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source: trunk/sources/HeuristicLab.Algorithms.EvolutionStrategy/3.3/EvolutionStrategyMainLoop.cs @ 9584

Last change on this file since 9584 was 9569, checked in by mkommend, 12 years ago

#2038: Added reevaluation of elites in ES, IslandGA, IslandOSGA, OSGA, SASEGASA, and RAPGA.
File size: 33.8 KB
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1#region License Information
2/* HeuristicLab
3 * Copyright (C) 2002-2013 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.Operators;
27using HeuristicLab.Parameters;
28using HeuristicLab.Persistence.Default.CompositeSerializers.Storable;
29using HeuristicLab.Selection;
30
31namespace HeuristicLab.Algorithms.EvolutionStrategy {
32  /// <summary>
33  /// An operator which represents the main loop of an evolution strategy (EvolutionStrategy).
34  /// </summary>
35  [Item("EvolutionStrategyMainLoop", "An operator which represents the main loop of an evolution strategy (EvolutionStrategy).")]
36  [StorableClass]
37  public sealed class EvolutionStrategyMainLoop : AlgorithmOperator {
38    #region Parameter properties
39    public ValueLookupParameter<IRandom> RandomParameter {
40      get { return (ValueLookupParameter<IRandom>)Parameters["Random"]; }
41    }
42    public ValueLookupParameter<BoolValue> MaximizationParameter {
43      get { return (ValueLookupParameter<BoolValue>)Parameters["Maximization"]; }
44    }
45    public ScopeTreeLookupParameter<DoubleValue> QualityParameter {
46      get { return (ScopeTreeLookupParameter<DoubleValue>)Parameters["Quality"]; }
47    }
48    public ValueLookupParameter<DoubleValue> BestKnownQualityParameter {
49      get { return (ValueLookupParameter<DoubleValue>)Parameters["BestKnownQuality"]; }
50    }
51    public ValueLookupParameter<IntValue> PopulationSizeParameter {
52      get { return (ValueLookupParameter<IntValue>)Parameters["PopulationSize"]; }
53    }
54    public ValueLookupParameter<IntValue> ParentsPerChildParameter {
55      get { return (ValueLookupParameter<IntValue>)Parameters["ParentsPerChild"]; }
56    }
57    public ValueLookupParameter<IntValue> ChildrenParameter {
58      get { return (ValueLookupParameter<IntValue>)Parameters["Children"]; }
59    }
60    public ValueLookupParameter<BoolValue> PlusSelectionParameter {
61      get { return (ValueLookupParameter<BoolValue>)Parameters["PlusSelection"]; }
62    }
63    public IValueLookupParameter<BoolValue> ReevaluateElitesParameter {
64      get { return (IValueLookupParameter<BoolValue>)Parameters["ReevaluateElites"]; }
65    }
66    public ValueLookupParameter<IntValue> MaximumGenerationsParameter {
67      get { return (ValueLookupParameter<IntValue>)Parameters["MaximumGenerations"]; }
68    }
69    public ValueLookupParameter<IOperator> MutatorParameter {
70      get { return (ValueLookupParameter<IOperator>)Parameters["Mutator"]; }
71    }
72    public ValueLookupParameter<IOperator> RecombinatorParameter {
73      get { return (ValueLookupParameter<IOperator>)Parameters["Recombinator"]; }
74    }
75    public ValueLookupParameter<IOperator> EvaluatorParameter {
76      get { return (ValueLookupParameter<IOperator>)Parameters["Evaluator"]; }
77    }
78    public ValueLookupParameter<VariableCollection> ResultsParameter {
79      get { return (ValueLookupParameter<VariableCollection>)Parameters["Results"]; }
80    }
81    public ValueLookupParameter<IOperator> AnalyzerParameter {
82      get { return (ValueLookupParameter<IOperator>)Parameters["Analyzer"]; }
83    }
84    public LookupParameter<IntValue> EvaluatedSolutionsParameter {
85      get { return (LookupParameter<IntValue>)Parameters["EvaluatedSolutions"]; }
86    }
87    private ScopeParameter CurrentScopeParameter {
88      get { return (ScopeParameter)Parameters["CurrentScope"]; }
89    }
90    private ValueLookupParameter<IOperator> StrategyParameterManipulatorParameter {
91      get { return (ValueLookupParameter<IOperator>)Parameters["StrategyParameterManipulator"]; }
92    }
93    private ValueLookupParameter<IOperator> StrategyParameterCrossoverParameter {
94      get { return (ValueLookupParameter<IOperator>)Parameters["StrategyParameterCrossover"]; }
95    }
96
97    public IScope CurrentScope {
98      get { return CurrentScopeParameter.ActualValue; }
