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Changeset 14187 for trunk


Ignore:
Timestamp:
07/22/16 20:36:57 (8 years ago)
Author:
swagner
Message:

#2526: Updated year of copyrights in license headers

Location:
trunk/sources
Files:
4 edited

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  • trunk/sources/HeuristicLab.Algorithms.EvolutionStrategy/3.3/EvolutionStrategyMainLoop.cs

    r14185 r14187  
    1 ണഊഊഊഊഊഊഊഊഊഊഊഊഊഊഊഊഊഊഊഊഊഊഊഊഊഊഊഊഊഊഊഊഊഊഊഊഊഊഊഊഊഊഊഊഊഊഊഊഊഊഊഊഊഊഊഊഊഊഊഊഊഊഊഊഊഊഊഊഊഊഊഊഊഊഊഊഊഊഊഊഊഊഊഊഊഊഊഊഊഊഊഊഊഊഊഊഊഊഊഊഊഊഊഊഊഊഊഊഊഊഊഊഊഊഊഊഊഊഊഊഊഊഊഊഊഊഊഊഊഊഊഊഊഊഊഊഊഊഊഊഊഊഊഊഊഊഊഊഊഊഊഊഊഊഊഊഊഊഊഊഊഊഊഊഊഊഊഊഊഊഊഊഊഊഊഊഊഊഊഊഊഊഊഊഊഊഊഊഊഊഊഊഊഊഊഊഊഊഊഊഊഊഊഊഊഊഊഊഊഊഊഊഊഊഊഊഊഊഊഊഊഊഊഊഊഊഊഊഊഊഊഊഊഊഊഊഊഊഊഊഊഊഊഊഊഊഊഊഊഊഊഊഊഊഊഊഊഊഊഊഊഊഊഊഊഊഊഊഊഊഊഊഊഊഊഊഊഊഊഊഊഊഊഊഊഊഊഊഊഊഊഊഊഊഊഊഊഊഊഊഊഊഊഊഊഊഊഊഊഊഊഊഊഊഊഊഊഊഊഊഊഊഊഊഊഊഊഊ
     1#region License Information
     2/* HeuristicLab
     3 * Copyright (C) 2002-2016 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.EvolutionStrategy {
     32  /// <summary>
     33  /// An operator which represents the main loop of an evolution strategy (EvolutionStrategy).
     34  /// </summary>
     35  [Item("EvolutionStrategyMainLoop", "An operator which represents the main loop of an evolution strategy (EvolutionStrategy).")]
     36  [StorableClass]
     37  public sealed class EvolutionStrategyMainLoop : 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<DoubleValue> BestKnownQualityParameter {
     49      get { return (ValueLookupParameter<DoubleValue>)Parameters["BestKnownQuality"]; }
     50    }
     51    public ValueLookupParameter<IntValue> PopulationSizeParameter {
     52      get { return (ValueLookupParameter<IntValue>)Parameters["PopulationSize"]; }
     53    }
     54    public ValueLookupParameter<IntValue> ParentsPerChildParameter {
     55      get { return (ValueLookupParameter<IntValue>)Parameters["ParentsPerChild"]; }
     56    }
     57    public ValueLookupParameter<IntValue> ChildrenParameter {
     58      get { return (ValueLookupParameter<IntValue>)Parameters["Children"]; }
     59    }
     60    public ValueLookupParameter<BoolValue> PlusSelectionParameter {
     61      get { return (ValueLookupParameter<BoolValue>)Parameters["PlusSelection"]; }
     62    }
     63    public IValueLookupParameter<BoolValue> ReevaluateElitesParameter {
     64      get { return (IValueLookupParameter<BoolValue>)Parameters["ReevaluateElites"]; }
     65    }
     66    public ValueLookupParameter<IntValue> MaximumGenerationsParameter {
     67      get { return (ValueLookupParameter<IntValue>)Parameters["MaximumGenerations"]; }
     68    }
     69    public ValueLookupParameter<IOperator> MutatorParameter {
     70      get { return (ValueLookupParameter<IOperator>)Parameters["Mutator"]; }
     71    }
     72    public ValueLookupParameter<IOperator> RecombinatorParameter {
     73      get { return (ValueLookupParameter<IOperator>)Parameters["Recombinator"]; }
     74    }
     75    public ValueLookupParameter<IOperator> EvaluatorParameter {
     76      get { return (ValueLookupParameter<IOperator>)Parameters["Evaluator"]; }
     77    }
     78    public ValueLookupParameter<VariableCollection> ResultsParameter {
     79      get { return (ValueLookupParameter<VariableCollection>)Parameters["Results"]; }
     80    }
     81    public ValueLookupParameter<IOperator> AnalyzerParameter {
     82      get { return (ValueLookupParameter<IOperator>)Parameters["Analyzer"]; }
     83    }
     84    public LookupParameter<IntValue> EvaluatedSolutionsParameter {
     85      get { return (LookupParameter<IntValue>)Parameters["EvaluatedSolutions"]; }
     86    }
     87    private ScopeParameter CurrentScopeParameter {
     88      get { return (ScopeParameter)Parameters["CurrentScope"]; }
     89    }
