source: branches/VOSGA/HeuristicLab.Algorithms.VOffspringSelectionGeneticAlgorithm/VOffspringSelectionGeneticAlgorithmMainOperator.cs @ 11513

Last change on this file since 11513 was 11513, checked in by ascheibe, 8 years ago

#2267 made subscopes offspring comparer configurable

File size: 20.4 KB
Line 
1#region License Information
2/* HeuristicLab
3 * Copyright (C) 2002-2014 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.VOffspringSelectionGeneticAlgorithm {
32  /// <summary>
33  /// An operator which represents the main loop of an offspring selection genetic algorithm.
34  /// </summary>
35  [Item("VOffspringSelectionGeneticAlgorithmMainOperator", "An operator that represents the core of an offspring selection genetic algorithm.")]
36  [StorableClass]
37  public sealed class VOffspringSelectionGeneticAlgorithmMainOperator : 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<IOperator> SelectorParameter {
49      get { return (ValueLookupParameter<IOperator>)Parameters["Selector"]; }
50    }
51    public ValueLookupParameter<IOperator> CrossoverParameter {
52      get { return (ValueLookupParameter<IOperator>)Parameters["Crossover"]; }
53    }
54    public ValueLookupParameter<PercentValue> MutationProbabilityParameter {
55      get { return (ValueLookupParameter<PercentValue>)Parameters["MutationProbability"]; }
56    }
57    public ValueLookupParameter<IOperator> MutatorParameter {
58      get { return (ValueLookupParameter<IOperator>)Parameters["Mutator"]; }
59    }
60    public ValueLookupParameter<IOperator> EvaluatorParameter {
61      get { return (ValueLookupParameter<IOperator>)Parameters["Evaluator"]; }
62    }
63    public LookupParameter<IntValue> EvaluatedSolutionsParameter {
64      get { return (LookupParameter<IntValue>)Parameters["EvaluatedSolutions"]; }
65    }
66    public ValueLookupParameter<IntValue> ElitesParameter {
67      get { return (ValueLookupParameter<IntValue>)Parameters["Elites"]; }
68    }
69    public IValueLookupParameter<BoolValue> ReevaluateElitesParameter {
70      get { return (IValueLookupParameter<BoolValue>)Parameters["ReevaluateElites"]; }
71    }
72    public LookupParameter<DoubleValue> ComparisonFactorParameter {
73      get { return (LookupParameter<DoubleValue>)Parameters["ComparisonFactor"]; }
74    }
75    public LookupParameter<DoubleValue> CurrentSuccessRatioParameter {
76      get { return (LookupParameter<DoubleValue>)Parameters["CurrentSuccessRatio"]; }
77    }
78    public ValueLookupParameter<DoubleValue> SuccessRatioParameter {
79      get { return (ValueLookupParameter<DoubleValue>)Parameters["SuccessRatio"]; }
80    }
81    public LookupParameter<DoubleValue> SelectionPressureParameter {
82      get { return (LookupParameter<DoubleValue>)Parameters["SelectionPressure"]; }
83    }
84    public ValueLookupParameter<DoubleValue> MaximumSelectionPressureParameter {
85      get { return (ValueLookupParameter<DoubleValue>)Parameters["MaximumSelectionPressure"]; }
86    }
87    public ValueLookupParameter<BoolValue> OffspringSelectionBeforeMutationParameter {
88      get { return (ValueLookupParameter<BoolValue>)Parameters["OffspringSelectionBeforeMutation"]; }
89    }
90    public IValueLookupParameter<BoolValue> FillPopulationWithParentsParameter {
91      get { return (IValueLookupParameter<BoolValue>)Parameters["FillPopulationWithParents"]; }
92    }
93    public ValueLookupParameter<IOffspringSelector> OffspringSelectorParameter {
94      get { return (ValueLookupParameter<IOffspringSelector>)Parameters["OffspringSelector"]; }
95    }
96    public ValueLookupParameter<ISubScopesQualityComparatorOperator> SubScopesQualityComparatorParameter {
97      get { return (ValueLookupParameter<ISubScopesQualityComparatorOperator>)Parameters["SubScopesQualityComparator"]; }
98    }
99    #endregion
100
101    [StorableConstructor]
