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source: branches/2913_MatlabScriptProblemInstanceProvider/HeuristicLab.Algorithms.OffspringSelectionGeneticAlgorithm/3.3/OffspringSelectionGeneticAlgorithmMainLoop.cs @ 15889

Last change on this file since 15889 was 15583, checked in by swagner, 7 years ago

#2640: Updated year of copyrights in license headers
File size: 17.1 KB
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1#region License Information
2/* HeuristicLab
3 * Copyright (C) 2002-2018 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;
29
30namespace HeuristicLab.Algorithms.OffspringSelectionGeneticAlgorithm {
31  /// <summary>
32  /// An operator which represents the main loop of an offspring selection genetic algorithm.
33  /// </summary>
34  [Item("OffspringSelectionGeneticAlgorithmMainLoop", "An operator which represents the main loop of an offspring selection genetic algorithm.")]
35  [StorableClass]
36  public sealed class OffspringSelectionGeneticAlgorithmMainLoop : AlgorithmOperator {
37    #region Parameter properties
38    public ValueLookupParameter<IRandom> RandomParameter {
39      get { return (ValueLookupParameter<IRandom>)Parameters["Random"]; }
40    }
41    public ValueLookupParameter<BoolValue> MaximizationParameter {
42      get { return (ValueLookupParameter<BoolValue>)Parameters["Maximization"]; }
43    }
44    public ScopeTreeLookupParameter<DoubleValue> QualityParameter {
45      get { return (ScopeTreeLookupParameter<DoubleValue>)Parameters["Quality"]; }
46    }
47    public ValueLookupParameter<IOperator> SelectorParameter {
48      get { return (ValueLookupParameter<IOperator>)Parameters["Selector"]; }
49    }
50    public ValueLookupParameter<IOperator> CrossoverParameter {
51      get { return (ValueLookupParameter<IOperator>)Parameters["Crossover"]; }
52    }
53    public ValueLookupParameter<PercentValue> MutationProbabilityParameter {
54      get { return (ValueLookupParameter<PercentValue>)Parameters["MutationProbability"]; }
55    }
56    public ValueLookupParameter<IOperator> MutatorParameter {
57      get { return (ValueLookupParameter<IOperator>)Parameters["Mutator"]; }
58    }
59    public ValueLookupParameter<IOperator> EvaluatorParameter {
60      get { return (ValueLookupParameter<IOperator>)Parameters["Evaluator"]; }
61    }
62    public ValueLookupParameter<IntValue> ElitesParameter {
63      get { return (ValueLookupParameter<IntValue>)Parameters["Elites"]; }
64    }
65    public IValueLookupParameter<BoolValue> ReevaluateElitesParameter {
66      get { return (IValueLookupParameter<BoolValue>)Parameters["ReevaluateElites"]; }
67    }
68    public ValueLookupParameter<IntValue> MaximumGenerationsParameter {
69      get { return (ValueLookupParameter<IntValue>)Parameters["MaximumGenerations"]; }
70    }
71    public ValueLookupParameter<VariableCollection> ResultsParameter {
72      get { return (ValueLookupParameter<VariableCollection>)Parameters["Results"]; }
73    }
74    public ValueLookupParameter<IOperator> AnalyzerParameter {
75      get { return (ValueLookupParameter<IOperator>)Parameters["Analyzer"]; }
76    }
77    public ValueLookupParameter<DoubleValue> SuccessRatioParameter {
78      get { return (ValueLookupParameter<DoubleValue>)Parameters["SuccessRatio"]; }
79    }
80    public LookupParameter<DoubleValue> ComparisonFactorParameter {
81      get { return (LookupParameter<DoubleValue>)Parameters["ComparisonFactor"]; }
82    }
83    public ValueLookupParameter<DoubleValue> ComparisonFactorStartParameter {
84      get { return (ValueLookupParameter<DoubleValue>)Parameters["ComparisonFactorStart"]; }
85    }
86    public ValueLookupParameter<IOperator> ComparisonFactorModifierParameter {
87      get { return (ValueLookupParameter<IOperator>)Parameters["ComparisonFactorModifier"]; }
88    }
89    public ValueLookupParameter<DoubleValue> MaximumSelectionPressureParameter {
90      get { return (ValueLookupParameter<DoubleValue>)Parameters["MaximumSelectionPressure"]; }
91    }
92    public ValueLookupParameter<BoolValue> OffspringSelectionBeforeMutationParameter {
93      get { return (ValueLookupParameter<BoolValue>)Parameters["OffspringSelectionBeforeMutation"]; }
94    }
95    public LookupParameter<IntValue> EvaluatedSolutionsParameter {
