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source: trunk/sources/HeuristicLab.Algorithms.OffspringSelectionGeneticAlgorithm/3.3/SASEGASA.cs @ 3696

Last change on this file since 3696 was 3689, checked in by abeham, 15 years ago

#893

  • fixed wiring in the algorithms
File size: 28.4 KB
Line 
1#region License Information
2/* HeuristicLab
3 * Copyright (C) 2002-2010 Heuristic and Evolutionary Algorithms Laboratory (HEAL)
4 *
5 * This file is part of HeuristicLab.
6 *
7 * HeuristicLab is free software: you can redistribute it and/or modify
8 * it under the terms of the GNU General Public License as published by
9 * the Free Software Foundation, either version 3 of the License, or
10 * (at your option) any later version.
11 *
12 * HeuristicLab is distributed in the hope that it will be useful,
13 * but WITHOUT ANY WARRANTY; without even the implied warranty of
14 * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
15 * GNU General Public License for more details.
16 *
17 * You should have received a copy of the GNU General Public License
18 * along with HeuristicLab. If not, see <http://www.gnu.org/licenses/>.
19 */
20#endregion
21
22using System;
23using System.Collections.Generic;
24using System.Linq;
25using HeuristicLab.Analysis;
26using HeuristicLab.Common;
27using HeuristicLab.Core;
28using HeuristicLab.Data;
29using HeuristicLab.Operators;
30using HeuristicLab.Optimization;
31using HeuristicLab.Optimization.Operators;
32using HeuristicLab.Parameters;
33using HeuristicLab.Persistence.Default.CompositeSerializers.Storable;
34using HeuristicLab.PluginInfrastructure;
35using HeuristicLab.Random;
36using HeuristicLab.Selection;
37
38namespace HeuristicLab.Algorithms.OffspringSelectionGeneticAlgorithm {
39  /// <summary>
40  /// The self-adaptive segregative genetic algorithm with simulated annealing aspects (Affenzeller, M. et al. 2009. Genetic Algorithms and Genetic Programming - Modern Concepts and Practical Applications. CRC Press).
41  /// </summary>
42  [Item("SASEGASA", "The self-adaptive segregative genetic algorithm with simulated annealing aspects (Affenzeller, M. et al. 2009. Genetic Algorithms and Genetic Programming - Modern Concepts and Practical Applications. CRC Press).")]
43  [Creatable("Algorithms")]
44  [StorableClass]
45  public sealed class SASEGASA : EngineAlgorithm {
46
47    #region Problem Properties
48    public override Type ProblemType {
49      get { return typeof(ISingleObjectiveProblem); }
50    }
51    public new ISingleObjectiveProblem Problem {
52      get { return (ISingleObjectiveProblem)base.Problem; }
53      set { base.Problem = value; }
54    }
55    #endregion
56
57    #region Parameter Properties
58    private ValueParameter<IntValue> SeedParameter {
59      get { return (ValueParameter<IntValue>)Parameters["Seed"]; }
60    }
61    private ValueParameter<BoolValue> SetSeedRandomlyParameter {
62      get { return (ValueParameter<BoolValue>)Parameters["SetSeedRandomly"]; }
63    }
64    private ValueParameter<IntValue> NumberOfVillagesParameter {
65      get { return (ValueParameter<IntValue>)Parameters["NumberOfVillages"]; }
66    }
67    private ValueParameter<IntValue> PopulationSizeParameter {
68      get { return (ValueParameter<IntValue>)Parameters["PopulationSize"]; }
69    }
70    private ValueParameter<IntValue> MaximumGenerationsParameter {
71      get { return (ValueParameter<IntValue>)Parameters["MaximumGenerations"]; }
72    }
73    private ConstrainedValueParameter<ISelector> SelectorParameter {
74      get { return (ConstrainedValueParameter<ISelector>)Parameters["Selector"]; }
75    }
76    private ConstrainedValueParameter<ICrossover> CrossoverParameter {
77      get { return (ConstrainedValueParameter<ICrossover>)Parameters["Crossover"]; }
