      initializeCurrentPopulationSize.ValueParameter.ActualName = "CurrentPopulationSize";
355      initializeCurrentPopulationSize.Successor = initializeLocalEvaluatedSolutions;
356
357      initializeAge.CollectedValues.Add(new ValueParameter<DoubleValue>("Age", new DoubleValue(0)));
358      initializeAge.Successor = null;
359
360      initializeLocalEvaluatedSolutions.LeftSideParameter.ActualName = "LayerEvaluatedSolutions";
361      initializeLocalEvaluatedSolutions.RightSideParameter.ActualName = "CurrentPopulationSize";
362      initializeLocalEvaluatedSolutions.Successor = null;
363
364      initializeGlobalEvaluatedSolutions.ReductionOperation.Value.Value = ReductionOperations.Sum;
365      initializeGlobalEvaluatedSolutions.TargetOperation.Value.Value = ReductionOperations.Assign;
366      initializeGlobalEvaluatedSolutions.ParameterToReduce.ActualName = "LayerEvaluatedSolutions";
367      initializeGlobalEvaluatedSolutions.TargetParameter.ActualName = "EvaluatedSolutions";
368      initializeGlobalEvaluatedSolutions.Successor = resultsCollector;
369
370      resultsCollector.CollectedValues.Add(new LookupParameter<IntValue>("Evaluated Solutions", null, "EvaluatedSolutions"));
371      resultsCollector.Successor = mainLoop;
372
373      mainLoop.GlobalRandomParameter.ActualName = "GlobalRandom";
374      mainLoop.LocalRandomParameter.ActualName = localRandomCreator.LocalRandomParameter.Name;
375      mainLoop.EvaluatedSolutionsParameter.ActualName = "EvaluatedSolutions";
376      mainLoop.AnalyzerParameter.ActualName = AnalyzerParameter.Name;
377      mainLoop.LayerAnalyzerParameter.ActualName = LayerAnalyzerParameter.Name;
378      mainLoop.NumberOfLayersParameter.ActualName = NumberOfLayersParameter.Name;
379      mainLoop.PopulationSizeParameter.ActualName = PopulationSizeParameter.Name;
380      mainLoop.CurrentPopulationSizeParameter.ActualName = "CurrentPopulationSize";
381      mainLoop.SelectorParameter.ActualName = SelectorParameter.Name;
382      mainLoop.CrossoverParameter.ActualName = CrossoverParameter.Name;
383      mainLoop.MutatorParameter.ActualName = MutatorParameter.Name;
384      mainLoop.MutationProbabilityParameter.ActualName = MutationProbabilityParameter.Name;
385      mainLoop.ElitesParameter.ActualName = ElitesParameter.Name;
386      mainLoop.ReevaluateElitesParameter.ActualName = ReevaluateElitesParameter.Name;
387      mainLoop.PlusSelectionParameter.ActualName = PlusSelectionParameter.Name;
388      mainLoop.AgeParameter.ActualName = "Age";
389      mainLoop.AgeGapParameter.ActualName = AgeGapParameter.Name;
390      mainLoop.AgeInheritanceParameter.ActualName = AgeInheritanceParameter.Name;
391      mainLoop.AgeLimitsParameter.ActualName = AgeLimitsParameter.Name;
392      mainLoop.MatingPoolRangeParameter.ActualName = MatingPoolRangeParameter.Name;
393      mainLoop.ReduceToPopulationSizeParameter.ActualName = ReduceToPopulationSizeParameter.Name;
394      mainLoop.TerminatorParameter.ActualName = TerminatorParameter.Name;
395      #endregion
396
397      #region Set selectors
398      foreach (var selector in ApplicationManager.Manager.GetInstances<ISelector>().Where(s => !(s is IMultiObjectiveSelector)).OrderBy(s => Name))
399        SelectorParameter.ValidValues.Add(selector);
400      var defaultSelector = SelectorParameter.ValidValues.OfType<GeneralizedRankSelector>().FirstOrDefault();
401      if (defaultSelector != null) {
402        defaultSelector.PressureParameter.Value = new DoubleValue(4.0);
403        SelectorParameter.Value = defaultSelector;
404      }
405      #endregion
406
407      #region Create analyzers
408      qualityAnalyzer = new BestAverageWorstQualityAnalyzer();
409      layerQualityAnalyzer = new BestAverageWorstQualityAnalyzer();
410      ageAnalyzer = new OldestAverageYoungestAgeAnalyzer();
411      layerAgeAnalyzer = new OldestAverageYoungestAgeAnalyzer();
