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source: branches/ALPS/HeuristicLab.Algorithms.ALPS.SteadyState/3.3/AlpsSsGeneticAlgorithm.cs @ 12120

Last change on this file since 12120 was 12120, checked in by pfleck, 9 years ago

#2350

  • Implemented AlpsSsGeneticAlgorithm.
  • Created empty AlpsSsGeneticAlgorithmMainLoop.
File size: 14.3 KB
Line 
1#region License Information
2/* HeuristicLab
3 * Copyright (C) 2002-2015 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 System;
23using System.Linq;
24using HeuristicLab.Common;
25using HeuristicLab.Core;
26using HeuristicLab.Data;
27using HeuristicLab.Operators;
28using HeuristicLab.Optimization;
29using HeuristicLab.Optimization.Operators;
30using HeuristicLab.Parameters;
31using HeuristicLab.Persistence.Default.CompositeSerializers.Storable;
32using HeuristicLab.PluginInfrastructure;
33using HeuristicLab.Random;
34using HeuristicLab.Selection;
35
36namespace HeuristicLab.Algorithms.ALPS.SteadyState {
37  [Item("ALPS Steady-State Genetic Algorithm", "A genetic algorithmn with a steady-state age-layered population structure")]
38  [Creatable("Algorithms")]
39  [StorableClass]
40  public class AlpsSsGeneticAlgorithm : Alps {
41    #region Parameter Properties
42    private IValueParameter<IntArray> PopulationSizeParameter {
43      get { return (IValueParameter<IntArray>)Parameters["PopulationSize"]; }
44    }
45    private IValueParameter<IntValue> MaximumGenerationsParameter {
46      get { return (IValueParameter<IntValue>)Parameters["MaximumGenerations"]; }
47    }
48    public IConstrainedValueParameter<ISelector> SelectorParameter {
49      get { return (IConstrainedValueParameter<ISelector>)Parameters["Selector"]; }
50    }
51    public IConstrainedValueParameter<ICrossover> CrossoverParameter {
52      get { return (IConstrainedValueParameter<ICrossover>)Parameters["Crossover"]; }
53    }
54    private IValueParameter<PercentValue> MutationProbabilityParameter {
55      get { return (IValueParameter<PercentValue>)Parameters["MutationProbability"]; }
56    }
57    public IConstrainedValueParameter<IManipulator> MutatorParameter {
58      get { return (IConstrainedValueParameter<IManipulator>)Parameters["Mutator"]; }
59    }
60    private IValueParameter<IntValue> ElitesParameter {
61      get { return (IValueParameter<IntValue>)Parameters["Elites"]; }
62    }
63    private IFixedValueParameter<BoolValue> ReevaluateElitesParameter {
64      get { return (IFixedValueParameter<BoolValue>)Parameters["ReevaluateElites"]; }
65    }
66    #endregion
67
68    #region Properties
69    public IntArray PopulationSize {
70      get { return PopulationSizeParameter.Value; }
71      set { PopulationSizeParameter.Value = value; }
72    }
73    public IntValue MaximumGenerations {
74      get { return MaximumGenerationsParameter.Value; }
75      set { MaximumGenerationsParameter.Value = value; }
76    }
77
78    public ISelector Selector {
79      get { return SelectorParameter.Value; }
80      set { SelectorParameter.Value = value; }
81    }
82    public ICrossover Crossover {
83      get { return CrossoverParameter.Value; }
84      set { CrossoverParameter.Value = value; }
85    }
86    public PercentValue MutationProbability {
87      get { return MutationProbabilityParameter.Value; }
88      set { MutationProbabilityParameter.Value = value; }
89    }
90    public IManipulator Mutator {
91      get { return MutatorParameter.Value; }
92      set { MutatorParameter.Value = value; }
93    }
94    public IntValue Elites {
95      get { return ElitesParameter.Value; }
96      set { ElitesParameter.Value = value; }
97    }
98    public bool ReevaluteElites {
99      get { return ReevaluateElitesParameter.Value.Value; }