78    }
79    private ValueParameter<PercentValue> MutationProbabilityParameter {
80      get { return (ValueParameter<PercentValue>)Parameters["MutationProbability"]; }
81    }
82    private OptionalConstrainedValueParameter<IManipulator> MutatorParameter {
83      get { return (OptionalConstrainedValueParameter<IManipulator>)Parameters["Mutator"]; }
84    }
85    private ValueParameter<IntValue> ElitesParameter {
86      get { return (ValueParameter<IntValue>)Parameters["Elites"]; }
87    }
88    private ValueParameter<BoolValue> ParallelParameter {
89      get { return (ValueParameter<BoolValue>)Parameters["Parallel"]; }
90    }
91    private ValueLookupParameter<DoubleValue> SuccessRatioParameter {
92      get { return (ValueLookupParameter<DoubleValue>)Parameters["SuccessRatio"]; }
93    }
94    private ValueLookupParameter<DoubleValue> ComparisonFactorLowerBoundParameter {
95      get { return (ValueLookupParameter<DoubleValue>)Parameters["ComparisonFactorLowerBound"]; }
96    }
97    private ValueLookupParameter<DoubleValue> ComparisonFactorUpperBoundParameter {
98      get { return (ValueLookupParameter<DoubleValue>)Parameters["ComparisonFactorUpperBound"]; }
99    }
100    private OptionalConstrainedValueParameter<IDiscreteDoubleValueModifier> ComparisonFactorModifierParameter {
101      get { return (OptionalConstrainedValueParameter<IDiscreteDoubleValueModifier>)Parameters["ComparisonFactorModifier"]; }
102    }
103    private ValueLookupParameter<DoubleValue> MaximumSelectionPressureParameter {
104      get { return (ValueLookupParameter<DoubleValue>)Parameters["MaximumSelectionPressure"]; }
105    }
106    private ValueLookupParameter<DoubleValue> FinalMaximumSelectionPressureParameter {
107      get { return (ValueLookupParameter<DoubleValue>)Parameters["FinalMaximumSelectionPressure"]; }
108    }
109    private ValueLookupParameter<BoolValue> OffspringSelectionBeforeMutationParameter {
110      get { return (ValueLookupParameter<BoolValue>)Parameters["OffspringSelectionBeforeMutation"]; }
111    }
112    private ValueLookupParameter<IntValue> SelectedParentsParameter {
113      get { return (ValueLookupParameter<IntValue>)Parameters["SelectedParents"]; }
114    }
115    private ValueParameter<MultiAnalyzer> AnalyzerParameter {
116      get { return (ValueParameter<MultiAnalyzer>)Parameters["Analyzer"]; }
117    }
118    private ValueParameter<MultiAnalyzer> VillageAnalyzerParameter {
119      get { return (ValueParameter<MultiAnalyzer>)Parameters["VillageAnalyzer"]; }
120    }
121    #endregion
122
123    #region Properties
124    public IntValue Seed {
125      get { return SeedParameter.Value; }
126      set { SeedParameter.Value = value; }
127    }
128    public BoolValue SetSeedRandomly {
129      get { return SetSeedRandomlyParameter.Value; }
130      set { SetSeedRandomlyParameter.Value = value; }
131    }
132    public IntValue NumberOfVillages {
133      get { return NumberOfVillagesParameter.Value; }
134      set { NumberOfVillagesParameter.Value = value; }
135    }
136    public IntValue PopulationSize {
137      get { return PopulationSizeParameter.Value; }
138      set { PopulationSizeParameter.Value = value; }
139    }
140    public IntValue MaximumGenerations {
141      get { return MaximumGenerationsParameter.Value; }
142      set { MaximumGenerationsParameter.Value = value; }
143    }
144    public ISelector Selector {
145      get { return SelectorParameter.Value; }
146      set { SelectorParameter.Value = value; }
147    }
148    public ICrossover Crossover {
149      get { return CrossoverParameter.Value; }
150      set { CrossoverParameter.Value = value; }
151    }
152    public PercentValue MutationProbability {
153      get { return MutationProbabilityParameter.Value; }
