Free cookie consent management tool by TermsFeed Policy Generator

source: branches/ALPS/HeuristicLab.Algorithms.ALPS/3.3/AlpsGeneticAlgorithm.cs @ 12531

Last change on this file since 12531 was 12531, checked in by pfleck, 9 years ago

#2269 Added Termination Criteria to standard ALPS-GA.

File size: 16.0 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.Collections.Generic;
24using System.Linq;
25using HeuristicLab.Common;
26using HeuristicLab.Core;
27using HeuristicLab.Data;
28using HeuristicLab.Operators;
29using HeuristicLab.Optimization;
30using HeuristicLab.Optimization.Operators;
31using HeuristicLab.Parameters;
32using HeuristicLab.Persistence.Default.CompositeSerializers.Storable;
33using HeuristicLab.PluginInfrastructure;
34using HeuristicLab.Random;
35using HeuristicLab.Selection;
36
37namespace HeuristicLab.Algorithms.ALPS {
38  [Item("ALPS Genetic Algorithm", "A genetic algorithm with an age-layered population structure.")]
39  [Creatable("Algorithms")]
40  [StorableClass]
41  public sealed class AlpsGeneticAlgorithm : Alps {
42    #region Parameter Properties
43    private IValueParameter<IntArray> PopulationSizeParameter {
44      get { return (IValueParameter<IntArray>)Parameters["PopulationSize"]; }
45    }
46    public IConstrainedValueParameter<ISelector> SelectorParameter {
47      get { return (IConstrainedValueParameter<ISelector>)Parameters["Selector"]; }
48    }
49    public IConstrainedValueParameter<ICrossover> CrossoverParameter {
50      get { return (IConstrainedValueParameter<ICrossover>)Parameters["Crossover"]; }
51    }
52    private IValueParameter<PercentValue> MutationProbabilityParameter {
53      get { return (IValueParameter<PercentValue>)Parameters["MutationProbability"]; }
54    }
55    public IConstrainedValueParameter<IManipulator> MutatorParameter {
56      get { return (IConstrainedValueParameter<IManipulator>)Parameters["Mutator"]; }
57    }
58    private IValueParameter<IntValue> ElitesParameter {
59      get { return (IValueParameter<IntValue>)Parameters["Elites"]; }
60    }
61    private IFixedValueParameter<BoolValue> ReevaluateElitesParameter {
62      get { return (IFixedValueParameter<BoolValue>)Parameters["ReevaluateElites"]; }
63    }
64    private IValueParameter<BoolValue> PlusSelectionParameter {
65      get { return (IValueParameter<BoolValue>)Parameters["PlusSelection"]; }
66    }
67    #endregion
68
69    #region Properties
70    public IntArray PopulationSize {
71      get { return PopulationSizeParameter.Value; }
72      set { PopulationSizeParameter.Value = value; }
73    }
74    public ISelector Selector {
75      get { return SelectorParameter.Value; }
76      set { SelectorParameter.Value = value; }
77    }
78    public ICrossover Crossover {
79      get { return CrossoverParameter.Value; }
80      set { CrossoverParameter.Value = value; }
81    }
82    public PercentValue MutationProbability {
83      get { return MutationProbabilityParameter.Value; }
84      set { MutationProbabilityParameter.Value = value; }
85    }
86    public IManipulator Mutator {
87      get { return MutatorParameter.Value; }
88      set { MutatorParameter.Value = value; }
89    }
90    public IntValue Elites {
91      get { return ElitesParameter.Value; }
92      set { ElitesParameter.Value = value; }
93    }
94    public bool ReevaluteElites {
95      get { return ReevaluateElitesParameter.Value.Value; }
96      set { ReevaluateElitesParameter.Value.Value = value; }
97    }
98    public bool PlusSelection {
99      get { return PlusSelectionParameter.Value.Value; }
100      set { PlusSelectionParameter.Value.Value = value; }
101    }
102
103    private AlpsGeneticAlgorithmMainLoop MainLoop {
104      get { return OperatorGraph.Iterate().OfType<AlpsGeneticAlgorithmMainLoop>().First(); }
105    }
106    #endregion
107
108    [Storable]
109    private ComparisonTerminator<IntValue> generationsTerminator;
110
111    [StorableConstructor]
112    private AlpsGeneticAlgorithm(bool deserializing)
113      : base(deserializing) { }
114    private AlpsGeneticAlgorithm(AlpsGeneticAlgorithm original, Cloner cloner)