102    private VOffspringSelectionGeneticAlgorithmMainOperator(bool deserializing) : base(deserializing) { }
103    private VOffspringSelectionGeneticAlgorithmMainOperator(VOffspringSelectionGeneticAlgorithmMainOperator original, Cloner cloner)
104      : base(original, cloner) {
105    }
106    public override IDeepCloneable Clone(Cloner cloner) {
107      return new VOffspringSelectionGeneticAlgorithmMainOperator(this, cloner);
108    }
109    public VOffspringSelectionGeneticAlgorithmMainOperator()
110      : base() {
111      Initialize();
112    }
113
114    [StorableHook(HookType.AfterDeserialization)]
115    private void AfterDeserialization() {
116      // BackwardsCompatibility3.3
117      #region Backwards compatible code, remove with 3.4
118      if (!Parameters.ContainsKey("ReevaluateElites")) {
119        Parameters.Add(new ValueLookupParameter<BoolValue>("ReevaluateElites", "Flag to determine if elite individuals should be reevaluated (i.e., if stochastic fitness functions are used.)"));
120      }
121      if (!Parameters.ContainsKey("FillPopulationWithParents"))
122        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."));
123      #endregion
124    }
125
126    private void Initialize() {
127      #region Create parameters
128      Parameters.Add(new ValueLookupParameter<IRandom>("Random", "A pseudo random number generator."));
129      Parameters.Add(new ValueLookupParameter<BoolValue>("Maximization", "True if the problem is a maximization problem, otherwise false."));
130      Parameters.Add(new ScopeTreeLookupParameter<DoubleValue>("Quality", "The value which represents the quality of a solution."));
131      Parameters.Add(new ValueLookupParameter<IOperator>("Selector", "The operator used to select solutions for reproduction."));
132      Parameters.Add(new ValueLookupParameter<IOperator>("Crossover", "The operator used to cross solutions."));
133      Parameters.Add(new ValueLookupParameter<PercentValue>("MutationProbability", "The probability that the mutation operator is applied on a solution."));
134      Parameters.Add(new ValueLookupParameter<IOperator>("Mutator", "The operator used to mutate solutions."));
135      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."));
136      Parameters.Add(new LookupParameter<IntValue>("EvaluatedSolutions", "The number of evaluated solutions."));
137      Parameters.Add(new ValueLookupParameter<IntValue>("Elites", "The numer of elite solutions which are kept in each generation."));
138      Parameters.Add(new ValueLookupParameter<BoolValue>("ReevaluateElites", "Flag to determine if elite individuals should be reevaluated (i.e., if stochastic fitness functions are used.)"));
139      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]."));
140      Parameters.Add(new LookupParameter<DoubleValue>("CurrentSuccessRatio", "The current success ratio."));
141      Parameters.Add(new ValueLookupParameter<DoubleValue>("SuccessRatio", "The ratio of successful to total children that should be achieved."));
142      Parameters.Add(new LookupParameter<DoubleValue>("SelectionPressure", "The actual selection pressure."));
143      Parameters.Add(new ValueLookupParameter<DoubleValue>("MaximumSelectionPressure", "The maximum selection pressure that terminates the algorithm."));
144      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."));
145      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."));
146      Parameters.Add(new ValueLookupParameter<IOffspringSelector>("OffspringSelector", "The operator used as selection criterea for deciding which individuals are successful and which should be disgarded."));
147      Parameters.Add(new ValueLookupParameter<ISubScopesQualityComparatorOperator>("SubScopesQualityComparator", "The operator used to compare solution candidates."));
148      #endregion
149
150      #region Create operators
151      Placeholder selector = new Placeholder();