154      set { MutationProbabilityParameter.Value = value; }
155    }
156    public IManipulator Mutator {
157      get { return MutatorParameter.Value; }
158      set { MutatorParameter.Value = value; }
159    }
160    public IntValue Elites {
161      get { return ElitesParameter.Value; }
162      set { ElitesParameter.Value = value; }
163    }
164    public BoolValue Parallel {
165      get { return ParallelParameter.Value; }
166      set { ParallelParameter.Value = value; }
167    }
168    public DoubleValue SuccessRatio {
169      get { return SuccessRatioParameter.Value; }
170      set { SuccessRatioParameter.Value = value; }
171    }
172    public DoubleValue ComparisonFactorLowerBound {
173      get { return ComparisonFactorLowerBoundParameter.Value; }
174      set { ComparisonFactorLowerBoundParameter.Value = value; }
175    }
176    public DoubleValue ComparisonFactorUpperBound {
177      get { return ComparisonFactorUpperBoundParameter.Value; }
178      set { ComparisonFactorUpperBoundParameter.Value = value; }
179    }
180    public IDiscreteDoubleValueModifier ComparisonFactorModifier {
181      get { return ComparisonFactorModifierParameter.Value; }
182      set { ComparisonFactorModifierParameter.Value = value; }
183    }
184    public DoubleValue MaximumSelectionPressure {
185      get { return MaximumSelectionPressureParameter.Value; }
186      set { MaximumSelectionPressureParameter.Value = value; }
187    }
188    public DoubleValue FinalMaximumSelectionPressure {
189      get { return FinalMaximumSelectionPressureParameter.Value; }
190      set { FinalMaximumSelectionPressureParameter.Value = value; }
191    }
192    public BoolValue OffspringSelectionBeforeMutation {
193      get { return OffspringSelectionBeforeMutationParameter.Value; }
194      set { OffspringSelectionBeforeMutationParameter.Value = value; }
195    }
196    public IntValue SelectedParents {
197      get { return SelectedParentsParameter.Value; }
198      set { SelectedParentsParameter.Value = value; }
199    }
200    public MultiAnalyzer Analyzer {
201      get { return AnalyzerParameter.Value; }
202      set { AnalyzerParameter.Value = value; }
203    }
204    public MultiAnalyzer VillageAnalyzer {
205      get { return VillageAnalyzerParameter.Value; }
206      set { VillageAnalyzerParameter.Value = value; }
207    }
208    private RandomCreator RandomCreator {
209      get { return (RandomCreator)OperatorGraph.InitialOperator; }
210    }
211    private UniformSubScopesProcessor VillageProcessor {
212      get { return ((RandomCreator.Successor as SubScopesCreator).Successor as UniformSubScopesProcessor); }
213    }
214    private SolutionsCreator SolutionsCreator {
215      get { return (SolutionsCreator)VillageProcessor.Operator; }
216    }
217    private SASEGASAMainLoop MainLoop {
218      get { return (SASEGASAMainLoop)VillageProcessor.Successor; }
219    }
220    [Storable]
221    private BestAverageWorstQualityAnalyzer villageQualityAnalyzer;
222    [Storable]
223    private BestAverageWorstQualityAnalyzer qualityAnalyzer;
224    [Storable]
225    private ValueAnalyzer villageSelectionPressureAnalyzer;
226    [Storable]
227    private ValueAnalyzer selectionPressureAnalyzer;
228    #endregion
229
230    [StorableConstructor]
231    private SASEGASA(bool deserializing) : base(deserializing) { }
232    public SASEGASA()
233      : base() {
234      Parameters.Add(new ValueParameter<IntValue>("Seed", "The random seed used to initialize the new pseudo random number generator.", new IntValue(0)));
235      Parameters.Add(new ValueParameter<BoolValue>("SetSeedRandomly", "True if the random seed should be set to a random value, otherwise false.", new BoolValue(true)));