96      get { return (LookupParameter<IntValue>)Parameters["EvaluatedSolutions"]; }
97    }
98    public IValueLookupParameter<BoolValue> FillPopulationWithParentsParameter {
99      get { return (IValueLookupParameter<BoolValue>)Parameters["FillPopulationWithParents"]; }
100    }
101    #endregion
102
103    [StorableConstructor]
104    private OffspringSelectionGeneticAlgorithmMainLoop(bool deserializing) : base(deserializing) { }
105    private OffspringSelectionGeneticAlgorithmMainLoop(OffspringSelectionGeneticAlgorithmMainLoop original, Cloner cloner)
106      : base(original, cloner) {
107    }
108    public override IDeepCloneable Clone(Cloner cloner) {
109      return new OffspringSelectionGeneticAlgorithmMainLoop(this, cloner);
110    }
111    public OffspringSelectionGeneticAlgorithmMainLoop()
112      : base() {
113      Initialize();
114    }
115
116    [StorableHook(HookType.AfterDeserialization)]
117    private void AfterDeserialization() {
118      // BackwardsCompatibility3.3
119      #region Backwards compatible code, remove with 3.4
120      if (!Parameters.ContainsKey("ReevaluateElites")) {
121        Parameters.Add(new ValueLookupParameter<BoolValue>("ReevaluateElites", "Flag to determine if elite individuals should be reevaluated (i.e., if stochastic fitness functions are used.)"));
122      }
123      if (!Parameters.ContainsKey("FillPopulationWithParents"))
124        Parameters.Add(new ValueLookupParameter<BoolValue>("FillPopulationWithParents", "True if the population should be filled with parent individual or false if worse children should be used when the maximum selection pressure is exceeded."));
125      #endregion
126    }
127
128    private void Initialize() {
129      #region Create parameters
130      Parameters.Add(new ValueLookupParameter<IRandom>("Random", "A pseudo random number generator."));
131      Parameters.Add(new ValueLookupParameter<BoolValue>("Maximization", "True if the problem is a maximization problem, otherwise false."));
132      Parameters.Add(new ScopeTreeLookupParameter<DoubleValue>("Quality", "The value which represents the quality of a solution."));
133      Parameters.Add(new ValueLookupParameter<DoubleValue>("BestKnownQuality", "The best known quality value found so far."));
134      Parameters.Add(new ValueLookupParameter<IOperator>("Selector", "The operator used to select solutions for reproduction."));
135      Parameters.Add(new ValueLookupParameter<IOperator>("Crossover", "The operator used to cross solutions."));
136      Parameters.Add(new ValueLookupParameter<PercentValue>("MutationProbability", "The probability that the mutation operator is applied on a solution."));
137      Parameters.Add(new ValueLookupParameter<IOperator>("Mutator", "The operator used to mutate solutions."));
138      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."));
139      Parameters.Add(new ValueLookupParameter<IntValue>("Elites", "The numer of elite solutions which are kept in each generation."));
140      Parameters.Add(new ValueLookupParameter<BoolValue>("ReevaluateElites", "Flag to determine if elite individuals should be reevaluated (i.e., if stochastic fitness functions are used.)"));
141      Parameters.Add(new ValueLookupParameter<IntValue>("MaximumGenerations", "The maximum number of generations which should be processed."));
142      Parameters.Add(new ValueLookupParameter<VariableCollection>("Results", "The variable collection where results should be stored."));
143      Parameters.Add(new ValueLookupParameter<IOperator>("Analyzer", "The operator used to analyze each generation."));
144      Parameters.Add(new ValueLookupParameter<DoubleValue>("SuccessRatio", "The ratio of successful to total children that should be achieved."));
145      Parameters.Add(new LookupParameter<DoubleValue>("ComparisonFactor", "The comparison factor is used to determine whether the offspring should be compared to the better parent, the worse parent or a quality value linearly interpolated between them. It is in the range [0;1]."));
146      Parameters.Add(new ValueLookupParameter<DoubleValue>("ComparisonFactorStart", "The initial value for the comparison factor."));