100      set { ReevaluateElitesParameter.Value.Value = value; }
101    }
102    #endregion
103
104    [StorableConstructor]
105    private AlpsSsGeneticAlgorithm(bool deserializing)
106      : base(deserializing) { }
107    private AlpsSsGeneticAlgorithm(AlpsSsGeneticAlgorithm original, Cloner cloner)
108      : base(original, cloner) {
109      Initialize();
110    }
111    public override IDeepCloneable Clone(Cloner cloner) {
112      return new AlpsSsGeneticAlgorithm(this, cloner);
113    }
114
115    public AlpsSsGeneticAlgorithm()
116      : base() {
117      Parameters.Add(new ValueParameter<IntArray>("PopulationSize", "The size of the population of solutions each layer.", new IntArray(new[] { 100 })));
118      Parameters.Add(new ValueParameter<IntValue>("MaximumGenerations", "The maximum number of generations that should be processed.", new IntValue(1000)));
119      Parameters.Add(new ConstrainedValueParameter<ISelector>("Selector", "The operator used to select solutions for reproduction."));
120      Parameters.Add(new ConstrainedValueParameter<ICrossover>("Crossover", "The operator used to cross solutions."));
121      Parameters.Add(new ValueParameter<PercentValue>("MutationProbability", "The probability that the mutation operator is applied on a solution.", new PercentValue(0.05)));
122      Parameters.Add(new OptionalConstrainedValueParameter<IManipulator>("Mutator", "The operator used to mutate solutions."));
123      Parameters.Add(new ValueParameter<IntValue>("Elites", "The numer of elite solutions which are kept in each generation.", new IntValue(1)));
124      Parameters.Add(new FixedValueParameter<BoolValue>("ReevaluateElites", "Flag to determine if elite individuals should be reevaluated (i.e., if stochastic fitness functions are used.)", new BoolValue(false)) { Hidden = true });
125      AgeInheritance = new ReductionOperation(ReductionOperations.Min);
126
127      var randomCreator = new RandomCreator();
128      var layer0Creator = new SubScopesCreator() { Name = "Create Layer Zero" };
129      var layer0Processor = new LayerUniformSubScopesProcessor();
130      var layer0VariableCreator = new VariableCreator();
131      var layer0SolutionsCreator = new SolutionsCreator();
132      var initializeAgeProcessor = new UniformSubScopesProcessor();
133      var initializeAge = new VariableCreator() { Name = "Initialize Age" };
134      var initializeLocalEvaluatedSolutions = new SubScopesCounter() { Name = "Initialize LayerEvaluatedSolutions" };
135      var initializeGlobalEvaluatedSolutions = new DataReducer() { Name = "Initialize EvaluatedSolutions" };
136      var resultsCollector = new ResultsCollector();
137      var mainLoop = new AlpsSsGeneticAlgorithmMainLoop();
138
139      OperatorGraph.InitialOperator = randomCreator;
140
141      randomCreator.SeedParameter.Value = null;
142      randomCreator.SetSeedRandomlyParameter.Value = null;
143      randomCreator.Successor = layer0Creator;
144
145      layer0Creator.NumberOfSubScopesParameter.Value = new IntValue(1);
146      layer0Creator.Successor = layer0Processor;
147
148      layer0Processor.Operator = layer0VariableCreator;
149      layer0Processor.Successor = initializeGlobalEvaluatedSolutions;
150
151      layer0VariableCreator.CollectedValues.Add(new ValueParameter<IntValue>("Layer", new IntValue(0)));
152      layer0VariableCreator.Successor = layer0SolutionsCreator;
153
154      layer0SolutionsCreator.NumberOfSolutionsParameter.ActualName = PopulationSizeParameter.Name;
155      layer0SolutionsCreator.Successor = initializeAgeProcessor;
156
157      initializeAgeProcessor.Operator = initializeAge;
158      initializeAgeProcessor.Successor = initializeLocalEvaluatedSolutions;