99    }
100    #endregion
101
102    [StorableConstructor]
103    private EvolutionStrategyMainLoop(bool deserializing) : base(deserializing) { }
104    private EvolutionStrategyMainLoop(EvolutionStrategyMainLoop original, Cloner cloner)
105      : base(original, cloner) {
106    }
107    public override IDeepCloneable Clone(Cloner cloner) {
108      return new EvolutionStrategyMainLoop(this, cloner);
109    }
110    public EvolutionStrategyMainLoop()
111      : base() {
112      Initialize();
113    }
114
115    private void Initialize() {
116      #region Create parameters
117      Parameters.Add(new ValueLookupParameter<IRandom>("Random", "A pseudo random number generator."));
118      Parameters.Add(new ValueLookupParameter<BoolValue>("Maximization", "True if the problem is a maximization problem, otherwise false."));
119      Parameters.Add(new ScopeTreeLookupParameter<DoubleValue>("Quality", "The value which represents the quality of a solution."));
120      Parameters.Add(new ValueLookupParameter<DoubleValue>("BestKnownQuality", "The best known quality value found so far."));
121      Parameters.Add(new ValueLookupParameter<IntValue>("PopulationSize", "µ (mu) - the size of the population."));
122      Parameters.Add(new ValueLookupParameter<IntValue>("ParentsPerChild", "ρ (rho) - how many parents should be recombined."));
123      Parameters.Add(new ValueLookupParameter<IntValue>("Children", "λ (lambda) - the size of the offspring population."));
124      Parameters.Add(new ValueLookupParameter<IntValue>("MaximumGenerations", "The maximum number of generations which should be processed."));
125      Parameters.Add(new ValueLookupParameter<BoolValue>("PlusSelection", "True for plus selection (elitist population), false for comma selection (non-elitist population)."));
126      Parameters.Add(new ValueLookupParameter<BoolValue>("ReevaluateElites", "Flag to determine if elite individuals should be reevaluated (i.e., if stochastic fitness functions are used.)"));
127      Parameters.Add(new ValueLookupParameter<IOperator>("Mutator", "The operator used to mutate solutions."));
128      Parameters.Add(new ValueLookupParameter<IOperator>("Recombinator", "The operator used to cross solutions."));
129      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."));
130      Parameters.Add(new ValueLookupParameter<VariableCollection>("Results", "The variable collection where results should be stored."));
131      Parameters.Add(new ValueLookupParameter<IOperator>("Analyzer", "The operator used to analyze each generation."));
132      Parameters.Add(new LookupParameter<IntValue>("EvaluatedSolutions", "The number of times solutions have been evaluated."));
133      Parameters.Add(new ScopeParameter("CurrentScope", "The current scope which represents a population of solutions on which the EvolutionStrategy should be applied."));
134      Parameters.Add(new ValueLookupParameter<IOperator>("StrategyParameterManipulator", "The operator to mutate the endogeneous strategy parameters."));
135      Parameters.Add(new ValueLookupParameter<IOperator>("StrategyParameterCrossover", "The operator to cross the endogeneous strategy parameters."));
136      #endregion
137
138      #region Create operators
139      VariableCreator variableCreator = new VariableCreator();
140      ResultsCollector resultsCollector1 = new ResultsCollector();
141      Placeholder analyzer1 = new Placeholder();
142      WithoutRepeatingBatchedRandomSelector selector = new WithoutRepeatingBatchedRandomSelector();
143      SubScopesProcessor subScopesProcessor1 = new SubScopesProcessor();
144      Comparator useRecombinationComparator = new Comparator();
145      ConditionalBranch useRecombinationBranch = new ConditionalBranch();
146      ChildrenCreator childrenCreator = new ChildrenCreator();
147      UniformSubScopesProcessor uniformSubScopesProcessor1 = new UniformSubScopesProcessor();
148      Placeholder recombinator = new Placeholder();
149      Placeholder strategyRecombinator = new Placeholder();
150      Placeholder strategyMutator1 = new Placeholder();
151      Placeholder mutator1 = new Placeholder();
152      SubScopesRemover subScopesRemover = new SubScopesRemover();
153      UniformSubScopesProcessor uniformSubScopesProcessor2 = new UniformSubScopesProcessor();
