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source: trunk/sources/HeuristicLab.Algorithms.NSGA2/3.3/NSGA2MainLoop.cs @ 4068

Last change on this file since 4068 was 4068, checked in by swagner, 12 years ago

Sorted usings and removed unused usings in entire solution (#1094)

File size: 10.9 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.Core;
23using HeuristicLab.Data;
24using HeuristicLab.Operators;
25using HeuristicLab.Optimization.Operators;
26using HeuristicLab.Parameters;
27using HeuristicLab.Persistence.Default.CompositeSerializers.Storable;
28using HeuristicLab.Selection;
29
30namespace HeuristicLab.Algorithms.NSGA2 {
31  /// <summary>
32  /// An operator that represents the mainloop of the NSGA-II
33  /// </summary>
34  [Item("NSGA2MainLoop", "An operator which represents the main loop of the NSGA-II algorithm.")]
35  [StorableClass]
36  public class NSGA2MainLoop : AlgorithmOperator {
37    #region Parameter properties
38    public ValueLookupParameter<IRandom> RandomParameter {
39      get { return (ValueLookupParameter<IRandom>)Parameters["Random"]; }
40    }
41    public ValueLookupParameter<BoolArray> MaximizationParameter {
42      get { return (ValueLookupParameter<BoolArray>)Parameters["Maximization"]; }
43    }
44    public ScopeTreeLookupParameter<DoubleArray> QualitiesParameter {
45      get { return (ScopeTreeLookupParameter<DoubleArray>)Parameters["Qualities"]; }
46    }
47    public ValueLookupParameter<IntValue> PopulationSizeParameter {
48      get { return (ValueLookupParameter<IntValue>)Parameters["PopulationSize"]; }
49    }
50    public ValueLookupParameter<IOperator> SelectorParameter {
51      get { return (ValueLookupParameter<IOperator>)Parameters["Selector"]; }
52    }
53    public ValueLookupParameter<PercentValue> CrossoverProbabilityParameter {
54      get { return (ValueLookupParameter<PercentValue>)Parameters["CrossoverProbability"]; }
55    }
56    public ValueLookupParameter<IOperator> CrossoverParameter {
57      get { return (ValueLookupParameter<IOperator>)Parameters["Crossover"]; }
58    }
59    public ValueLookupParameter<PercentValue> MutationProbabilityParameter {
60      get { return (ValueLookupParameter<PercentValue>)Parameters["MutationProbability"]; }
61    }
62    public ValueLookupParameter<IOperator> MutatorParameter {
63      get { return (ValueLookupParameter<IOperator>)Parameters["Mutator"]; }
64    }
65    public ValueLookupParameter<IOperator> EvaluatorParameter {
66      get { return (ValueLookupParameter<IOperator>)Parameters["Evaluator"]; }
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    #endregion
78
79    [StorableConstructor]
80    private NSGA2MainLoop(bool deserializing) : base() { }
81    public NSGA2MainLoop()
82      : base() {
83      Initialize();
84    }
85
86    private void Initialize() {
87      #region Create parameters
88      Parameters.Add(new ValueLookupParameter<IRandom>("Random", "A pseudo random number generator."));
89      Parameters.Add(new ValueLookupParameter<BoolArray>("Maximization", "True if an objective should be maximized, or false if it should be minimized."));
90      Parameters.Add(new ScopeTreeLookupParameter<DoubleArray>("Qualities", "The vector of quality values."));
91      Parameters.Add(new ValueLookupParameter<IntValue>("PopulationSize", "The population size."));
92      Parameters.Add(new ValueLookupParameter<IOperator>("Selector", "The operator used to select solutions for reproduction."));
93      Parameters.Add(new ValueLookupParameter<PercentValue>("CrossoverProbability", "The probability that the crossover operator is applied on a solution."));
94      Parameters.Add(new ValueLookupParameter<IOperator>("Crossover", "The operator used to cross solutions."));
95      Parameters.Add(new ValueLookupParameter<PercentValue>("MutationProbability", "The probability that the mutation operator is applied on a solution."));
96      Parameters.Add(new ValueLookupParameter<IOperator>("Mutator", "The operator used to mutate solutions."));
97      Parameters.Add(new ValueLookupParameter<IOperator>("Evaluator", "The operator used to evaluate solutions."));
98      Parameters.Add(new ValueLookupParameter<IntValue>("MaximumGenerations", "The maximum number of generations which should be processed."));
99      Parameters.Add(new ValueLookupParameter<VariableCollection>("Results", "The variable collection where results should be stored."));
100      Parameters.Add(new ValueLookupParameter<IOperator>("Analyzer", "The operator used to analyze each generation."));
101      #endregion
102
103      #region Create operators
104      VariableCreator variableCreator = new VariableCreator();
105      ResultsCollector resultsCollector1 = new ResultsCollector();
106      Placeholder analyzer1 = new Placeholder();
107      Placeholder selector = new Placeholder();
108      SubScopesProcessor subScopesProcessor1 = new SubScopesProcessor();
109      ChildrenCreator childrenCreator = new ChildrenCreator();
110      UniformSubScopesProcessor uniformSubScopesProcessor = new UniformSubScopesProcessor();
111      StochasticBranch crossoverStochasticBranch = new StochasticBranch();
112      Placeholder crossover = new Placeholder();
113      DefaultCrossover noCrossover = new DefaultCrossover();