159
160      initializeAge.CollectedValues.Add(new ValueParameter<IntValue>("Age", new IntValue(0)));
161
162      initializeLocalEvaluatedSolutions.ValueParameter.ActualName = "LayerEvaluatedSolutions";
163
164      initializeGlobalEvaluatedSolutions.ReductionOperation.Value.Value = ReductionOperations.Sum;
165      initializeGlobalEvaluatedSolutions.TargetOperation.Value.Value = ReductionOperations.Assign;
166      initializeGlobalEvaluatedSolutions.ParameterToReduce.ActualName = "LayerEvaluatedSolutions";
167      initializeGlobalEvaluatedSolutions.TargetParameter.ActualName = "EvaluatedSolutions";
168      initializeGlobalEvaluatedSolutions.Successor = resultsCollector;
169
170      resultsCollector.CollectedValues.Add(new LookupParameter<IntValue>("Evaluated Solutions", null, "EvaluatedSolutions"));
171      resultsCollector.Successor = mainLoop;
172
173      foreach (var selector in ApplicationManager.Manager.GetInstances<ISelector>().Where(s => !(s is IMultiObjectiveSelector)).OrderBy(s => Name))
174        SelectorParameter.ValidValues.Add(selector);
175      var tournamentSelector = SelectorParameter.ValidValues.OfType<TournamentSelector>().FirstOrDefault();
176      if (tournamentSelector != null) {
177        tournamentSelector.GroupSizeParameter.Value = new IntValue(5);
178        SelectorParameter.Value = tournamentSelector;
179      }
180
181      ParameterizeSelectors();
182      Initialize();
183    }
184
185    #region Events
186    protected override void OnProblemChanged() {
187      base.OnProblemChanged();
188      ParameterizeSolutionsCreator();
189      ParameterizeMainLoop();
190      ParameterizeSelectors();
191      ParameterizeIterationBasedOperators();
192      UpdateCrossovers();
193      UpdateMutators();
194    }
195    protected override void Problem_SolutionCreatorChanged(object sender, EventArgs e) {
196      base.Problem_SolutionCreatorChanged(sender, e);
197      ParameterizeSolutionsCreator();
198    }
199    protected override void Problem_EvaluatorChanged(object sender, EventArgs e) {
200      base.Problem_EvaluatorChanged(sender, e);
201      ParameterizeSolutionsCreator();
202      ParameterizeMainLoop();
203      ParameterizeSelectors();
204    }
205    protected override void Problem_OperatorsChanged(object sender, EventArgs e) {
206      base.Problem_OperatorsChanged(sender, e);
207      ParameterizeIterationBasedOperators();
208      UpdateCrossovers();
209      UpdateMutators();
210    }
211    protected override void Evaluator_QualityParameter_ActualNameChanged(object sender, EventArgs e) {
212      base.Evaluator_QualityParameter_ActualNameChanged(sender, e);
213      ParameterizeMainLoop();
214      ParameterizeSelectors();
215    }
216    #endregion
217
218    #region Parameterization
219    private void Initialize() {
220      //
221    }
222    private void ParameterizeSolutionsCreator() {
223      //MainLoop.LayerUpdator.SolutionsCreator.EvaluatorParameter.ActualName = Problem.EvaluatorParameter.Name;
224      //MainLoop.LayerUpdator.SolutionsCreator.SolutionCreatorParameter.ActualName = Problem.SolutionCreatorParameter.Name;
225    }
226    private void ParameterizeMainLoop() {
227      //MainLoop.MaximizationParameter.ActualName = Problem.MaximizationParameter.Name;
228      //MainLoop.QualityParameter.ActualName = Problem.Evaluator.QualityParameter.ActualName;
229      //MainLoop.MainOperator.EvaluatorParameter.ActualName = Problem.EvaluatorParameter.Name;
230      //MainLoop.MainOperator.MaximizationParameter.ActualName = Problem.MaximizationParameter.Name;
231      //MainLoop.MainOperator.QualityParameter.ActualName = Problem.Evaluator.QualityParameter.ActualName;