147      Parameters.Add(new ValueLookupParameter<IOperator>("ComparisonFactorModifier", "The operator used to modify the comparison factor."));
148      Parameters.Add(new ValueLookupParameter<DoubleValue>("MaximumSelectionPressure", "The maximum selection pressure that terminates the algorithm."));
149      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."));
150      Parameters.Add(new LookupParameter<IntValue>("EvaluatedSolutions", "The number of times solutions have been evaluated."));
151      Parameters.Add(new ValueLookupParameter<BoolValue>("FillPopulationWithParents", "True if the population should be filled with parent individual or false if worse children should be used when the maximum selection pressure is exceeded."));
152      #endregion
153
154      #region Create operators
155      VariableCreator variableCreator = new VariableCreator();
156      Assigner comparisonFactorInitializer = new Assigner();
157      Placeholder analyzer1 = new Placeholder();
158      ResultsCollector resultsCollector1 = new ResultsCollector();
159      OffspringSelectionGeneticAlgorithmMainOperator mainOperator = new OffspringSelectionGeneticAlgorithmMainOperator();
160      IntCounter generationsCounter = new IntCounter();
161      Comparator maxGenerationsComparator = new Comparator();
162      Comparator maxSelectionPressureComparator = new Comparator();
163      Comparator maxEvaluatedSolutionsComparator = new Comparator();
164      Placeholder comparisonFactorModifier = new Placeholder();
165      Placeholder analyzer2 = new Placeholder();
166      ConditionalBranch conditionalBranch1 = new ConditionalBranch();
167      ConditionalBranch conditionalBranch2 = new ConditionalBranch();
168      ConditionalBranch conditionalBranch3 = new ConditionalBranch();
169
170      variableCreator.CollectedValues.Add(new ValueParameter<IntValue>("Generations", new IntValue(0))); // Class OffspringSelectionGeneticAlgorithm expects this to be called Generations
171      variableCreator.CollectedValues.Add(new ValueParameter<DoubleValue>("SelectionPressure", new DoubleValue(0)));
172      variableCreator.CollectedValues.Add(new ValueParameter<DoubleValue>("CurrentSuccessRatio", new DoubleValue(0)));
173
174      comparisonFactorInitializer.Name = "Initialize ComparisonFactor (placeholder)";
175      comparisonFactorInitializer.LeftSideParameter.ActualName = ComparisonFactorParameter.Name;
176      comparisonFactorInitializer.RightSideParameter.ActualName = ComparisonFactorStartParameter.Name;
177
178      analyzer1.Name = "Analyzer (placeholder)";
179      analyzer1.OperatorParameter.ActualName = AnalyzerParameter.Name;
180
181      resultsCollector1.CopyValue = new BoolValue(false);
182      resultsCollector1.CollectedValues.Add(new LookupParameter<IntValue>("Generations"));
183      resultsCollector1.CollectedValues.Add(new LookupParameter<DoubleValue>("Current Comparison Factor", null, ComparisonFactorParameter.Name));
184      resultsCollector1.CollectedValues.Add(new LookupParameter<DoubleValue>("Current Selection Pressure", "Displays the rising selection pressure during a generation.", "SelectionPressure"));
185      resultsCollector1.CollectedValues.Add(new LookupParameter<DoubleValue>("Current Success Ratio", "Indicates how many successful children were already found during a generation (relative to the population size).", "CurrentSuccessRatio"));
186      resultsCollector1.ResultsParameter.ActualName = ResultsParameter.Name;
187
188      mainOperator.ComparisonFactorParameter.ActualName = ComparisonFactorParameter.Name;
189      mainOperator.CrossoverParameter.ActualName = CrossoverParameter.Name;
190      mainOperator.CurrentSuccessRatioParameter.ActualName = "CurrentSuccessRatio";
191      mainOperator.ElitesParameter.ActualName = ElitesParameter.Name;
192      mainOperator.ReevaluateElitesParameter.ActualName = ReevaluateElitesParameter.Name;
193      mainOperator.EvaluatedSolutionsParameter.ActualName = EvaluatedSolutionsParameter.Name;
194      mainOperator.EvaluatorParameter.ActualName = EvaluatorParameter.Name;
195      mainOperator.MaximizationParameter.ActualName = MaximizationParameter.Name;
196      mainOperator.MaximumSelectionPressureParameter.ActualName = MaximumSelectionPressureParameter.Name;