     90    private ValueLookupParameter<IOperator> StrategyParameterManipulatorParameter {
     91      get { return (ValueLookupParameter<IOperator>)Parameters["StrategyParameterManipulator"]; }
     92    }
     93    private ValueLookupParameter<IOperator> StrategyParameterCrossoverParameter {
     94      get { return (ValueLookupParameter<IOperator>)Parameters["StrategyParameterCrossover"]; }
     95    }
     96
     97    public IScope CurrentScope {
     98      get { return CurrentScopeParameter.ActualValue; }
     99    }
     100    #endregion
     101
     102    [StorableConstructor]
     103    private EvolutionStrategyMainLoop(bool deserializing) : base(deserializing) { }
     104    private EvolutionStrategyMainLoop(EvolutionStrategyMainLoop original, Cloner cloner)
     105      : base(original, cloner) {
     106    }
     107    public override IDeepCloneable Clone(Cloner cloner) {
     108      return new EvolutionStrategyMainLoop(this, cloner);
     109    }
     110    public EvolutionStrategyMainLoop()
     111      : base() {
     112      Initialize();
     113    }
     114
     115    [StorableHook(HookType.AfterDeserialization)]
     116    private void AfterDeserialization() {
     117      // BackwardsCompatibility3.3
     118      #region Backwards compatible code, remove with 3.4
     119      if (!Parameters.ContainsKey("ReevaluateElites")) {
     120        Parameters.Add(new ValueLookupParameter<BoolValue>("ReevaluateElites", "Flag to determine if elite individuals should be reevaluated (i.e., if stochastic fitness functions are used.)"));
     121      }
     122      #endregion
     123    }
     124
     125    private void Initialize() {
     126      #region Create parameters
     127      Parameters.Add(new ValueLookupParameter<IRandom>("Random", "A pseudo random number generator."));
     128      Parameters.Add(new ValueLookupParameter<BoolValue>("Maximization", "True if the problem is a maximization problem, otherwise false."));
     129      Parameters.Add(new ScopeTreeLookupParameter<DoubleValue>("Quality", "The value which represents the quality of a solution."));
     130      Parameters.Add(new ValueLookupParameter<DoubleValue>("BestKnownQuality", "The best known quality value found so far."));
     131      Parameters.Add(new ValueLookupParameter<IntValue>("PopulationSize", "µ (mu) - the size of the population."));
     132      Parameters.Add(new ValueLookupParameter<IntValue>("ParentsPerChild", "ρ (rho) - how many parents should be recombined."));
     133      Parameters.Add(new ValueLookupParameter<IntValue>("Children", "λ (lambda) - the size of the offspring population."));
     134      Parameters.Add(new ValueLookupParameter<IntValue>("MaximumGenerations", "The maximum number of generations which should be processed."));
     135      Parameters.Add(new ValueLookupParameter<BoolValue>("PlusSelection", "True for plus selection (elitist population), false for comma selection (non-elitist population)."));
     136      Parameters.Add(new ValueLookupParameter<BoolValue>("ReevaluateElites", "Flag to determine if elite individuals should be reevaluated (i.e., if stochastic fitness functions are used.)"));
     137      Parameters.Add(new ValueLookupParameter<IOperator>("Mutator", "The operator used to mutate solutions."));
     138      Parameters.Add(new ValueLookupParameter<IOperator>("Recombinator", "The operator used to cross solutions."));
     139      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."));
     140      Parameters.Add(new ValueLookupParameter<VariableCollection>("Results", "The variable collection where results should be stored."));
     141      Parameters.Add(new ValueLookupParameter<IOperator>("Analyzer", "The operator used to analyze each generation."));