412      ageDistributionAnalyzer = new AgeDistributionAnalyzer();
413      layerAgeDistributionAnalyzer = new AgeDistributionAnalyzer();
414      #endregion
415
416      #region Create terminators
417      generationsTerminator = new ComparisonTerminator<IntValue>("Generations", ComparisonType.Less, new IntValue(1000)) { Name = "Generations" };
418      evaluationsTerminator = new ComparisonTerminator<IntValue>("EvaluatedSolutions", ComparisonType.Less, new IntValue(int.MaxValue)) { Name = "Evaluations" };
419      qualityTerminator = new SingleObjectiveQualityTerminator() { Name = "Quality" };
420      executionTimeTerminator = new ExecutionTimeTerminator(this, new TimeSpanValue(TimeSpan.FromMinutes(5)));
421      #endregion
422
423      #region Parameterize
424      UpdateAnalyzers();
425      ParameterizeAnalyzers();
426
427      ParameterizeSelectors();
428
429      UpdateTerminators();
430
431      ParameterizeAgeLimits();
432      #endregion
433
434      Initialize();
435    }
436    #endregion
437
438    #region Events
439    public override void Prepare() {
440      if (Problem != null)
441        base.Prepare();
442    }
443    protected override void OnProblemChanged() {
444      base.OnProblemChanged();
445      ParameterizeStochasticOperator(Problem.SolutionCreator);
446      foreach (var @operator in Problem.Operators.OfType<IOperator>())
447        ParameterizeStochasticOperator(@operator);
448      ParameterizeStochasticOperatorForLayer(Problem.Evaluator);
449
450      ParameterizeIterationBasedOperators();
451
452      ParameterizeSolutionsCreator();
453      ParameterizeMainLoop();
454      ParameterizeAnalyzers();
455      ParameterizeSelectors();
456      ParameterizeTerminators();
457
458      Problem.Evaluator.QualityParameter.ActualNameChanged += Evaluator_QualityParameter_ActualNameChanged;
459
460      UpdateAnalyzers();
461      UpdateCrossovers();
462      UpdateMutators();
463      UpdateTerminators();
464    }
465
466    protected override void RegisterProblemEvents() {
467      base.RegisterProblemEvents();
468      var maximizationParameter = (IValueParameter<BoolValue>)Problem.MaximizationParameter;
469      if (maximizationParameter != null) maximizationParameter.ValueChanged += new EventHandler(MaximizationParameter_ValueChanged);
470    }
471    protected override void DeregisterProblemEvents() {
472      var maximizationParameter = (IValueParameter<BoolValue>)Problem.MaximizationParameter;
473      if (maximizationParameter != null) maximizationParameter.ValueChanged -= new EventHandler(MaximizationParameter_ValueChanged);
474      base.DeregisterProblemEvents();
475    }
476
477    protected override void Problem_SolutionCreatorChanged(object sender, EventArgs e) {
478      base.Problem_SolutionCreatorChanged(sender, e);
479      ParameterizeStochasticOperator(Problem.SolutionCreator);
480
481      Problem.Evaluator.QualityParameter.ActualNameChanged += Evaluator_QualityParameter_ActualNameChanged;
482
483      ParameterizeSolutionsCreator();
484      ParameterizeAnalyzers();
485    }
486    protected override void Problem_EvaluatorChanged(object sender, EventArgs e) {
487      base.Problem_EvaluatorChanged(sender, e);
488      ParameterizeStochasticOperatorForLayer(Problem.Evaluator);
489
490      UpdateAnalyzers();
491
492      ParameterizeSolutionsCreator();
493      ParameterizeMainLoop();
494      ParameterizeSelectors();
495    }
496    protected override void Problem_OperatorsChanged(object sender, EventArgs e) {
497      base.Problem_OperatorsChanged(sender, e);
498      foreach (IOperator op in Problem.Operators.OfType<IOperator>()) ParameterizeStochasticOperator(op);
499      ParameterizeStochasticOperatorForLayer(Problem.Evaluator);
500      ParameterizeIterationBasedOperators();
501      UpdateCrossovers();
502      UpdateMutators();
503      UpdateTerminators();
504    }
505    private void Evaluator_QualityParameter_ActualNameChanged(object sender, EventArgs e) {