154      Placeholder strategyMutator2 = new Placeholder();
155      Placeholder mutator2 = new Placeholder();
156      UniformSubScopesProcessor uniformSubScopesProcessor3 = new UniformSubScopesProcessor();
157      Placeholder evaluator = new Placeholder();
158      SubScopesCounter subScopesCounter = new SubScopesCounter();
159      ConditionalBranch plusOrCommaReplacementBranch = new ConditionalBranch();
160      MergingReducer plusReplacement = new MergingReducer();
161      RightReducer commaReplacement = new RightReducer();
162      BestSelector bestSelector = new BestSelector();
163      RightReducer rightReducer = new RightReducer();
164      IntCounter intCounter = new IntCounter();
165      Comparator comparator = new Comparator();
166      Placeholder analyzer2 = new Placeholder();
167      ConditionalBranch conditionalBranch = new ConditionalBranch();
168      ConditionalBranch reevaluateElitesBranch = new ConditionalBranch();
169      SubScopesProcessor subScopesProcessor2 = new SubScopesProcessor();
170      UniformSubScopesProcessor uniformSubScopesProcessor4 = new UniformSubScopesProcessor();
171      Placeholder evaluator2 = new Placeholder();
172      SubScopesCounter subScopesCounter2 = new SubScopesCounter();
173
174
175      variableCreator.CollectedValues.Add(new ValueParameter<IntValue>("Generations", new IntValue(0))); // Class EvolutionStrategy expects this to be called Generations
176
177      resultsCollector1.CollectedValues.Add(new LookupParameter<IntValue>("Generations"));
178      resultsCollector1.ResultsParameter.ActualName = "Results";
179
180      analyzer1.Name = "Analyzer (placeholder)";
181      analyzer1.OperatorParameter.ActualName = AnalyzerParameter.Name;
182
183      selector.Name = "ES Random Selector";
184      selector.RandomParameter.ActualName = RandomParameter.Name;
185      selector.ParentsPerChildParameter.ActualName = ParentsPerChildParameter.Name;
186      selector.ChildrenParameter.ActualName = ChildrenParameter.Name;
187
188      useRecombinationComparator.Name = "ParentsPerChild > 1";
189      useRecombinationComparator.LeftSideParameter.ActualName = ParentsPerChildParameter.Name;
190      useRecombinationComparator.RightSideParameter.Value = new IntValue(1);
191      useRecombinationComparator.Comparison = new Comparison(ComparisonType.Greater);
192      useRecombinationComparator.ResultParameter.ActualName = "UseRecombination";
193
194      useRecombinationBranch.Name = "Use Recombination?";
195      useRecombinationBranch.ConditionParameter.ActualName = "UseRecombination";
196
197      childrenCreator.ParentsPerChild = null;
198      childrenCreator.ParentsPerChildParameter.ActualName = ParentsPerChildParameter.Name;
199
200      recombinator.Name = "Recombinator (placeholder)";
201      recombinator.OperatorParameter.ActualName = RecombinatorParameter.Name;
202
203      strategyRecombinator.Name = "Strategy Parameter Recombinator (placeholder)";
204      strategyRecombinator.OperatorParameter.ActualName = StrategyParameterCrossoverParameter.Name;
205
206      strategyMutator1.Name = "Strategy Parameter Manipulator (placeholder)";
207      strategyMutator1.OperatorParameter.ActualName = StrategyParameterManipulatorParameter.Name;
208
209      mutator1.Name = "Mutator (placeholder)";
210      mutator1.OperatorParameter.ActualName = MutatorParameter.Name;
211
212      subScopesRemover.RemoveAllSubScopes = true;
213
214      strategyMutator2.Name = "Strategy Parameter Manipulator (placeholder)";
215      strategyMutator2.OperatorParameter.ActualName = StrategyParameterManipulatorParameter.Name;
216
217      mutator2.Name = "Mutator (placeholder)";
218      mutator2.OperatorParameter.ActualName = MutatorParameter.Name;
219
220      uniformSubScopesProcessor3.Parallel.Value = true;
221
222      evaluator.Name = "Evaluator (placeholder)";
223      evaluator.OperatorParameter.ActualName = EvaluatorParameter.Name;
224
225      subScopesCounter.Name = "Increment EvaluatedSolutions";
226      subScopesCounter.ValueParameter.ActualName = EvaluatedSolutionsParameter.Name;
227
228      plusOrCommaReplacementBranch.ConditionParameter.ActualName = PlusSelectionParameter.Name;
229
230      bestSelector.CopySelected = new BoolValue(false);
231      bestSelector.MaximizationParameter.ActualName = MaximizationParameter.Name;