236      Parameters.Add(new ValueParameter<IntValue>("NumberOfVillages", "The initial number of villages.", new IntValue(10)));
237      Parameters.Add(new ValueParameter<IntValue>("PopulationSize", "The size of the population of solutions.", new IntValue(100)));
238      Parameters.Add(new ValueParameter<IntValue>("MaximumGenerations", "The maximum number of generations that should be processed.", new IntValue(1000)));
239      Parameters.Add(new ConstrainedValueParameter<ISelector>("Selector", "The operator used to select solutions for reproduction."));
240      Parameters.Add(new ConstrainedValueParameter<ICrossover>("Crossover", "The operator used to cross solutions."));
241      Parameters.Add(new ValueParameter<PercentValue>("MutationProbability", "The probability that the mutation operator is applied on a solution.", new PercentValue(0.05)));
242      Parameters.Add(new OptionalConstrainedValueParameter<IManipulator>("Mutator", "The operator used to mutate solutions."));
243      Parameters.Add(new ValueParameter<IntValue>("Elites", "The numer of elite solutions which are kept in each generation.", new IntValue(1)));
244      Parameters.Add(new ValueParameter<BoolValue>("Parallel", "True if the villages should be run in parallel (also requires a parallel engine)", new BoolValue(false)));
245      Parameters.Add(new ValueLookupParameter<DoubleValue>("SuccessRatio", "The ratio of successful to total children that should be achieved.", new DoubleValue(1)));
246      Parameters.Add(new ValueLookupParameter<DoubleValue>("ComparisonFactorLowerBound", "The lower bound of the comparison factor (start).", new DoubleValue(0.3)));
247      Parameters.Add(new ValueLookupParameter<DoubleValue>("ComparisonFactorUpperBound", "The upper bound of the comparison factor (end).", new DoubleValue(0.7)));
248      Parameters.Add(new OptionalConstrainedValueParameter<IDiscreteDoubleValueModifier>("ComparisonFactorModifier", "The operator used to modify the comparison factor.", new ItemSet<IDiscreteDoubleValueModifier>(new IDiscreteDoubleValueModifier[] { new LinearDiscreteDoubleValueModifier() }), new LinearDiscreteDoubleValueModifier()));
249      Parameters.Add(new ValueLookupParameter<DoubleValue>("MaximumSelectionPressure", "The maximum selection pressure that terminates the algorithm.", new DoubleValue(100)));
250      Parameters.Add(new ValueLookupParameter<DoubleValue>("FinalMaximumSelectionPressure", "The maximum selection pressure used when there is only one village left.", new DoubleValue(100)));
251      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.", new BoolValue(false)));
252      Parameters.Add(new ValueLookupParameter<IntValue>("SelectedParents", "Should be about 2 * PopulationSize, for large problems use a smaller value to decrease memory footprint.", new IntValue(200)));
253      Parameters.Add(new ValueParameter<MultiAnalyzer>("Analyzer", "The operator used to analyze the villages.", new MultiAnalyzer()));
254      Parameters.Add(new ValueParameter<MultiAnalyzer>("VillageAnalyzer", "The operator used to analyze each village.", new MultiAnalyzer()));
255     
256      RandomCreator randomCreator = new RandomCreator();
257      SubScopesCreator populationCreator = new SubScopesCreator();
258      UniformSubScopesProcessor ussp1 = new UniformSubScopesProcessor();
259      SolutionsCreator solutionsCreator = new SolutionsCreator();
260      SASEGASAMainLoop mainLoop = new SASEGASAMainLoop();
261      OperatorGraph.InitialOperator = randomCreator;
262
263      randomCreator.RandomParameter.ActualName = "Random";
264      randomCreator.SeedParameter.ActualName = SeedParameter.Name;
265      randomCreator.SeedParameter.Value = null;
266      randomCreator.SetSeedRandomlyParameter.ActualName = SetSeedRandomlyParameter.Name;
