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source: trunk/sources/HeuristicLab.Algorithms.EvolutionStrategy/3.3/EvolutionStrategyMainLoop.cs @ 3750

Last change on this file since 3750 was 3750, checked in by abeham, 14 years ago

#893

  • Fixed wiring of iteration based operators like the michalewicz manipulators for real vector encoding
File size: 29.0 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 HeuristicLab.Analysis;
23using HeuristicLab.Common;
24using HeuristicLab.Core;
25using HeuristicLab.Data;
26using HeuristicLab.Operators;
27using HeuristicLab.Optimization.Operators;
28using HeuristicLab.Parameters;
29using HeuristicLab.Persistence.Default.CompositeSerializers.Storable;
30using HeuristicLab.Selection;
31
32namespace HeuristicLab.Algorithms.EvolutionStrategy {
33  /// <summary>
34  /// An operator which represents the main loop of an evolution strategy (EvolutionStrategy).
35  /// </summary>
36  [Item("EvolutionStrategyMainLoop", "An operator which represents the main loop of an evolution strategy (EvolutionStrategy).")]
37  [StorableClass]
38  public sealed class EvolutionStrategyMainLoop : AlgorithmOperator {
39    #region Parameter properties
40    public ValueLookupParameter<IRandom> RandomParameter {
41      get { return (ValueLookupParameter<IRandom>)Parameters["Random"]; }
42    }
43    public ValueLookupParameter<BoolValue> MaximizationParameter {
44      get { return (ValueLookupParameter<BoolValue>)Parameters["Maximization"]; }
45    }
46    public ScopeTreeLookupParameter<DoubleValue> QualityParameter {
47      get { return (ScopeTreeLookupParameter<DoubleValue>)Parameters["Quality"]; }
48    }
49    public ValueLookupParameter<DoubleValue> BestKnownQualityParameter {
50      get { return (ValueLookupParameter<DoubleValue>)Parameters["BestKnownQuality"]; }
51    }
52    public ValueLookupParameter<IntValue> PopulationSizeParameter {
53      get { return (ValueLookupParameter<IntValue>)Parameters["PopulationSize"]; }
54    }
55    public ValueLookupParameter<IntValue> ParentsPerChildParameter {
56      get { return (ValueLookupParameter<IntValue>)Parameters["ParentsPerChild"]; }
57    }
58    public ValueLookupParameter<IntValue> ChildrenParameter {
59      get { return (ValueLookupParameter<IntValue>)Parameters["Children"]; }
60    }
61    public ValueLookupParameter<BoolValue> PlusSelectionParameter {
62      get { return (ValueLookupParameter<BoolValue>)Parameters["PlusSelection"]; }
63    }
64    public ValueLookupParameter<IntValue> MaximumGenerationsParameter {
65      get { return (ValueLookupParameter<IntValue>)Parameters["MaximumGenerations"]; }
66    }
67    public ValueLookupParameter<IOperator> MutatorParameter {
68      get { return (ValueLookupParameter<IOperator>)Parameters["Mutator"]; }
69    }
70    public ValueLookupParameter<IOperator> RecombinatorParameter {
71      get { return (ValueLookupParameter<IOperator>)Parameters["Recombinator"]; }
72    }
73    public ValueLookupParameter<IOperator> EvaluatorParameter {
74      get { return (ValueLookupParameter<IOperator>)Parameters["Evaluator"]; }
75    }
76    public ValueLookupParameter<VariableCollection> ResultsParameter {
77      get { return (ValueLookupParameter<VariableCollection>)Parameters["Results"]; }
78    }
79    public ValueLookupParameter<IOperator> AnalyzerParameter {
80      get { return (ValueLookupParameter<IOperator>)Parameters["Analyzer"]; }
81    }
82    private ScopeParameter CurrentScopeParameter {
83      get { return (ScopeParameter)Parameters["CurrentScope"]; }
84    }
85    private ValueLookupParameter<IOperator> StrategyParameterManipulatorParameter {
86      get { return (ValueLookupParameter<IOperator>)Parameters["StrategyParameterManipulator"]; }