115      : base(original, cloner) {
116      generationsTerminator = cloner.Clone(original.generationsTerminator);
117      Initialize();
118    }
119    public override IDeepCloneable Clone(Cloner cloner) {
120      return new AlpsGeneticAlgorithm(this, cloner);
121    }
122    public AlpsGeneticAlgorithm()
123      : base() {
124      Parameters.Add(new ValueParameter<IntArray>("PopulationSize", "The size of the population of solutions each layer.", new IntArray(new[] { 100 })));
125      Parameters.Add(new ConstrainedValueParameter<ISelector>("Selector", "The operator used to select solutions for reproduction."));
126      Parameters.Add(new ConstrainedValueParameter<ICrossover>("Crossover", "The operator used to cross solutions."));
127      Parameters.Add(new ValueParameter<PercentValue>("MutationProbability", "The probability that the mutation operator is applied on a solution.", new PercentValue(0.05)));
128      Parameters.Add(new OptionalConstrainedValueParameter<IManipulator>("Mutator", "The operator used to mutate solutions."));
129      Parameters.Add(new ValueParameter<IntValue>("Elites", "The numer of elite solutions which are kept in each generation.", new IntValue(1)));
130      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 });
131      Parameters.Add(new ValueParameter<BoolValue>("PlusSelection", "Include the parents in the selection of the invividuals for the next generation.", new BoolValue(false)) { Hidden = true });
132
133      var globalRandomCreator = new RandomCreator();
134      var layer0Creator = new SubScopesCreator() { Name = "Create Layer Zero" };
135      var layer0Processor = new LayerUniformSubScopesProcessor();
136      var localRandomCreator = new LocalRandomCreator();
137      var layerVariableCreator = new VariableCreator();
138      var layerSolutionsCreator = new SolutionsCreator();
139      var initializeAgeProcessor = new UniformSubScopesProcessor();
140      var initializeAge = new VariableCreator() { Name = "Initialize Age" };
141      var initializeLayerPopulationSize = new SubScopesCounter() { Name = "Init LayerPopulationCounter" };
142      var initializeLocalEvaluatedSolutions = new Assigner() { Name = "Initialize LayerEvaluatedSolutions" };
143      var initializeGlobalEvaluatedSolutions = new DataReducer() { Name = "Initialize EvaluatedSolutions" };
144      var resultsCollector = new ResultsCollector();
145      var mainLoop = new AlpsGeneticAlgorithmMainLoop();
146
147      OperatorGraph.InitialOperator = globalRandomCreator;
148
149      globalRandomCreator.RandomParameter.ActualName = "GlobalRandom";
150      globalRandomCreator.SeedParameter.Value = null;
151      globalRandomCreator.SetSeedRandomlyParameter.Value = null;
152      globalRandomCreator.Successor = layer0Creator;
153
154      layer0Creator.NumberOfSubScopesParameter.Value = new IntValue(1);
155      layer0Creator.Successor = layer0Processor;
156
157      layer0Processor.Operator = localRandomCreator;
158      layer0Processor.Successor = initializeGlobalEvaluatedSolutions;
159
160      localRandomCreator.Successor = layerVariableCreator;
161
162      layerVariableCreator.CollectedValues.Add(new ValueParameter<IntValue>("Layer", new IntValue(0)));
163      layerVariableCreator.Successor = layerSolutionsCreator;
164
165      layerSolutionsCreator.NumberOfSolutionsParameter.ActualName = PopulationSizeParameter.Name;
166      layerSolutionsCreator.Successor = initializeAgeProcessor;
167
168      initializeAgeProcessor.Operator = initializeAge;
169      initializeAgeProcessor.Successor = initializeLayerPopulationSize;
170
171      initializeLayerPopulationSize.ValueParameter.ActualName = "LayerPopulationSize";
172      initializeLayerPopulationSize.Successor = initializeLocalEvaluatedSolutions;
173
174      initializeAge.CollectedValues.Add(new ValueParameter<IntValue>("Age", new IntValue(0)));
175      initializeAge.Successor = null;
176
177      initializeLocalEvaluatedSolutions.LeftSideParameter.ActualName = "LayerEvaluatedSolutions";