267      randomCreator.SetSeedRandomlyParameter.Value = null;
268      randomCreator.Successor = populationCreator;
269
270      populationCreator.NumberOfSubScopesParameter.ActualName = NumberOfVillagesParameter.Name;
271      populationCreator.Successor = ussp1;
272
273      ussp1.Parallel = null;
274      ussp1.ParallelParameter.ActualName = ParallelParameter.Name;
275      ussp1.Operator = solutionsCreator;
276      ussp1.Successor = mainLoop;
277
278      solutionsCreator.NumberOfSolutionsParameter.ActualName = PopulationSizeParameter.Name;
279      solutionsCreator.Successor = null;
280
281      mainLoop.NumberOfVillagesParameter.ActualName = NumberOfVillagesParameter.Name;
282      mainLoop.SelectorParameter.ActualName = SelectorParameter.Name;
283      mainLoop.CrossoverParameter.ActualName = CrossoverParameter.Name;
284      mainLoop.ElitesParameter.ActualName = ElitesParameter.Name;
285      mainLoop.MutatorParameter.ActualName = MutatorParameter.Name;
286      mainLoop.MutationProbabilityParameter.ActualName = MutationProbabilityParameter.Name;
287      mainLoop.RandomParameter.ActualName = randomCreator.RandomParameter.ActualName;
288      mainLoop.ResultsParameter.ActualName = "Results";
289      mainLoop.SuccessRatioParameter.ActualName = SuccessRatioParameter.Name;
290      mainLoop.ComparisonFactorLowerBoundParameter.ActualName = ComparisonFactorLowerBoundParameter.Name;
291      mainLoop.ComparisonFactorModifierParameter.ActualName = ComparisonFactorModifierParameter.Name;
292      mainLoop.ComparisonFactorUpperBoundParameter.ActualName = ComparisonFactorUpperBoundParameter.Name;
293      mainLoop.MaximumSelectionPressureParameter.ActualName = MaximumSelectionPressureParameter.Name;
294      mainLoop.FinalMaximumSelectionPressureParameter.ActualName = FinalMaximumSelectionPressureParameter.Name;
295      mainLoop.MaximumGenerationsParameter.ActualName = MaximumGenerationsParameter.Name;
296      mainLoop.OffspringSelectionBeforeMutationParameter.ActualName = OffspringSelectionBeforeMutationParameter.Name;
297      mainLoop.Successor = null;
298
299      foreach (ISelector selector in ApplicationManager.Manager.GetInstances<ISelector>().Where(x => !(x is IMultiObjectiveSelector)).OrderBy(x => x.Name))
300        SelectorParameter.ValidValues.Add(selector);
301      ISelector proportionalSelector = SelectorParameter.ValidValues.FirstOrDefault(x => x.GetType().Name.Equals("ProportionalSelector"));
302      if (proportionalSelector != null) SelectorParameter.Value = proportionalSelector;
303
304      ParameterizeSelectors();
305
306      foreach (IDiscreteDoubleValueModifier modifier in ApplicationManager.Manager.GetInstances<IDiscreteDoubleValueModifier>().OrderBy(x => x.Name))
307        ComparisonFactorModifierParameter.ValidValues.Add(modifier);
308      IDiscreteDoubleValueModifier linearModifier = ComparisonFactorModifierParameter.ValidValues.FirstOrDefault(x => x.GetType().Name.Equals("LinearDiscreteDoubleValueModifier"));
309      if (linearModifier != null) ComparisonFactorModifierParameter.Value = linearModifier;
310      ParameterizeComparisonFactorModifiers();
311
312      qualityAnalyzer = new BestAverageWorstQualityAnalyzer();
313      villageQualityAnalyzer = new BestAverageWorstQualityAnalyzer();
314      selectionPressureAnalyzer = new ValueAnalyzer();
315      villageSelectionPressureAnalyzer = new ValueAnalyzer();
316      ParameterizeAnalyzers();
317      UpdateAnalyzers();
318
319      Initialize();
320    }
321
322    public override IDeepCloneable Clone(Cloner cloner) {
323      SASEGASA clone = (SASEGASA)base.Clone(cloner);
324      clone.qualityAnalyzer = (BestAverageWorstQualityAnalyzer)cloner.Clone(qualityAnalyzer);
325      clone.villageQualityAnalyzer = (BestAverageWorstQualityAnalyzer)cloner.Clone(villageQualityAnalyzer);