506      ParameterizeMainLoop();
507      ParameterizeAnalyzers();
508      ParameterizeSelectors();
509    }
510    private void MaximizationParameter_ValueChanged(object sender, EventArgs e) {
511      ParameterizeTerminators();
512    }
513    private void QualityAnalyzer_CurrentBestQualityParameter_NameChanged(object sender, EventArgs e) {
514      ParameterizeTerminators();
515    }
516
517    private void AgeGapParameter_ValueChanged(object sender, EventArgs e) {
518      AgeGap.ValueChanged += AgeGap_ValueChanged;
519      ParameterizeAgeLimits();
520    }
521    private void AgeGap_ValueChanged(object sender, EventArgs e) {
522      ParameterizeAgeLimits();
523    }
524    private void AgingSchemeParameter_ValueChanged(object sender, EventArgs e) {
525      AgingScheme.ValueChanged += AgingScheme_ValueChanged;
526      ParameterizeAgeLimits();
527    }
528    private void AgingScheme_ValueChanged(object sender, EventArgs e) {
529      ParameterizeAgeLimits();
530    }
531    private void NumberOfLayersParameter_ValueChanged(object sender, EventArgs e) {
532      NumberOfLayers.ValueChanged += NumberOfLayers_ValueChanged;
533      ParameterizeAgeLimits();
534    }
535    private void NumberOfLayers_ValueChanged(object sender, EventArgs e) {
536      ParameterizeAgeLimits();
537    }
538
539    private void AnalyzerOperators_ItemsAdded(object sender, CollectionItemsChangedEventArgs<IndexedItem<IAnalyzer>> e) {
540      foreach (var analyzer in e.Items) {
541        foreach (var parameter in analyzer.Value.Parameters.OfType<IScopeTreeLookupParameter>()) {
542          parameter.Depth = 2;
543        }
544      }
545    }
546    private void LayerAnalyzerOperators_ItemsAdded(object sender, CollectionItemsChangedEventArgs<IndexedItem<IAnalyzer>> e) {
547      foreach (var analyzer in e.Items) {
548        IParameter resultParameter;
549        if (analyzer.Value.Parameters.TryGetValue("Results", out resultParameter)) {
550          var lookupParameter = resultParameter as ILookupParameter;
551          if (lookupParameter != null)
552            lookupParameter.ActualName = "LayerResults";
553        }
554        foreach (var parameter in analyzer.Value.Parameters.OfType<IScopeTreeLookupParameter>()) {
555          parameter.Depth = 1;
556        }
557      }
558    }
559    #endregion
560
561    #region Parameterization
562    private void Initialize() {
563      if (Problem != null)
564        Problem.Evaluator.QualityParameter.ActualNameChanged += Evaluator_QualityParameter_ActualNameChanged;
565
566      NumberOfLayersParameter.ValueChanged += NumberOfLayersParameter_ValueChanged;
567      NumberOfLayers.ValueChanged += NumberOfLayers_ValueChanged;
568
569      Analyzer.Operators.ItemsAdded += AnalyzerOperators_ItemsAdded;
570      LayerAnalyzer.Operators.ItemsAdded += LayerAnalyzerOperators_ItemsAdded;
571
572      AgeGapParameter.ValueChanged += AgeGapParameter_ValueChanged;
573      AgeGap.ValueChanged += AgeGap_ValueChanged;
574      AgingSchemeParameter.ValueChanged += AgingSchemeParameter_ValueChanged;
575      AgingScheme.ValueChanged += AgingScheme_ValueChanged;
576
577      qualityAnalyzer.CurrentBestQualityParameter.NameChanged += new EventHandler(QualityAnalyzer_CurrentBestQualityParameter_NameChanged);
578    }
579    private void ParameterizeSolutionsCreator() {
580      SolutionsCreator.EvaluatorParameter.ActualName = Problem.EvaluatorParameter.Name;
581      SolutionsCreator.SolutionCreatorParameter.ActualName = Problem.SolutionCreatorParameter.Name;
582    }
583    private void ParameterizeMainLoop() {
584      MainLoop.EvaluatorParameter.ActualName = Problem.EvaluatorParameter.Name;
585      MainLoop.QualityParameter.ActualName = Problem.Evaluator.QualityParameter.ActualName;
586      MainLoop.MaximizationParameter.ActualName = Problem.MaximizationParameter.Name;
587    }