178      initializeLocalEvaluatedSolutions.RightSideParameter.ActualName = "LayerPopulationSize";
179      initializeLocalEvaluatedSolutions.Successor = null;
180
181      initializeGlobalEvaluatedSolutions.ReductionOperation.Value.Value = ReductionOperations.Sum;
182      initializeGlobalEvaluatedSolutions.TargetOperation.Value.Value = ReductionOperations.Assign;
183      initializeGlobalEvaluatedSolutions.ParameterToReduce.ActualName = "LayerEvaluatedSolutions";
184      initializeGlobalEvaluatedSolutions.TargetParameter.ActualName = "EvaluatedSolutions";
185      initializeGlobalEvaluatedSolutions.Successor = resultsCollector;
186
187      resultsCollector.CollectedValues.Add(new LookupParameter<IntValue>("Evaluated Solutions", null, "EvaluatedSolutions"));
188      resultsCollector.Successor = mainLoop;
189
190      foreach (var selector in ApplicationManager.Manager.GetInstances<ISelector>().Where(s => !(s is IMultiObjectiveSelector)).OrderBy(s => Name))
191        SelectorParameter.ValidValues.Add(selector);
192      var tournamentSelector = SelectorParameter.ValidValues.OfType<TournamentSelector>().FirstOrDefault();
193      if (tournamentSelector != null) {
194        tournamentSelector.GroupSizeParameter.Value = new IntValue(4);
195        SelectorParameter.Value = tournamentSelector;
196      }
197
198      ParameterizeSelectors();
199      Initialize();
200    }
201
202    #region Events
203    protected override void OnProblemChanged() {
204      base.OnProblemChanged();
205      ParameterizeSolutionsCreator();
206      ParameterizeMainLoop();
207      ParameterizeSelectors();
208      ParameterizeIterationBasedOperators();
209      UpdateCrossovers();
210      UpdateMutators();
211    }
212    protected override void Problem_SolutionCreatorChanged(object sender, EventArgs e) {
213      base.Problem_SolutionCreatorChanged(sender, e);
214      ParameterizeSolutionsCreator();
215    }
216    protected override void Problem_EvaluatorChanged(object sender, EventArgs e) {
217      base.Problem_EvaluatorChanged(sender, e);
218      ParameterizeSolutionsCreator();
219      ParameterizeMainLoop();
220      ParameterizeSelectors();
221    }
222    protected override void Problem_OperatorsChanged(object sender, EventArgs e) {
223      base.Problem_OperatorsChanged(sender, e);
224      ParameterizeIterationBasedOperators();
225      UpdateCrossovers();
226      UpdateMutators();
227    }
228    protected override void Evaluator_QualityParameter_ActualNameChanged(object sender, EventArgs e) {
229      base.Evaluator_QualityParameter_ActualNameChanged(sender, e);
230      ParameterizeMainLoop();
231      ParameterizeSelectors();
232    }
233    #endregion
234
235    #region Parameterization
236    private void Initialize() {
237    }
238    private void ParameterizeSolutionsCreator() {
239      MainLoop.LayerUpdator.SolutionsCreator.EvaluatorParameter.ActualName = Problem.EvaluatorParameter.Name;
240      MainLoop.LayerUpdator.SolutionsCreator.SolutionCreatorParameter.ActualName = Problem.SolutionCreatorParameter.Name;
241    }
242    private void ParameterizeMainLoop() {
243      MainLoop.MaximizationParameter.ActualName = Problem.MaximizationParameter.Name;
244      MainLoop.QualityParameter.ActualName = Problem.Evaluator.QualityParameter.ActualName;
245      MainLoop.MainOperator.EvaluatorParameter.ActualName = Problem.EvaluatorParameter.Name;
246      MainLoop.MainOperator.MaximizationParameter.ActualName = Problem.MaximizationParameter.Name;
247      MainLoop.MainOperator.QualityParameter.ActualName = Problem.Evaluator.QualityParameter.ActualName;
248      MainLoop.LayerUpdator.SolutionsCreator.NumberOfSolutionsParameter.ActualName = PopulationSizeParameter.Name;
249    }
250    private void ParameterizeSelectors() {
251      foreach (var selector in SelectorParameter.ValidValues) {
252        selector.CopySelected = new BoolValue(true);
253        // Explicit setting of NumberOfSelectedSubScopesParameter is not required anymore because the NumberOfSelectedSubScopesCalculator calculates it itself