326      clone.selectionPressureAnalyzer = (ValueAnalyzer)cloner.Clone(selectionPressureAnalyzer);
327      clone.villageSelectionPressureAnalyzer = (ValueAnalyzer)cloner.Clone(villageSelectionPressureAnalyzer);
328      clone.Initialize();
329      return clone;
330    }
331
332    public override void Prepare() {
333      if (Problem != null) base.Prepare();
334    }
335
336    #region Events
337    protected override void OnProblemChanged() {
338      ParameterizeStochasticOperator(Problem.SolutionCreator);
339      ParameterizeStochasticOperator(Problem.Evaluator);
340      foreach (IOperator op in Problem.Operators) ParameterizeStochasticOperator(op);
341      ParameterizeSolutionsCreator();
342      ParameterizeMainLoop();
343      ParameterizeSelectors();
344      ParameterizeAnalyzers();
345      UpdateCrossovers();
346      UpdateMutators();
347      UpdateAnalyzers();
348      Problem.Evaluator.QualityParameter.ActualNameChanged += new EventHandler(Evaluator_QualityParameter_ActualNameChanged);
349      base.OnProblemChanged();
350    }
351
352    protected override void Problem_SolutionCreatorChanged(object sender, EventArgs e) {
353      ParameterizeStochasticOperator(Problem.SolutionCreator);
354      ParameterizeSolutionsCreator();
355      base.Problem_SolutionCreatorChanged(sender, e);
356    }
357    protected override void Problem_EvaluatorChanged(object sender, EventArgs e) {
358      ParameterizeStochasticOperator(Problem.Evaluator);
359      ParameterizeSolutionsCreator();
360      ParameterizeMainLoop();
361      ParameterizeSelectors();
362      ParameterizeAnalyzers();
363      Problem.Evaluator.QualityParameter.ActualNameChanged += new EventHandler(Evaluator_QualityParameter_ActualNameChanged);
364      base.Problem_EvaluatorChanged(sender, e);
365    }
366    protected override void Problem_OperatorsChanged(object sender, EventArgs e) {
367      foreach (IOperator op in Problem.Operators) ParameterizeStochasticOperator(op);
368      UpdateCrossovers();
369      UpdateMutators();
370      UpdateAnalyzers();
371      base.Problem_OperatorsChanged(sender, e);
372    }
373    private void ElitesParameter_ValueChanged(object sender, EventArgs e) {
374      Elites.ValueChanged += new EventHandler(Elites_ValueChanged);
375      ParameterizeSelectors();
376    }
377    private void Elites_ValueChanged(object sender, EventArgs e) {
378      ParameterizeSelectors();
379    }
380    private void PopulationSizeParameter_ValueChanged(object sender, EventArgs e) {
381      NumberOfVillages.ValueChanged += new EventHandler(PopulationSize_ValueChanged);
382      ParameterizeSelectors();
383    }
384    private void PopulationSize_ValueChanged(object sender, EventArgs e) {
385      ParameterizeSelectors();
386    }
387    private void Evaluator_QualityParameter_ActualNameChanged(object sender, EventArgs e) {
388      ParameterizeMainLoop();
389      ParameterizeSelectors();
390      ParameterizeAnalyzers();
391    }
392    private void MaximumGenerationsParameter_ValueChanged(object sender, EventArgs e) {
393      MaximumGenerations.ValueChanged += new EventHandler(MaximumGenerations_ValueChanged);
394      MaximumGenerations_ValueChanged(sender, e);
395    }
396    private void MaximumGenerations_ValueChanged(object sender, EventArgs e) {
397      if (MaximumGenerations.Value < NumberOfVillages.Value) NumberOfVillages.Value = MaximumGenerations.Value;
398      ParameterizeMainLoop();
399    }
400    private void NumberOfVillagesParameter_ValueChanged(object sender, EventArgs e) {
401      NumberOfVillages.ValueChanged += new EventHandler(NumberOfVillages_ValueChanged);
402      NumberOfVillages_ValueChanged(sender, e);
403    }