232      //MainLoop.LayerUpdator.SolutionsCreator.NumberOfSolutionsParameter.ActualName = PopulationSizeParameter.Name;
233    }
234    private void ParameterizeSelectors() {
235      foreach (var selector in SelectorParameter.ValidValues) {
236        selector.CopySelected = new BoolValue(true);
237        // Explicit setting of NumberOfSelectedSubScopesParameter is not required anymore because the NumberOfSelectedSubScopesCalculator calculates it itself
238        //selector.NumberOfSelectedSubScopesParameter.Value = new IntValue(2 * (PopulationSize - Elites.Value));
239        selector.NumberOfSelectedSubScopesParameter.Hidden = true;
240        ParameterizeStochasticOperatorForLayer(selector);
241      }
242      if (Problem != null) {
243        foreach (var selector in SelectorParameter.ValidValues.OfType<ISingleObjectiveSelector>()) {
244          selector.MaximizationParameter.ActualName = Problem.MaximizationParameter.Name;
245          selector.MaximizationParameter.Hidden = true;
246          selector.QualityParameter.ActualName = Problem.Evaluator.QualityParameter.ActualName;
247          selector.QualityParameter.Hidden = true;
248        }
249      }
250    }
251    private void ParameterizeIterationBasedOperators() {
252      if (Problem != null) {
253        foreach (var @operator in Problem.Operators.OfType<IIterationBasedOperator>()) {
254          @operator.IterationsParameter.ActualName = "Generations";
255          @operator.IterationsParameter.Hidden = true;
256          @operator.MaximumIterationsParameter.ActualName = MaximumGenerationsParameter.Name;
257          @operator.MaximumIterationsParameter.Hidden = true;
258        }
259      }
260    }
261
262    protected override void ParameterizeStochasticOperatorForLayer(IOperator @operator) {
263      var stochasticOperator = @operator as IStochasticOperator;
264      if (stochasticOperator != null) {
265        stochasticOperator.RandomParameter.ActualName = GlobalRandomCreator.Name;
266        stochasticOperator.RandomParameter.Hidden = true;
267      }
268    }
269
270    #endregion
271
272    #region Updates
273    private void UpdateCrossovers() {
274      var oldCrossover = CrossoverParameter.Value;
275      var defaultCrossover = Problem.Operators.OfType<ICrossover>().FirstOrDefault();
276      CrossoverParameter.ValidValues.Clear();
277      foreach (var crossover in Problem.Operators.OfType<ICrossover>().OrderBy(c => c.Name)) {
278        ParameterizeStochasticOperatorForLayer(crossover);
279        CrossoverParameter.ValidValues.Add(crossover);
280      }
281      if (oldCrossover != null) {
282        var crossover = CrossoverParameter.ValidValues.FirstOrDefault(c => c.GetType() == oldCrossover.GetType());
283        if (crossover != null)
284          CrossoverParameter.Value = crossover;
285        else
286          oldCrossover = null;
287      }
288      if (oldCrossover == null && defaultCrossover != null)
289        CrossoverParameter.Value = defaultCrossover;
290    }
291    private void UpdateMutators() {
292      var oldMutator = MutatorParameter.Value;
293      MutatorParameter.ValidValues.Clear();
294      foreach (var mutator in Problem.Operators.OfType<IManipulator>().OrderBy(m => m.Name)) {
295        ParameterizeStochasticOperatorForLayer(mutator);
296        MutatorParameter.ValidValues.Add(mutator);
297      }
298      if (oldMutator != null) {
299        var mutator = MutatorParameter.ValidValues.FirstOrDefault(m => m.GetType() == oldMutator.GetType());
300        if (mutator != null)
301          MutatorParameter.Value = mutator;
302      }
303    }
304    #endregion
305  }
306}
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