254        //selector.NumberOfSelectedSubScopesParameter.Value = new IntValue(2 * (PopulationSize - Elites.Value));
255        selector.NumberOfSelectedSubScopesParameter.Hidden = true;
256        ParameterizeStochasticOperatorForLayer(selector);
257      }
258      if (Problem != null) {
259        foreach (var selector in SelectorParameter.ValidValues.OfType<ISingleObjectiveSelector>()) {
260          selector.MaximizationParameter.ActualName = Problem.MaximizationParameter.Name;
261          selector.MaximizationParameter.Hidden = true;
262          selector.QualityParameter.ActualName = Problem.Evaluator.QualityParameter.ActualName;
263          selector.QualityParameter.Hidden = true;
264        }
265      }
266    }
267    private void ParameterizeIterationBasedOperators() {
268      if (Problem != null) {
269        foreach (var @operator in Problem.Operators.OfType<IIterationBasedOperator>()) {
270          @operator.IterationsParameter.ActualName = "Generations";
271          @operator.IterationsParameter.Hidden = true;
272          @operator.MaximumIterationsParameter.ActualName = generationsTerminator.ThresholdParameter.Name;
273          @operator.MaximumIterationsParameter.Hidden = true;
274        }
275      }
276    }
277
278    protected override ReductionOperations GetAgeInheritanceReduction(AgeInheritance ageInheritance) {
279      switch (ageInheritance) {
280        case ALPS.AgeInheritance.Older: return ReductionOperations.Max;
281        case ALPS.AgeInheritance.Agerage: return ReductionOperations.Avg;
282        case ALPS.AgeInheritance.Younger: return ReductionOperations.Min;
283        default: throw new NotSupportedException("AgeInheritance " + ageInheritance + " is not supported.");
284      }
285    }
286    #endregion
287
288    #region Updates
289    protected override void UpdateTerminators() {
290      var newTerminators = new Dictionary<ITerminator, bool> {
291        {generationsTerminator, !Terminators.Operators.Contains(generationsTerminator) || Terminators.Operators.ItemChecked(generationsTerminator)},
292      };
293
294      base.UpdateTerminators();
295
296      foreach (var newTerminator in newTerminators)
297        Terminators.Operators.Insert(0, newTerminator.Key, newTerminator.Value);
298    }
299    protected override void CreateTerminators() {
300      generationsTerminator = new ComparisonTerminator<IntValue>("Generations", ComparisonType.Less, new IntValue(1000)) { Name = "Generations" };
301      base.CreateTerminators();
302    }
303    private void UpdateCrossovers() {
304      var oldCrossover = CrossoverParameter.Value;
305      var defaultCrossover = Problem.Operators.OfType<ICrossover>().FirstOrDefault();
306      CrossoverParameter.ValidValues.Clear();
307      foreach (var crossover in Problem.Operators.OfType<ICrossover>().OrderBy(c => c.Name)) {
308        ParameterizeStochasticOperatorForLayer(crossover);
309        CrossoverParameter.ValidValues.Add(crossover);
310      }
311      if (oldCrossover != null) {
312        var crossover = CrossoverParameter.ValidValues.FirstOrDefault(c => c.GetType() == oldCrossover.GetType());
313        if (crossover != null)
314          CrossoverParameter.Value = crossover;
315        else
316          oldCrossover = null;
317      }
318      if (oldCrossover == null && defaultCrossover != null)
319        CrossoverParameter.Value = defaultCrossover;
320    }
321    private void UpdateMutators() {
322      var oldMutator = MutatorParameter.Value;
323      MutatorParameter.ValidValues.Clear();
324      foreach (var mutator in Problem.Operators.OfType<IManipulator>().OrderBy(m => m.Name)) {
325        ParameterizeStochasticOperatorForLayer(mutator);
326        MutatorParameter.ValidValues.Add(mutator);
327      }
328      if (oldMutator != null) {
329        var mutator = MutatorParameter.ValidValues.FirstOrDefault(m => m.GetType() == oldMutator.GetType());
330        if (mutator != null)
331          MutatorParameter.Value = mutator;
332      }
333    }
334    #endregion
335  }
336}
Note: See TracBrowser for help on using the repository browser.