152      SubScopesProcessor subScopesProcessor1 = new SubScopesProcessor();
153      ChildrenCreator childrenCreator = new ChildrenCreator();
154      ConditionalBranch osBeforeMutationBranch = new ConditionalBranch();
155      UniformSubScopesProcessor uniformSubScopesProcessor1 = new UniformSubScopesProcessor();
156      Placeholder crossover1 = new Placeholder();
157      UniformSubScopesProcessor uniformSubScopesProcessor2 = new UniformSubScopesProcessor();
158      Placeholder evaluator1 = new Placeholder();
159      SubScopesCounter subScopesCounter1 = new SubScopesCounter();
160      Placeholder qualityComparer1 = new Placeholder();
161      SubScopesRemover subScopesRemover1 = new SubScopesRemover();
162      UniformSubScopesProcessor uniformSubScopesProcessor3 = new UniformSubScopesProcessor();
163      StochasticBranch mutationBranch1 = new StochasticBranch();
164      Placeholder mutator1 = new Placeholder();
165      VariableCreator variableCreator1 = new VariableCreator();
166      VariableCreator variableCreator2 = new VariableCreator();
167      ConditionalSelector conditionalSelector = new ConditionalSelector();
168      SubScopesProcessor subScopesProcessor2 = new SubScopesProcessor();
169      UniformSubScopesProcessor uniformSubScopesProcessor4 = new UniformSubScopesProcessor();
170      Placeholder evaluator2 = new Placeholder();
171      SubScopesCounter subScopesCounter2 = new SubScopesCounter();
172      MergingReducer mergingReducer1 = new MergingReducer();
173      UniformSubScopesProcessor uniformSubScopesProcessor5 = new UniformSubScopesProcessor();
174      Placeholder crossover2 = new Placeholder();
175      StochasticBranch mutationBranch2 = new StochasticBranch();
176      Placeholder mutator2 = new Placeholder();
177      UniformSubScopesProcessor uniformSubScopesProcessor6 = new UniformSubScopesProcessor();
178      Placeholder evaluator3 = new Placeholder();
179      SubScopesCounter subScopesCounter3 = new SubScopesCounter();
180      Placeholder qualityComparer2 = new Placeholder();
181      SubScopesRemover subScopesRemover2 = new SubScopesRemover();
182      Placeholder offspringSelector = new Placeholder();
183      SubScopesProcessor subScopesProcessor3 = new SubScopesProcessor();
184      BestSelector bestSelector = new BestSelector();
185      WorstSelector worstSelector = new WorstSelector();
186      RightReducer rightReducer = new RightReducer();
187      LeftReducer leftReducer = new LeftReducer();
188      MergingReducer mergingReducer2 = new MergingReducer();
189      ConditionalBranch reevaluateElitesBranch = new ConditionalBranch();
190      UniformSubScopesProcessor uniformSubScopesProcessor7 = new UniformSubScopesProcessor();
191      Placeholder evaluator4 = new Placeholder();
192      SubScopesCounter subScopesCounter4 = new SubScopesCounter();
193      ConditionalBranch conditionalBranch = new ConditionalBranch();
194
195      selector.Name = "Selector (placeholder)";
196      selector.OperatorParameter.ActualName = SelectorParameter.Name;
197
198      childrenCreator.ParentsPerChild = new IntValue(2);
199
200      osBeforeMutationBranch.Name = "Apply OS before mutation?";
201      osBeforeMutationBranch.ConditionParameter.ActualName = OffspringSelectionBeforeMutationParameter.Name;
202
203      crossover1.Name = "Crossover (placeholder)";
204      crossover1.OperatorParameter.ActualName = CrossoverParameter.Name;
205
206      uniformSubScopesProcessor2.Parallel.Value = true;
207
208      evaluator1.Name = "Evaluator (placeholder)";
209      evaluator1.OperatorParameter.ActualName = EvaluatorParameter.Name;
210
211      subScopesCounter1.Name = "Increment EvaluatedSolutions";
212      subScopesCounter1.ValueParameter.ActualName = EvaluatedSolutionsParameter.Name;
213
214      qualityComparer1.Name = "Quality Comparator (placeholder)";