     142      Parameters.Add(new LookupParameter<IntValue>("EvaluatedSolutions", "The number of times solutions have been evaluated."));
     143      Parameters.Add(new ScopeParameter("CurrentScope", "The current scope which represents a population of solutions on which the EvolutionStrategy should be applied."));
     144      Parameters.Add(new ValueLookupParameter<IOperator>("StrategyParameterManipulator", "The operator to mutate the endogeneous strategy parameters."));
     145      Parameters.Add(new ValueLookupParameter<IOperator>("StrategyParameterCrossover", "The operator to cross the endogeneous strategy parameters."));
     146      #endregion
     147
     148      #region Create operators
     149      VariableCreator variableCreator = new VariableCreator();
     150      ResultsCollector resultsCollector1 = new ResultsCollector();
     151      Placeholder analyzer1 = new Placeholder();
     152      WithoutRepeatingBatchedRandomSelector selector = new WithoutRepeatingBatchedRandomSelector();
     153      SubScopesProcessor subScopesProcessor1 = new SubScopesProcessor();
     154      Comparator useRecombinationComparator = new Comparator();
     155      ConditionalBranch useRecombinationBranch = new ConditionalBranch();
     156      ChildrenCreator childrenCreator = new ChildrenCreator();
     157      UniformSubScopesProcessor uniformSubScopesProcessor1 = new UniformSubScopesProcessor();
     158      Placeholder recombinator = new Placeholder();
     159      Placeholder strategyRecombinator = new Placeholder();
     160      Placeholder strategyMutator1 = new Placeholder();
     161      Placeholder mutator1 = new Placeholder();
     162      SubScopesRemover subScopesRemover = new SubScopesRemover();
     163      UniformSubScopesProcessor uniformSubScopesProcessor2 = new UniformSubScopesProcessor();
     164      Placeholder strategyMutator2 = new Placeholder();
     165      Placeholder mutator2 = new Placeholder();
     166      UniformSubScopesProcessor uniformSubScopesProcessor3 = new UniformSubScopesProcessor();
     167      Placeholder evaluator = new Placeholder();
     168      SubScopesCounter subScopesCounter = new SubScopesCounter();
     169      ConditionalBranch plusOrCommaReplacementBranch = new ConditionalBranch();
     170      MergingReducer plusReplacement = new MergingReducer();
     171      RightReducer commaReplacement = new RightReducer();
     172      BestSelector bestSelector = new BestSelector();
     173      RightReducer rightReducer = new RightReducer();
     174      IntCounter intCounter = new IntCounter();
     175      Comparator comparator = new Comparator();
     176      Placeholder analyzer2 = new Placeholder();
     177      ConditionalBranch conditionalBranch = new ConditionalBranch();
     178      ConditionalBranch reevaluateElitesBranch = new ConditionalBranch();
     179      SubScopesProcessor subScopesProcessor2 = new SubScopesProcessor();
     180      UniformSubScopesProcessor uniformSubScopesProcessor4 = new UniformSubScopesProcessor();
     181      Placeholder evaluator2 = new Placeholder();
     182      SubScopesCounter subScopesCounter2 = new SubScopesCounter();
     183
     184
     185      variableCreator.CollectedValues.Add(new ValueParameter<IntValue>("Generations", new IntValue(0))); // Class EvolutionStrategy expects this to be called Generations
     186
     187      resultsCollector1.CollectedValues.Add(new LookupParameter<IntValue>("Generations"));
     188      resultsCollector1.ResultsParameter.ActualName = "Results";
     189
     190      analyzer1.Name = "Analyzer (placeholder)";
     191      analyzer1.OperatorParameter.ActualName = AnalyzerParameter.Name;
     192
     193      selector.Name = "ES Random Selector";