232      bestSelector.NumberOfSelectedSubScopesParameter.ActualName = PopulationSizeParameter.Name;
233      bestSelector.QualityParameter.ActualName = QualityParameter.Name;
234
235      intCounter.Increment = new IntValue(1);
236      intCounter.ValueParameter.ActualName = "Generations";
237
238      comparator.Comparison = new Comparison(ComparisonType.GreaterOrEqual);
239      comparator.LeftSideParameter.ActualName = "Generations";
240      comparator.ResultParameter.ActualName = "Terminate";
241      comparator.RightSideParameter.ActualName = MaximumGenerationsParameter.Name;
242
243      analyzer2.Name = "Analyzer (placeholder)";
244      analyzer2.OperatorParameter.ActualName = AnalyzerParameter.Name;
245
246      conditionalBranch.ConditionParameter.ActualName = "Terminate";
247
248      reevaluateElitesBranch.ConditionParameter.ActualName = "ReevaluateElites";
249      reevaluateElitesBranch.Name = "Reevaluate elites ?";
250
251      uniformSubScopesProcessor4.Parallel.Value = true;
252
253      evaluator2.Name = "Evaluator (placeholder)";
254      evaluator2.OperatorParameter.ActualName = EvaluatorParameter.Name;
255
256      subScopesCounter2.Name = "Increment EvaluatedSolutions";
257      subScopesCounter2.ValueParameter.ActualName = EvaluatedSolutionsParameter.Name;
258      #endregion
259
260      #region Create operator graph
261      OperatorGraph.InitialOperator = variableCreator;
262      variableCreator.Successor = resultsCollector1;
263      resultsCollector1.Successor = analyzer1;
264      analyzer1.Successor = selector;
265      selector.Successor = subScopesProcessor1;
266      subScopesProcessor1.Operators.Add(new EmptyOperator());
267      subScopesProcessor1.Operators.Add(useRecombinationComparator);
268      subScopesProcessor1.Successor = plusOrCommaReplacementBranch;
269      useRecombinationComparator.Successor = useRecombinationBranch;
270      useRecombinationBranch.TrueBranch = childrenCreator;
271      useRecombinationBranch.FalseBranch = uniformSubScopesProcessor2;
272      useRecombinationBranch.Successor = uniformSubScopesProcessor3;
273      childrenCreator.Successor = uniformSubScopesProcessor1;
274      uniformSubScopesProcessor1.Operator = recombinator;
275      uniformSubScopesProcessor1.Successor = null;
276      recombinator.Successor = strategyRecombinator;
277      strategyRecombinator.Successor = strategyMutator1;
278      strategyMutator1.Successor = mutator1;
279      mutator1.Successor = subScopesRemover;
280      subScopesRemover.Successor = null;
281      uniformSubScopesProcessor2.Operator = strategyMutator2;
282      uniformSubScopesProcessor2.Successor = null;
283      strategyMutator2.Successor = mutator2;
284      mutator2.Successor = null;
285      uniformSubScopesProcessor3.Operator = evaluator;
286      uniformSubScopesProcessor3.Successor = subScopesCounter;
287      evaluator.Successor = null;
288      subScopesCounter.Successor = null;
289
290      plusOrCommaReplacementBranch.TrueBranch = reevaluateElitesBranch;
291      reevaluateElitesBranch.TrueBranch = subScopesProcessor2;
292      reevaluateElitesBranch.FalseBranch = null;
293      subScopesProcessor2.Operators.Add(uniformSubScopesProcessor4);
294      subScopesProcessor2.Operators.Add(new EmptyOperator());
295      uniformSubScopesProcessor4.Operator = evaluator2;
296      uniformSubScopesProcessor4.Successor = subScopesCounter2;
297      subScopesCounter2.Successor = null;
298      reevaluateElitesBranch.Successor = plusReplacement;
299
300      plusOrCommaReplacementBranch.FalseBranch = commaReplacement;
301      plusOrCommaReplacementBranch.Successor = bestSelector;
302      bestSelector.Successor = rightReducer;
303      rightReducer.Successor = intCounter;
304      intCounter.Successor = comparator;
305      comparator.Successor = analyzer2;
306      analyzer2.Successor = conditionalBranch;
307      conditionalBranch.FalseBranch = selector;
308      conditionalBranch.TrueBranch = null;
309      conditionalBranch.Successor = null;
310      #endregion
311    }
312
313    public override IOperation Apply() {
314      if (MutatorParameter.ActualValue == null)
315        return null;
316      return base.Apply();
317    }
318  }
319}
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