588    private void ParameterizeAnalyzers() {
589      qualityAnalyzer.ResultsParameter.ActualName = "Results";
590      qualityAnalyzer.ResultsParameter.Hidden = true;
591      qualityAnalyzer.QualityParameter.Depth = 2;
592      layerQualityAnalyzer.ResultsParameter.ActualName = "LayerResults";
593      layerQualityAnalyzer.ResultsParameter.Hidden = true;
594      layerQualityAnalyzer.QualityParameter.Depth = 1;
595      if (Problem != null) {
596        qualityAnalyzer.MaximizationParameter.ActualName = Problem.MaximizationParameter.Name;
597        qualityAnalyzer.MaximizationParameter.Hidden = true;
598        qualityAnalyzer.QualityParameter.ActualName = Problem.Evaluator.QualityParameter.ActualName;
599        qualityAnalyzer.QualityParameter.Hidden = true;
600        qualityAnalyzer.BestKnownQualityParameter.ActualName = Problem.BestKnownQualityParameter.Name;
601        qualityAnalyzer.BestKnownQualityParameter.Hidden = true;
602        layerQualityAnalyzer.MaximizationParameter.ActualName = Problem.MaximizationParameter.Name;
603        layerQualityAnalyzer.MaximizationParameter.Hidden = true;
604        layerQualityAnalyzer.QualityParameter.ActualName = Problem.Evaluator.QualityParameter.ActualName;
605        layerQualityAnalyzer.QualityParameter.Hidden = true;
606        layerQualityAnalyzer.BestKnownQualityParameter.ActualName = Problem.BestKnownQualityParameter.Name;
607        layerQualityAnalyzer.BestKnownQualityParameter.Hidden = true;
608      }
609    }
610    private void ParameterizeSelectors() {
611      foreach (var selector in SelectorParameter.ValidValues) {
612        selector.CopySelected = new BoolValue(true);
613        selector.NumberOfSelectedSubScopesParameter.Hidden = true;
614        ParameterizeStochasticOperatorForLayer(selector);
615      }
616      if (Problem != null) {
617        foreach (var selector in SelectorParameter.ValidValues.OfType<ISingleObjectiveSelector>()) {
618          selector.MaximizationParameter.ActualName = Problem.MaximizationParameter.Name;
619          selector.MaximizationParameter.Hidden = true;
620          selector.QualityParameter.ActualName = Problem.Evaluator.QualityParameter.ActualName;
621          selector.QualityParameter.Hidden = true;
622        }
623      }
624    }
625    private void ParameterizeTerminators() {
626      qualityTerminator.Parameterize(qualityAnalyzer.CurrentBestQualityParameter, Problem);
627    }
628    private void ParameterizeIterationBasedOperators() {
629      if (Problem != null) {
630        foreach (var @operator in Problem.Operators.OfType<IIterationBasedOperator>()) {
631          @operator.IterationsParameter.ActualName = "Generations";
632          @operator.IterationsParameter.Hidden = true;
633          @operator.MaximumIterationsParameter.ActualName = generationsTerminator.ThresholdParameter.Name;
634          @operator.MaximumIterationsParameter.Hidden = true;
635        }
636      }
637    }
638    private void ParameterizeAgeLimits() {
639      var scheme = AgingScheme.Value;
640      int ageGap = AgeGap.Value;
641      int numberOfLayers = NumberOfLayers.Value;
642      AgeLimits = scheme.CalculateAgeLimits(ageGap, numberOfLayers);
643    }
644
645    private void ParameterizeStochasticOperator(IOperator @operator) {
646      var stochasticOperator = @operator as IStochasticOperator;
647      if (stochasticOperator != null) {
648        stochasticOperator.RandomParameter.ActualName = "GlobalRandom";
649        stochasticOperator.RandomParameter.Hidden = true;
650      }
651    }
652
653    private void ParameterizeStochasticOperatorForLayer(IOperator @operator) {
654      var stochasticOperator = @operator as IStochasticOperator;
655      if (stochasticOperator != null) {
656        stochasticOperator.RandomParameter.ActualName = "LocalRandom";
657        stochasticOperator.RandomParameter.Hidden = true;
658      }
659    }
660
661    #endregion
662