215      qualityComparer1.OperatorParameter.ActualName = SubScopesQualityComparatorParameter.ActualName;
216
217      subScopesRemover1.RemoveAllSubScopes = true;
218
219      mutationBranch1.ProbabilityParameter.ActualName = MutationProbabilityParameter.Name;
220      mutationBranch1.RandomParameter.ActualName = RandomParameter.Name;
221
222      mutator1.Name = "Mutator (placeholder)";
223      mutator1.OperatorParameter.ActualName = MutatorParameter.Name;
224
225      variableCreator1.Name = "MutatedOffspring = true";
226      variableCreator1.CollectedValues.Add(new ValueParameter<BoolValue>("MutatedOffspring", null, new BoolValue(true), false));
227
228      variableCreator2.Name = "MutatedOffspring = false";
229      variableCreator2.CollectedValues.Add(new ValueParameter<BoolValue>("MutatedOffspring", null, new BoolValue(false), false));
230
231      conditionalSelector.ConditionParameter.ActualName = "MutatedOffspring";
232      conditionalSelector.ConditionParameter.Depth = 1;
233      conditionalSelector.CopySelected.Value = false;
234
235      uniformSubScopesProcessor4.Parallel.Value = true;
236
237      evaluator2.Name = "Evaluator (placeholder)";
238      evaluator2.OperatorParameter.ActualName = EvaluatorParameter.Name;
239
240      subScopesCounter2.Name = "Increment EvaluatedSolutions";
241      subScopesCounter2.ValueParameter.ActualName = EvaluatedSolutionsParameter.Name;
242
243      crossover2.Name = "Crossover (placeholder)";
244      crossover2.OperatorParameter.ActualName = CrossoverParameter.Name;
245
246      mutationBranch2.ProbabilityParameter.ActualName = MutationProbabilityParameter.Name;
247      mutationBranch2.RandomParameter.ActualName = RandomParameter.Name;
248
249      mutator2.Name = "Mutator (placeholder)";
250      mutator2.OperatorParameter.ActualName = MutatorParameter.Name;
251
252      uniformSubScopesProcessor6.Parallel.Value = true;
253
254      evaluator3.Name = "Evaluator (placeholder)";
255      evaluator3.OperatorParameter.ActualName = EvaluatorParameter.Name;
256
257      subScopesCounter3.Name = "Increment EvaluatedSolutions";
258      subScopesCounter3.ValueParameter.ActualName = EvaluatedSolutionsParameter.Name;
259
260      qualityComparer2.Name = "Quality Comparator (placeholder)";
261      qualityComparer2.OperatorParameter.ActualName = SubScopesQualityComparatorParameter.ActualName;
262
263      subScopesRemover2.RemoveAllSubScopes = true;
264
265      offspringSelector.Name = "OffspringSelector (placeholder)";
266      offspringSelector.OperatorParameter.ActualName = OffspringSelectorParameter.Name;
267
268      bestSelector.CopySelected = new BoolValue(false);
269      bestSelector.MaximizationParameter.ActualName = MaximizationParameter.Name;
270      bestSelector.NumberOfSelectedSubScopesParameter.ActualName = ElitesParameter.Name;
271      bestSelector.QualityParameter.ActualName = QualityParameter.Name;
272
273      worstSelector.CopySelected = new BoolValue(false);
274      worstSelector.MaximizationParameter.ActualName = MaximizationParameter.Name;
275      worstSelector.NumberOfSelectedSubScopesParameter.ActualName = ElitesParameter.Name;
276      worstSelector.QualityParameter.ActualName = QualityParameter.Name;
277
278      reevaluateElitesBranch.ConditionParameter.ActualName = "ReevaluateElites";
279      reevaluateElitesBranch.Name = "Reevaluate elites ?";
280
281      uniformSubScopesProcessor7.Parallel.Value = true;
282
283      evaluator4.Name = "Evaluator (placeholder)";
284      evaluator4.OperatorParameter.ActualName = EvaluatorParameter.Name;
285
286      subScopesCounter4.Name = "Increment EvaluatedSolutions";
287      subScopesCounter4.ValueParameter.ActualName = EvaluatedSolutionsParameter.Name;
288
289      conditionalBranch.Name = "Enough children produced?";
290      conditionalBranch.ConditionParameter.ActualName = "EnoughChildrenGenerated";
291      conditionalBranch.FalseBranch = selector;