114      StochasticBranch mutationStochasticBranch = new StochasticBranch();
115      Placeholder mutator = new Placeholder();
116      Placeholder evaluator = new Placeholder();
117      SubScopesRemover subScopesRemover = new SubScopesRemover();
118      MergingReducer mergingReducer = new MergingReducer();
119      RankAndCrowdingSorter rankAndCrowdingSorter = new RankAndCrowdingSorter();
120      LeftSelector leftSelector = new LeftSelector();
121      RightReducer rightReducer = new RightReducer();
122      IntCounter intCounter = new IntCounter();
123      Comparator comparator = new Comparator();
124      ResultsCollector resultsCollector2 = new ResultsCollector();
125      Placeholder analyzer2 = new Placeholder();
126      ConditionalBranch conditionalBranch = new ConditionalBranch();
127
128      variableCreator.CollectedValues.Add(new ValueParameter<IntValue>("Generations", new IntValue(0)));
129
130      resultsCollector1.CollectedValues.Add(new LookupParameter<IntValue>("Generations"));
131      resultsCollector1.ResultsParameter.ActualName = ResultsParameter.Name;
132
133      analyzer1.Name = "Analyzer";
134      analyzer1.OperatorParameter.ActualName = AnalyzerParameter.Name;
135
136      selector.Name = "Selector";
137      selector.OperatorParameter.ActualName = SelectorParameter.Name;
138
139      childrenCreator.ParentsPerChild = new IntValue(2);
140
141      crossoverStochasticBranch.ProbabilityParameter.ActualName = CrossoverProbabilityParameter.Name;
142      crossoverStochasticBranch.RandomParameter.ActualName = RandomParameter.Name;
143
144      crossover.Name = "Crossover";
145      crossover.OperatorParameter.ActualName = CrossoverParameter.Name;
146
147      noCrossover.Name = "Clone parent";
148      noCrossover.RandomParameter.ActualName = RandomParameter.Name;
149
150      mutationStochasticBranch.ProbabilityParameter.ActualName = MutationProbabilityParameter.Name;
151      mutationStochasticBranch.RandomParameter.ActualName = RandomParameter.Name;
152
153      mutator.Name = "Mutator";
154      mutator.OperatorParameter.ActualName = MutatorParameter.Name;
155
156      evaluator.Name = "Evaluator";
157      evaluator.OperatorParameter.ActualName = EvaluatorParameter.Name;
158
159      subScopesRemover.RemoveAllSubScopes = true;
160
161      rankAndCrowdingSorter.CrowdingDistanceParameter.ActualName = "CrowdingDistance";
162      rankAndCrowdingSorter.RankParameter.ActualName = "Rank";
163
164      leftSelector.CopySelected = new BoolValue(false);
165      leftSelector.NumberOfSelectedSubScopesParameter.ActualName = PopulationSizeParameter.Name;
166
167      intCounter.Increment = new IntValue(1);
168      intCounter.ValueParameter.ActualName = "Generations";
169
170      comparator.Comparison = new Comparison(ComparisonType.GreaterOrEqual);
171      comparator.LeftSideParameter.ActualName = "Generations";
172      comparator.ResultParameter.ActualName = "Terminate";
173      comparator.RightSideParameter.ActualName = MaximumGenerationsParameter.Name;
174
175      resultsCollector2.CollectedValues.Add(new LookupParameter<IntValue>("Generations"));
176      resultsCollector2.ResultsParameter.ActualName = ResultsParameter.Name;
177
178      analyzer2.Name = "Analyzer";
179      analyzer2.OperatorParameter.ActualName = "Analyzer";
180
181      conditionalBranch.ConditionParameter.ActualName = "Terminate";
182      #endregion
183
184      #region Create operator graph
185      OperatorGraph.InitialOperator = variableCreator;
186      variableCreator.Successor = resultsCollector1;
187      resultsCollector1.Successor = analyzer1;
188      analyzer1.Successor = selector;
189      selector.Successor = subScopesProcessor1;
190      subScopesProcessor1.Operators.Add(new EmptyOperator());
191      subScopesProcessor1.Operators.Add(childrenCreator);
192      subScopesProcessor1.Successor = mergingReducer;
193      childrenCreator.Successor = uniformSubScopesProcessor;
194      uniformSubScopesProcessor.Operator = crossoverStochasticBranch;
195      uniformSubScopesProcessor.Successor = null;
196      crossoverStochasticBranch.FirstBranch = crossover;
197      crossoverStochasticBranch.SecondBranch = noCrossover;
198      crossoverStochasticBranch.Successor = mutationStochasticBranch;
199      crossover.Successor = null;
200      noCrossover.Successor = null;
201      mutationStochasticBranch.FirstBranch = mutator;
202      mutationStochasticBranch.SecondBranch = null;
203      mutationStochasticBranch.Successor = evaluator;
204      mutator.Successor = null;
205      evaluator.Successor = subScopesRemover;
206      subScopesRemover.Successor = null;
207      mergingReducer.Successor = rankAndCrowdingSorter;
208      rankAndCrowdingSorter.Successor = leftSelector;
209      leftSelector.Successor = rightReducer;
210      rightReducer.Successor = intCounter;
211      intCounter.Successor = comparator;
212      comparator.Successor = resultsCollector2;
213      resultsCollector2.Successor = analyzer2;
214      analyzer2.Successor = conditionalBranch;
215      conditionalBranch.FalseBranch = selector;
216      conditionalBranch.TrueBranch = null;
217      conditionalBranch.Successor = null;
218      #endregion
219    }
220  }
221}
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