404    private void NumberOfVillages_ValueChanged(object sender, EventArgs e) {
405      if (NumberOfVillages.Value > MaximumGenerations.Value) MaximumGenerations.Value = NumberOfVillages.Value;
406      ParameterizeComparisonFactorModifiers();
407      ParameterizeMainLoop();
408    }
409    #endregion
410
411    #region Helpers
412    [StorableHook(HookType.AfterDeserialization)]
413    private void Initialize() {
414      NumberOfVillagesParameter.ValueChanged += new EventHandler(NumberOfVillagesParameter_ValueChanged);
415      NumberOfVillages.ValueChanged += new EventHandler(NumberOfVillages_ValueChanged);
416      PopulationSizeParameter.ValueChanged += new EventHandler(PopulationSizeParameter_ValueChanged);
417      PopulationSize.ValueChanged += new EventHandler(PopulationSize_ValueChanged);
418      ElitesParameter.ValueChanged += new EventHandler(ElitesParameter_ValueChanged);
419      Elites.ValueChanged += new EventHandler(Elites_ValueChanged);
420      MaximumGenerationsParameter.ValueChanged += new EventHandler(MaximumGenerationsParameter_ValueChanged);
421      MaximumGenerations.ValueChanged += new EventHandler(MaximumGenerations_ValueChanged);
422      if (Problem != null) {
423        Problem.Evaluator.QualityParameter.ActualNameChanged += new EventHandler(Evaluator_QualityParameter_ActualNameChanged);
424      }
425    }
426    private void ParameterizeSolutionsCreator() {
427      SolutionsCreator.EvaluatorParameter.ActualName = Problem.EvaluatorParameter.Name;
428      SolutionsCreator.SolutionCreatorParameter.ActualName = Problem.SolutionCreatorParameter.Name;
429    }
430    private void ParameterizeMainLoop() {
431      MainLoop.BestKnownQualityParameter.ActualName = Problem.BestKnownQualityParameter.Name;
432      MainLoop.EvaluatorParameter.ActualName = Problem.EvaluatorParameter.Name;
433      MainLoop.MaximizationParameter.ActualName = Problem.MaximizationParameter.Name;
434      MainLoop.QualityParameter.ActualName = Problem.Evaluator.QualityParameter.ActualName;
435      MainLoop.MigrationIntervalParameter.Value = new IntValue(MaximumGenerations.Value / NumberOfVillages.Value);
436    }
437    private void ParameterizeStochasticOperator(IOperator op) {
438      if (op is IStochasticOperator)
439        ((IStochasticOperator)op).RandomParameter.ActualName = RandomCreator.RandomParameter.ActualName;
440    }
441    private void ParameterizeSelectors() {
442      foreach (ISelector selector in SelectorParameter.ValidValues) {
443        selector.CopySelected = new BoolValue(true);
444        selector.NumberOfSelectedSubScopesParameter.Value = null;
445        selector.NumberOfSelectedSubScopesParameter.ActualName = SelectedParentsParameter.Name;
446        ParameterizeStochasticOperator(selector);
447      }
448      if (Problem != null) {
449        foreach (ISingleObjectiveSelector selector in SelectorParameter.ValidValues.OfType<ISingleObjectiveSelector>()) {
450          selector.MaximizationParameter.ActualName = Problem.MaximizationParameter.Name;
451          selector.QualityParameter.ActualName = Problem.Evaluator.QualityParameter.ActualName;
452        }
453      }
454    }
455    private void ParameterizeAnalyzers() {
456      villageQualityAnalyzer.ResultsParameter.ActualName = "Results";
457      villageQualityAnalyzer.QualityParameter.Depth = 1;
458      qualityAnalyzer.ResultsParameter.ActualName = "Results";
459      qualityAnalyzer.QualityParameter.Depth = 2;
460
461      villageSelectionPressureAnalyzer.ResultsParameter.ActualName = "Results";
462      villageSelectionPressureAnalyzer.Name = "SelectionPressure Analyzer";
463      villageSelectionPressureAnalyzer.ValueParameter.Depth = 0;
464      villageSelectionPressureAnalyzer.ValueParameter.ActualName = "SelectionPressure";