87    }
88    private ValueLookupParameter<IOperator> StrategyParameterCrossoverParameter {
89      get { return (ValueLookupParameter<IOperator>)Parameters["StrategyParameterCrossover"]; }
90    }
91
92    public IScope CurrentScope {
93      get { return CurrentScopeParameter.ActualValue; }
94    }
95    #endregion
96
97    [StorableConstructor]
98    private EvolutionStrategyMainLoop(bool deserializing) : base() { }
99    public EvolutionStrategyMainLoop()
100      : base() {
101      Initialize();
102    }
103
104    private void Initialize() {
105      #region Create parameters
106      Parameters.Add(new ValueLookupParameter<IRandom>("Random", "A pseudo random number generator."));
107      Parameters.Add(new ValueLookupParameter<BoolValue>("Maximization", "True if the problem is a maximization problem, otherwise false."));
108      Parameters.Add(new ScopeTreeLookupParameter<DoubleValue>("Quality", "The value which represents the quality of a solution."));
109      Parameters.Add(new ValueLookupParameter<DoubleValue>("BestKnownQuality", "The best known quality value found so far."));
110      Parameters.Add(new ValueLookupParameter<IntValue>("PopulationSize", "µ (mu) - the size of the population."));
111      Parameters.Add(new ValueLookupParameter<IntValue>("ParentsPerChild", "ρ (rho) - how many parents should be recombined."));
112      Parameters.Add(new ValueLookupParameter<IntValue>("Children", "λ (lambda) - the size of the offspring population."));
113      Parameters.Add(new ValueLookupParameter<IntValue>("MaximumGenerations", "The maximum number of generations which should be processed."));
114      Parameters.Add(new ValueLookupParameter<BoolValue>("PlusSelection", "True for plus selection (elitist population), false for comma selection (non-elitist population)."));
115      Parameters.Add(new ValueLookupParameter<IOperator>("Mutator", "The operator used to mutate solutions."));
116      Parameters.Add(new ValueLookupParameter<IOperator>("Recombinator", "The operator used to cross solutions."));
117      Parameters.Add(new ValueLookupParameter<IOperator>("Evaluator", "The operator used to evaluate solutions."));
118      Parameters.Add(new ValueLookupParameter<VariableCollection>("Results", "The variable collection where results should be stored."));
119      Parameters.Add(new ValueLookupParameter<IOperator>("Analyzer", "The operator used to analyze each generation."));
120      Parameters.Add(new ScopeParameter("CurrentScope", "The current scope which represents a population of solutions on which the EvolutionStrategy should be applied."));
121      Parameters.Add(new ValueLookupParameter<IOperator>("StrategyParameterManipulator", "The operator to mutate the endogeneous strategy parameters."));
122      Parameters.Add(new ValueLookupParameter<IOperator>("StrategyParameterCrossover", "The operator to cross the endogeneous strategy parameters."));
123      #endregion
124
125      #region Create operators
126      VariableCreator variableCreator = new VariableCreator();
127      ResultsCollector resultsCollector1 = new ResultsCollector();
128      Placeholder analyzer1 = new Placeholder();
129      WithoutRepeatingBatchedRandomSelector selector = new WithoutRepeatingBatchedRandomSelector();
130      SubScopesProcessor subScopesProcessor1 = new SubScopesProcessor();
131      Comparator useRecombinationComparator = new Comparator();
132      ConditionalBranch useRecombinationBranch = new ConditionalBranch();
133      ChildrenCreator childrenCreator = new ChildrenCreator();
134      UniformSubScopesProcessor uniformSubScopesProcessor1 = new UniformSubScopesProcessor();
135      Placeholder recombinator = new Placeholder();