663    #region Updates
664    private void UpdateAnalyzers() {
665      Analyzer.Operators.Clear();
666      LayerAnalyzer.Operators.Clear();
667
668      Analyzer.Operators.Add(qualityAnalyzer, qualityAnalyzer.EnabledByDefault);
669      Analyzer.Operators.Add(ageAnalyzer, ageAnalyzer.EnabledByDefault);
670      Analyzer.Operators.Add(ageDistributionAnalyzer, ageDistributionAnalyzer.EnabledByDefault);
671      LayerAnalyzer.Operators.Add(layerQualityAnalyzer, false);
672      LayerAnalyzer.Operators.Add(layerAgeAnalyzer, false);
673      LayerAnalyzer.Operators.Add(layerAgeDistributionAnalyzer, false);
674
675      if (Problem != null) {
676        foreach (var analyzer in Problem.Operators.OfType<IAnalyzer>()) {
677          Analyzer.Operators.Add(analyzer, analyzer.EnabledByDefault);
678          LayerAnalyzer.Operators.Add((IAnalyzer)analyzer.Clone(), false);
679        }
680      }
681    }
682    private void UpdateCrossovers() {
683      var oldCrossover = CrossoverParameter.Value;
684      var defaultCrossover = Problem.Operators.OfType<ICrossover>().FirstOrDefault();
685      CrossoverParameter.ValidValues.Clear();
686      foreach (var crossover in Problem.Operators.OfType<ICrossover>().OrderBy(c => c.Name)) {
687        ParameterizeStochasticOperatorForLayer(crossover);
688        CrossoverParameter.ValidValues.Add(crossover);
689      }
690      if (oldCrossover != null) {
691        var crossover = CrossoverParameter.ValidValues.FirstOrDefault(c => c.GetType() == oldCrossover.GetType());
692        if (crossover != null)
693          CrossoverParameter.Value = crossover;
694        else
695          oldCrossover = null;
696      }
697      if (oldCrossover == null && defaultCrossover != null)
698        CrossoverParameter.Value = defaultCrossover;
699    }
700    private void UpdateMutators() {
701      IManipulator oldMutator = MutatorParameter.Value;
702      MutatorParameter.ValidValues.Clear();
703      IManipulator defaultMutator = Problem.Operators.OfType<IManipulator>().FirstOrDefault();
704
705      foreach (IManipulator mutator in Problem.Operators.OfType<IManipulator>().OrderBy(x => x.Name)) {
706        ParameterizeStochasticOperatorForLayer(mutator);
707        MutatorParameter.ValidValues.Add(mutator);
708      }
709
710      if (oldMutator != null) {
711        IManipulator mutator = MutatorParameter.ValidValues.FirstOrDefault(x => x.GetType() == oldMutator.GetType());
712        if (mutator != null) MutatorParameter.Value = mutator;
713        else oldMutator = null;
714      }
715
716      if (oldMutator == null && defaultMutator != null)
717        MutatorParameter.Value = defaultMutator;
718    }
719    private void UpdateTerminators() {
720      var newTerminators = new Dictionary<ITerminator, bool> {
721        {generationsTerminator, !Terminators.Operators.Contains(generationsTerminator) || Terminators.Operators.ItemChecked(generationsTerminator)},
722        {evaluationsTerminator, Terminators.Operators.Contains(evaluationsTerminator) && Terminators.Operators.ItemChecked(evaluationsTerminator)},
723        {qualityTerminator, Terminators.Operators.Contains(qualityTerminator) && Terminators.Operators.ItemChecked(qualityTerminator) },
724        {executionTimeTerminator, Terminators.Operators.Contains(executionTimeTerminator) && Terminators.Operators.ItemChecked(executionTimeTerminator)}
725      };
726      if (Problem != null) {
727        foreach (var terminator in Problem.Operators.OfType<ITerminator>())
728          newTerminators.Add(terminator, !Terminators.Operators.Contains(terminator) || Terminators.Operators.ItemChecked(terminator));
729      }
730
731      Terminators.Operators.Clear();
732
733      foreach (var newTerminator in newTerminators)
734        Terminators.Operators.Add(newTerminator.Key, newTerminator.Value);
735    }
736    #endregion
737  }
738}
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