292      conditionalBranch.TrueBranch = subScopesProcessor3;
293      #endregion
294
295      #region Create operator graph
296      OperatorGraph.InitialOperator = selector;
297      selector.Successor = subScopesProcessor1;
298      subScopesProcessor1.Operators.Add(new EmptyOperator());
299      subScopesProcessor1.Operators.Add(childrenCreator);
300      subScopesProcessor1.Successor = offspringSelector;
301      childrenCreator.Successor = osBeforeMutationBranch;
302      osBeforeMutationBranch.TrueBranch = uniformSubScopesProcessor1;
303      osBeforeMutationBranch.FalseBranch = uniformSubScopesProcessor5;
304      osBeforeMutationBranch.Successor = null;
305      uniformSubScopesProcessor1.Operator = crossover1;
306      uniformSubScopesProcessor1.Successor = uniformSubScopesProcessor2;
307      crossover1.Successor = null;
308      uniformSubScopesProcessor2.Operator = evaluator1;
309      uniformSubScopesProcessor2.Successor = subScopesCounter1;
310      evaluator1.Successor = qualityComparer1;
311      qualityComparer1.Successor = subScopesRemover1;
312      subScopesRemover1.Successor = null;
313      subScopesCounter1.Successor = uniformSubScopesProcessor3;
314      uniformSubScopesProcessor3.Operator = mutationBranch1;
315      uniformSubScopesProcessor3.Successor = conditionalSelector;
316      mutationBranch1.FirstBranch = mutator1;
317      mutationBranch1.SecondBranch = variableCreator2;
318      mutationBranch1.Successor = null;
319      mutator1.Successor = variableCreator1;
320      variableCreator1.Successor = null;
321      variableCreator2.Successor = null;
322      conditionalSelector.Successor = subScopesProcessor2;
323      subScopesProcessor2.Operators.Add(new EmptyOperator());
324      subScopesProcessor2.Operators.Add(uniformSubScopesProcessor4);
325      subScopesProcessor2.Successor = mergingReducer1;
326      uniformSubScopesProcessor4.Operator = evaluator2;
327      uniformSubScopesProcessor4.Successor = subScopesCounter2;
328      evaluator2.Successor = null;
329      subScopesCounter2.Successor = null;
330      mergingReducer1.Successor = null;
331      uniformSubScopesProcessor5.Operator = crossover2;
332      uniformSubScopesProcessor5.Successor = uniformSubScopesProcessor6;
333      crossover2.Successor = mutationBranch2;
334      mutationBranch2.FirstBranch = mutator2;
335      mutationBranch2.SecondBranch = null;
336      mutationBranch2.Successor = null;
337      mutator2.Successor = null;
338      uniformSubScopesProcessor6.Operator = evaluator3;
339      uniformSubScopesProcessor6.Successor = subScopesCounter3;
340      evaluator3.Successor = qualityComparer2;
341      qualityComparer2.Successor = subScopesRemover2;
342      subScopesRemover2.Successor = null;
343      subScopesCounter3.Successor = null;
344      offspringSelector.Successor = conditionalBranch;
345      subScopesProcessor3.Operators.Add(bestSelector);
346      subScopesProcessor3.Operators.Add(worstSelector);
347      subScopesProcessor3.Successor = mergingReducer2;
348      bestSelector.Successor = rightReducer;
349      rightReducer.Successor = reevaluateElitesBranch;
350      reevaluateElitesBranch.TrueBranch = uniformSubScopesProcessor7;
351      uniformSubScopesProcessor7.Operator = evaluator4;
352      uniformSubScopesProcessor7.Successor = subScopesCounter4;
353      subScopesCounter4.Successor = null;
354      reevaluateElitesBranch.FalseBranch = null;
355      reevaluateElitesBranch.Successor = null;
356      worstSelector.Successor = leftReducer;
357      leftReducer.Successor = null;
358      mergingReducer2.Successor = null;
359      #endregion
360    }
361
362    public override IOperation Apply() {
363      if (CrossoverParameter.ActualValue == null)
364        return null;
365      return base.Apply();
366    }
367  }
368}
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