136      Placeholder strategyRecombinator = new Placeholder();
137      Placeholder strategyMutator1 = new Placeholder();
138      Placeholder mutator1 = new Placeholder();
139      Placeholder evaluator1 = new Placeholder();
140      SubScopesRemover subScopesRemover = new SubScopesRemover();
141      UniformSubScopesProcessor uniformSubScopesProcessor2 = new UniformSubScopesProcessor();
142      Placeholder strategyMutator2 = new Placeholder();
143      Placeholder mutator2 = new Placeholder();
144      Placeholder evaluator2 = new Placeholder();
145      ConditionalBranch plusOrCommaReplacementBranch = new ConditionalBranch();
146      MergingReducer plusReplacement = new MergingReducer();
147      RightReducer commaReplacement = new RightReducer();
148      BestSelector bestSelector = new BestSelector();
149      RightReducer rightReducer = new RightReducer();
150      IntCounter intCounter = new IntCounter();
151      Comparator comparator = new Comparator();
152      ResultsCollector resultsCollector2 = new ResultsCollector();
153      Placeholder analyzer2 = new Placeholder();
154      ConditionalBranch conditionalBranch = new ConditionalBranch();
155
156      variableCreator.CollectedValues.Add(new ValueParameter<IntValue>("Generations", new IntValue(0))); // Class EvolutionStrategy expects this to be called Generations
157
158      resultsCollector1.CollectedValues.Add(new LookupParameter<IntValue>("Generations"));
159      resultsCollector1.ResultsParameter.ActualName = "Results";
160
161      analyzer1.Name = "Analyzer (placeholder)";
162      analyzer1.OperatorParameter.ActualName = AnalyzerParameter.Name;
163
164      selector.Name = "ES Random Selector";
165      selector.ParentsPerChildParameter.ActualName = ParentsPerChildParameter.Name;
166      selector.ChildrenParameter.ActualName = ChildrenParameter.Name;
167
168      useRecombinationComparator.Name = "ParentsPerChild > 1";
169      useRecombinationComparator.LeftSideParameter.ActualName = ParentsPerChildParameter.Name;
170      useRecombinationComparator.RightSideParameter.Value = new IntValue(1);
171      useRecombinationComparator.Comparison = new Comparison(ComparisonType.Greater);
172      useRecombinationComparator.ResultParameter.ActualName = "UseRecombination";
173
174      useRecombinationBranch.Name = "Use Recombination?";
175      useRecombinationBranch.ConditionParameter.ActualName = "UseRecombination";
176
177      childrenCreator.ParentsPerChild = null;
178      childrenCreator.ParentsPerChildParameter.ActualName = ParentsPerChildParameter.Name;
179
180      recombinator.Name = "Recombinator (placeholder)";
181      recombinator.OperatorParameter.ActualName = RecombinatorParameter.Name;
182
183      strategyRecombinator.Name = "Strategy Parameter Recombinator (placeholder)";
184      strategyRecombinator.OperatorParameter.ActualName = StrategyParameterCrossoverParameter.Name;
185
186      strategyMutator1.Name = "Strategy Parameter Manipulator (placeholder)";
187      strategyMutator1.OperatorParameter.ActualName = StrategyParameterManipulatorParameter.Name;
188
189      mutator1.Name = "Mutator (placeholder)";
190      mutator1.OperatorParameter.ActualName = MutatorParameter.Name;
191
192      evaluator1.Name = "Evaluator (placeholder)";
193      evaluator1.OperatorParameter.ActualName = EvaluatorParameter.Name;
194
195      subScopesRemover.RemoveAllSubScopes = true;
196
197      strategyMutator2.Name = "Strategy Parameter Manipulator (placeholder)";
198      strategyMutator2.OperatorParameter.ActualName = StrategyParameterManipulatorParameter.Name;
199
200      mutator2.Name = "Mutator (placeholder)";
201      mutator2.OperatorParameter.ActualName = MutatorParameter.Name;