465      villageSelectionPressureAnalyzer.ValuesParameter.ActualName = "Selection Pressure History";
466
467      selectionPressureAnalyzer.ResultsParameter.ActualName = "Results";
468      selectionPressureAnalyzer.Name = "SelectionPressure Analyzer";
469      selectionPressureAnalyzer.ValueParameter.Depth = 1;
470      selectionPressureAnalyzer.ValueParameter.ActualName = "SelectionPressure";
471      selectionPressureAnalyzer.ValuesParameter.ActualName = "Selection Pressure History";
472
473      if (Problem != null) {
474        villageQualityAnalyzer.MaximizationParameter.ActualName = Problem.MaximizationParameter.Name;
475        villageQualityAnalyzer.QualityParameter.ActualName = Problem.Evaluator.QualityParameter.ActualName;
476        villageQualityAnalyzer.BestKnownQualityParameter.ActualName = Problem.BestKnownQualityParameter.Name;
477
478        qualityAnalyzer.MaximizationParameter.ActualName = Problem.MaximizationParameter.Name;
479        qualityAnalyzer.QualityParameter.ActualName = Problem.Evaluator.QualityParameter.ActualName;
480        qualityAnalyzer.BestKnownQualityParameter.ActualName = Problem.BestKnownQualityParameter.Name;
481      }
482    }
483    private void ParameterizeComparisonFactorModifiers() {
484      foreach (IDiscreteDoubleValueModifier modifier in ComparisonFactorModifierParameter.ValidValues) {
485        modifier.IndexParameter.ActualName = "Reunifications";
486        modifier.StartIndexParameter.Value = new IntValue(0);
487        modifier.StartValueParameter.ActualName = ComparisonFactorLowerBoundParameter.Name;
488        modifier.EndIndexParameter.Value = new IntValue(NumberOfVillages.Value - 1);
489        modifier.EndValueParameter.ActualName = ComparisonFactorUpperBoundParameter.Name;
490        modifier.ValueParameter.ActualName = "ComparisonFactor";
491      }
492    }
493    private void UpdateCrossovers() {
494      ICrossover oldCrossover = CrossoverParameter.Value;
495      CrossoverParameter.ValidValues.Clear();
496      foreach (ICrossover crossover in Problem.Operators.OfType<ICrossover>().OrderBy(x => x.Name))
497        CrossoverParameter.ValidValues.Add(crossover);
498      if (oldCrossover != null) {
499        ICrossover crossover = CrossoverParameter.ValidValues.FirstOrDefault(x => x.GetType() == oldCrossover.GetType());
500        if (crossover != null) CrossoverParameter.Value = crossover;
501      }
502    }
503    private void UpdateMutators() {
504      IManipulator oldMutator = MutatorParameter.Value;
505      MutatorParameter.ValidValues.Clear();
506      foreach (IManipulator mutator in Problem.Operators.OfType<IManipulator>().OrderBy(x => x.Name))
507        MutatorParameter.ValidValues.Add(mutator);
508      if (oldMutator != null) {
509        IManipulator mutator = MutatorParameter.ValidValues.FirstOrDefault(x => x.GetType() == oldMutator.GetType());
510        if (mutator != null) MutatorParameter.Value = mutator;
511      }
512    }
513    private void UpdateAnalyzers() {
514      VillageAnalyzer.Operators.Clear();
515      Analyzer.Operators.Clear();
516      VillageAnalyzer.Operators.Add(villageQualityAnalyzer);
517      VillageAnalyzer.Operators.Add(villageSelectionPressureAnalyzer);
518      Analyzer.Operators.Add(qualityAnalyzer);
519      Analyzer.Operators.Add(selectionPressureAnalyzer);
520      if (Problem != null) {
521        foreach (IAnalyzer analyzer in Problem.Operators.OfType<IAnalyzer>().OrderBy(x => x.Name)) {
522          foreach (IScopeTreeLookupParameter param in analyzer.Parameters.OfType<IScopeTreeLookupParameter>())
523            param.Depth = 2;
524          Analyzer.Operators.Add(analyzer);
525        }
526      }
527    }
528    #endregion
529  }
530}
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