197      mainOperator.MutationProbabilityParameter.ActualName = MutationProbabilityParameter.Name;
198      mainOperator.MutatorParameter.ActualName = MutatorParameter.Name;
199      mainOperator.OffspringSelectionBeforeMutationParameter.ActualName = OffspringSelectionBeforeMutationParameter.Name;
200      mainOperator.QualityParameter.ActualName = QualityParameter.Name;
201      mainOperator.RandomParameter.ActualName = RandomParameter.Name;
202      mainOperator.SelectionPressureParameter.ActualName = "SelectionPressure";
203      mainOperator.SelectorParameter.ActualName = SelectorParameter.Name;
204      mainOperator.SuccessRatioParameter.ActualName = SuccessRatioParameter.Name;
205      mainOperator.FillPopulationWithParentsParameter.ActualName = FillPopulationWithParentsParameter.Name;
206
207      generationsCounter.Increment = new IntValue(1);
208      generationsCounter.ValueParameter.ActualName = "Generations";
209
210      maxGenerationsComparator.Comparison = new Comparison(ComparisonType.GreaterOrEqual);
211      maxGenerationsComparator.LeftSideParameter.ActualName = "Generations";
212      maxGenerationsComparator.ResultParameter.ActualName = "TerminateMaximumGenerations";
213      maxGenerationsComparator.RightSideParameter.ActualName = MaximumGenerationsParameter.Name;
214
215      maxSelectionPressureComparator.Comparison = new Comparison(ComparisonType.GreaterOrEqual);
216      maxSelectionPressureComparator.LeftSideParameter.ActualName = "SelectionPressure";
217      maxSelectionPressureComparator.ResultParameter.ActualName = "TerminateSelectionPressure";
218      maxSelectionPressureComparator.RightSideParameter.ActualName = MaximumSelectionPressureParameter.Name;
219
220      maxEvaluatedSolutionsComparator.Comparison = new Comparison(ComparisonType.GreaterOrEqual);
221      maxEvaluatedSolutionsComparator.LeftSideParameter.ActualName = EvaluatedSolutionsParameter.Name;
222      maxEvaluatedSolutionsComparator.ResultParameter.ActualName = "TerminateEvaluatedSolutions";
223      maxEvaluatedSolutionsComparator.RightSideParameter.ActualName = "MaximumEvaluatedSolutions";
224
225      comparisonFactorModifier.Name = "Update ComparisonFactor (placeholder)";
226      comparisonFactorModifier.OperatorParameter.ActualName = ComparisonFactorModifierParameter.Name;
227
228      analyzer2.Name = "Analyzer (placeholder)";
229      analyzer2.OperatorParameter.ActualName = AnalyzerParameter.Name;
230
231      conditionalBranch1.Name = "MaximumSelectionPressure reached?";
232      conditionalBranch1.ConditionParameter.ActualName = "TerminateSelectionPressure";
233
234      conditionalBranch2.Name = "MaximumGenerations reached?";
235      conditionalBranch2.ConditionParameter.ActualName = "TerminateMaximumGenerations";
236
237      conditionalBranch3.Name = "MaximumEvaluatedSolutions reached?";
238      conditionalBranch3.ConditionParameter.ActualName = "TerminateEvaluatedSolutions";
239      #endregion
240
241      #region Create operator graph
242      OperatorGraph.InitialOperator = variableCreator;
243      variableCreator.Successor = comparisonFactorInitializer;
244      comparisonFactorInitializer.Successor = analyzer1;
245      analyzer1.Successor = resultsCollector1;
246      resultsCollector1.Successor = mainOperator;
247      mainOperator.Successor = generationsCounter;
248      generationsCounter.Successor = maxGenerationsComparator;
249      maxGenerationsComparator.Successor = maxSelectionPressureComparator;
250      maxSelectionPressureComparator.Successor = maxEvaluatedSolutionsComparator;
251      maxEvaluatedSolutionsComparator.Successor = comparisonFactorModifier;
252      comparisonFactorModifier.Successor = analyzer2;
253      analyzer2.Successor = conditionalBranch1;
254      conditionalBranch1.FalseBranch = conditionalBranch2;
255      conditionalBranch1.TrueBranch = null;
256      conditionalBranch1.Successor = null;
257      conditionalBranch2.FalseBranch = conditionalBranch3;
258      conditionalBranch2.TrueBranch = null;
259      conditionalBranch2.Successor = null;
260      conditionalBranch3.FalseBranch = mainOperator;
261      conditionalBranch3.TrueBranch = null;
262      conditionalBranch3.Successor = null;
263      #endregion
264    }
265  }
266}
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