     194      selector.RandomParameter.ActualName = RandomParameter.Name;
     195      selector.ParentsPerChildParameter.ActualName = ParentsPerChildParameter.Name;
     196      selector.ChildrenParameter.ActualName = ChildrenParameter.Name;
     197
     198      useRecombinationComparator.Name = "ParentsPerChild > 1";
     199      useRecombinationComparator.LeftSideParameter.ActualName = ParentsPerChildParameter.Name;
     200      useRecombinationComparator.RightSideParameter.Value = new IntValue(1);
     201      useRecombinationComparator.Comparison = new Comparison(ComparisonType.Greater);
     202      useRecombinationComparator.ResultParameter.ActualName = "UseRecombination";
     203
     204      useRecombinationBranch.Name = "Use Recombination?";
     205      useRecombinationBranch.ConditionParameter.ActualName = "UseRecombination";
     206
     207      childrenCreator.ParentsPerChild = null;
     208      childrenCreator.ParentsPerChildParameter.ActualName = ParentsPerChildParameter.Name;
     209
     210      recombinator.Name = "Recombinator (placeholder)";
     211      recombinator.OperatorParameter.ActualName = RecombinatorParameter.Name;
     212
     213      strategyRecombinator.Name = "Strategy Parameter Recombinator (placeholder)";
     214      strategyRecombinator.OperatorParameter.ActualName = StrategyParameterCrossoverParameter.Name;
     215
     216      strategyMutator1.Name = "Strategy Parameter Manipulator (placeholder)";
     217      strategyMutator1.OperatorParameter.ActualName = StrategyParameterManipulatorParameter.Name;
     218
     219      mutator1.Name = "Mutator (placeholder)";
     220      mutator1.OperatorParameter.ActualName = MutatorParameter.Name;
     221
     222      subScopesRemover.RemoveAllSubScopes = true;
     223
     224      strategyMutator2.Name = "Strategy Parameter Manipulator (placeholder)";
     225      strategyMutator2.OperatorParameter.ActualName = StrategyParameterManipulatorParameter.Name;
     226
     227      mutator2.Name = "Mutator (placeholder)";
     228      mutator2.OperatorParameter.ActualName = MutatorParameter.Name;
     229
     230      uniformSubScopesProcessor3.Parallel.Value = true;
     231
     232      evaluator.Name = "Evaluator (placeholder)";
     233      evaluator.OperatorParameter.ActualName = EvaluatorParameter.Name;
     234
     235      subScopesCounter.Name = "Increment EvaluatedSolutions";
     236      subScopesCounter.ValueParameter.ActualName = EvaluatedSolutionsParameter.Name;
     237
     238      plusOrCommaReplacementBranch.ConditionParameter.ActualName = PlusSelectionParameter.Name;
     239
     240      bestSelector.CopySelected = new BoolValue(false);
     241      bestSelector.MaximizationParameter.ActualName = MaximizationParameter.Name;
     242      bestSelector.NumberOfSelectedSubScopesParameter.ActualName = PopulationSizeParameter.Name;
     243      bestSelector.QualityParameter.ActualName = QualityParameter.Name;
     244
     245      intCounter.Increment = new IntValue(1);
     246      intCounter.ValueParameter.ActualName = "Generations";
     247
     248      comparator.Comparison = new Comparison(ComparisonType.GreaterOrEqual);
     249      comparator.LeftSideParameter.ActualName = "Generations";
     250      comparator.ResultParameter.ActualName = "Terminate";
     251      comparator.RightSideParameter.ActualName = MaximumGenerationsParameter.Name;
     252
     253      analyzer2.Name = "Analyzer (placeholder)";
     254      analyzer2.OperatorParameter.ActualName = AnalyzerParameter.Name;
     255
     256      conditionalBranch.ConditionParameter.ActualName = "Terminate";
     257
     258      reevaluateElitesBranch.ConditionParameter.ActualName = "ReevaluateElites";