202
203      evaluator2.Name = "Evaluator (placeholder)";
204      evaluator2.OperatorParameter.ActualName = EvaluatorParameter.Name;
205
206      plusOrCommaReplacementBranch.ConditionParameter.ActualName = PlusSelectionParameter.Name;
207
208      bestSelector.CopySelected = new BoolValue(false);
209      bestSelector.MaximizationParameter.ActualName = MaximizationParameter.Name;
210      bestSelector.NumberOfSelectedSubScopesParameter.ActualName = PopulationSizeParameter.Name;
211      bestSelector.QualityParameter.ActualName = QualityParameter.Name;
212
213      intCounter.Increment = new IntValue(1);
214      intCounter.ValueParameter.ActualName = "Generations";
215
216      comparator.Comparison = new Comparison(ComparisonType.GreaterOrEqual);
217      comparator.LeftSideParameter.ActualName = "Generations";
218      comparator.ResultParameter.ActualName = "Terminate";
219      comparator.RightSideParameter.ActualName = MaximumGenerationsParameter.Name;
220
221      resultsCollector2.CollectedValues.Add(new LookupParameter<IntValue>("Generations"));
222      resultsCollector2.ResultsParameter.ActualName = "Results";
223
224      analyzer2.Name = "Analyzer (placeholder)";
225      analyzer2.OperatorParameter.ActualName = AnalyzerParameter.Name;
226
227      conditionalBranch.ConditionParameter.ActualName = "Terminate";
228      #endregion
229
230      #region Create operator graph
231      OperatorGraph.InitialOperator = variableCreator;
232      variableCreator.Successor = resultsCollector1;
233      resultsCollector1.Successor = analyzer1;
234      analyzer1.Successor = selector;
235      selector.Successor = subScopesProcessor1;
236      subScopesProcessor1.Operators.Add(new EmptyOperator());
237      subScopesProcessor1.Operators.Add(useRecombinationComparator);
238      subScopesProcessor1.Successor = plusOrCommaReplacementBranch;
239      useRecombinationComparator.Successor = useRecombinationBranch;
240      useRecombinationBranch.TrueBranch = childrenCreator;
241      useRecombinationBranch.FalseBranch = uniformSubScopesProcessor2;
242      useRecombinationBranch.Successor = null;
243      childrenCreator.Successor = uniformSubScopesProcessor1;
244      uniformSubScopesProcessor1.Operator = recombinator;
245      uniformSubScopesProcessor1.Successor = null;
246      recombinator.Successor = strategyRecombinator;
247      strategyRecombinator.Successor = strategyMutator1;
248      strategyMutator1.Successor = mutator1;
249      mutator1.Successor = evaluator1;
250      evaluator1.Successor = subScopesRemover;
251      subScopesRemover.Successor = null;
252      uniformSubScopesProcessor2.Operator = strategyMutator2;
253      uniformSubScopesProcessor2.Successor = null;
254      strategyMutator2.Successor = mutator2;
255      mutator2.Successor = evaluator2;
256      plusOrCommaReplacementBranch.TrueBranch = plusReplacement;
257      plusOrCommaReplacementBranch.FalseBranch = commaReplacement;
258      plusOrCommaReplacementBranch.Successor = bestSelector;
259      bestSelector.Successor = rightReducer;
260      rightReducer.Successor = intCounter;
261      intCounter.Successor = comparator;
262      comparator.Successor = resultsCollector2;
263      resultsCollector2.Successor = analyzer2;
264      analyzer2.Successor = conditionalBranch;
265      conditionalBranch.FalseBranch = selector;
266      conditionalBranch.TrueBranch = null;
267      conditionalBranch.Successor = null;
268      #endregion
269    }
270
271    public override IOperation Apply() {
272      if (MutatorParameter.ActualValue == null)
273        return null;
274      return base.Apply();
275    }
276  }
277}
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