     259      reevaluateElitesBranch.Name = "Reevaluate elites ?";
     260
     261      uniformSubScopesProcessor4.Parallel.Value = true;
     262
     263      evaluator2.Name = "Evaluator (placeholder)";
     264      evaluator2.OperatorParameter.ActualName = EvaluatorParameter.Name;
     265
     266      subScopesCounter2.Name = "Increment EvaluatedSolutions";
     267      subScopesCounter2.ValueParameter.ActualName = EvaluatedSolutionsParameter.Name;
     268      #endregion
     269
     270      #region Create operator graph
     271      OperatorGraph.InitialOperator = variableCreator;
     272      variableCreator.Successor = resultsCollector1;
     273      resultsCollector1.Successor = analyzer1;
     274      analyzer1.Successor = selector;
     275      selector.Successor = subScopesProcessor1;
     276      subScopesProcessor1.Operators.Add(new EmptyOperator());
     277      subScopesProcessor1.Operators.Add(useRecombinationComparator);
     278      subScopesProcessor1.Successor = plusOrCommaReplacementBranch;
     279      useRecombinationComparator.Successor = useRecombinationBranch;
     280      useRecombinationBranch.TrueBranch = childrenCreator;
     281      useRecombinationBranch.FalseBranch = uniformSubScopesProcessor2;
     282      useRecombinationBranch.Successor = uniformSubScopesProcessor3;
     283      childrenCreator.Successor = uniformSubScopesProcessor1;
     284      uniformSubScopesProcessor1.Operator = recombinator;
     285      uniformSubScopesProcessor1.Successor = null;
     286      recombinator.Successor = strategyRecombinator;
     287      strategyRecombinator.Successor = strategyMutator1;
     288      strategyMutator1.Successor = mutator1;
     289      mutator1.Successor = subScopesRemover;
     290      subScopesRemover.Successor = null;
     291      uniformSubScopesProcessor2.Operator = strategyMutator2;
     292      uniformSubScopesProcessor2.Successor = null;
     293      strategyMutator2.Successor = mutator2;
     294      mutator2.Successor = null;
     295      uniformSubScopesProcessor3.Operator = evaluator;
     296      uniformSubScopesProcessor3.Successor = subScopesCounter;
     297      evaluator.Successor = null;
     298      subScopesCounter.Successor = null;
     299
     300      plusOrCommaReplacementBranch.TrueBranch = reevaluateElitesBranch;
     301      reevaluateElitesBranch.TrueBranch = subScopesProcessor2;
     302      reevaluateElitesBranch.FalseBranch = null;
     303      subScopesProcessor2.Operators.Add(uniformSubScopesProcessor4);
     304      subScopesProcessor2.Operators.Add(new EmptyOperator());
     305      uniformSubScopesProcessor4.Operator = evaluator2;
     306      uniformSubScopesProcessor4.Successor = subScopesCounter2;
     307      subScopesCounter2.Successor = null;
     308      reevaluateElitesBranch.Successor = plusReplacement;
     309
     310      plusOrCommaReplacementBranch.FalseBranch = commaReplacement;
     311      plusOrCommaReplacementBranch.Successor = bestSelector;
     312      bestSelector.Successor = rightReducer;
     313      rightReducer.Successor = intCounter;
     314      intCounter.Successor = comparator;
     315      comparator.Successor = analyzer2;
     316      analyzer2.Successor = conditionalBranch;
     317      conditionalBranch.FalseBranch = selector;
     318      conditionalBranch.TrueBranch = null;
     319      conditionalBranch.Successor = null;
     320      #endregion
     321    }
     322
     323    public override IOperation Apply() {
     324      if (MutatorParameter.ActualValue == null)
     325        return null;
     326      return base.Apply();
     327    }
     328  }
     329}
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