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Changeset 3740


Ignore:
Timestamp:
05/10/10 15:10:36 (15 years ago)
Author:
abeham
Message:

#893

  • Changed the way offspring selection works
  • Added depth parameter to ScopeTreeLookupParameter
Location:
trunk/sources
Files:
3 edited

Legend:

Unmodified
Added
Removed
  • trunk/sources/HeuristicLab.Algorithms.OffspringSelectionGeneticAlgorithm/3.3/OffspringSelectionGeneticAlgorithmMainOperator.cs

    r3715 r3740  
    134134      WeightedParentsQualityComparator qualityComparer2 = new WeightedParentsQualityComparator();
    135135      SubScopesRemover subScopesRemover = new SubScopesRemover();
    136       ConditionalSelector conditionalSelector = new ConditionalSelector();
    137136      OffspringSelector offspringSelector = new OffspringSelector();
    138137      SubScopesProcessor subScopesProcessor2 = new SubScopesProcessor();
     
    201200      subScopesRemover.RemoveAllSubScopes = true;
    202201
    203       conditionalSelector.CopySelected = new BoolValue(false);
    204       conditionalSelector.ConditionParameter.ActualName = "SuccessfulOffspring";
    205 
    206202      offspringSelector.CurrentSuccessRatioParameter.ActualName = CurrentSuccessRatioParameter.Name;
    207       offspringSelector.LuckyLosersParameter.ActualName = "OSLuckyLosers";
    208203      offspringSelector.MaximumSelectionPressureParameter.ActualName = MaximumSelectionPressureParameter.Name;
    209204      offspringSelector.SelectionPressureParameter.ActualName = SelectionPressureParameter.Name;
    210205      offspringSelector.SuccessRatioParameter.ActualName = SuccessRatioParameter.Name;
    211       offspringSelector.WinnersParameter.ActualName = "OSWinners";
     206      offspringSelector.OffspringPopulationParameter.ActualName = "OffspringPopulation";
     207      offspringSelector.OffspringPopulationWinnersParameter.ActualName = "OffspringPopulationWinners";
     208      offspringSelector.SuccessfulOffspringParameter.ActualName = "SuccessfulOffspring";
    212209
    213210      bestSelector.CopySelected = new BoolValue(false);
     
    230227      childrenCreator.Successor = uniformSubScopesProcessor;
    231228      uniformSubScopesProcessor.Operator = crossover;
    232       uniformSubScopesProcessor.Successor = conditionalSelector;
     229      uniformSubScopesProcessor.Successor = null;
    233230      crossover.Successor = osBeforeMutationBranch;
    234231      osBeforeMutationBranch.TrueBranch = evaluator1;
  • trunk/sources/HeuristicLab.Parameters/3.3/ScopeTreeLookupParameter.cs

    r3687 r3740  
    5555      depth = 1;
    5656    }
     57    public ScopeTreeLookupParameter(string name, int depth)
     58      : base(name) {
     59      this.depth = depth;
     60    }
    5761    public ScopeTreeLookupParameter(string name, string description)
    5862      : base(name, description) {
    5963      depth = 1;
    6064    }
     65    public ScopeTreeLookupParameter(string name, string description, int depth)
     66      : base(name, description) {
     67      this.depth = depth;
     68    }
    6169    public ScopeTreeLookupParameter(string name, string description, string actualName)
    6270      : base(name, description, actualName) {
    6371      depth = 1;
     72    }
     73    public ScopeTreeLookupParameter(string name, string description, string actualName, int depth)
     74      : base(name, description, actualName) {
     75      this.depth = depth;
    6476    }
    6577    [StorableConstructor]
  • trunk/sources/HeuristicLab.Selection/3.3/OffspringSelector.cs

    r3489 r3740  
    4646      get { return (LookupParameter<DoubleValue>)Parameters["CurrentSuccessRatio"]; }
    4747    }
    48     public LookupParameter<ItemList<IScope>> WinnersParameter {
    49       get { return (LookupParameter<ItemList<IScope>>)Parameters["Winners"]; }
     48    public LookupParameter<ItemList<IScope>> OffspringPopulationParameter {
     49      get { return (LookupParameter<ItemList<IScope>>)Parameters["OffspringPopulation"]; }
    5050    }
    51     public LookupParameter<ItemList<IScope>> LuckyLosersParameter {
    52       get { return (LookupParameter<ItemList<IScope>>)Parameters["LuckyLosers"]; }
     51    public LookupParameter<IntValue> OffspringPopulationWinnersParameter {
     52      get { return (LookupParameter<IntValue>)Parameters["OffspringPopulationWinners"]; }
     53    }
     54    public ScopeTreeLookupParameter<BoolValue> SuccessfulOffspringParameter {
     55      get { return (ScopeTreeLookupParameter<BoolValue>)Parameters["SuccessfulOffspring"]; }
    5356    }
    5457    public OperatorParameter OffspringCreatorParameter {
     
    6770      Parameters.Add(new ValueLookupParameter<DoubleValue>("SelectionPressure", "The amount of selection pressure currently necessary to fulfill the success ratio."));
    6871      Parameters.Add(new ValueLookupParameter<DoubleValue>("CurrentSuccessRatio", "The current success ratio indicates how much of the successful offspring have already been generated."));
    69       Parameters.Add(new LookupParameter<ItemList<IScope>>("Winners", "Temporary store of the successful offspring."));
    70       Parameters.Add(new LookupParameter<ItemList<IScope>>("LuckyLosers", "Temporary store of the lucky losers."));
     72      Parameters.Add(new LookupParameter<ItemList<IScope>>("OffspringPopulation", "Temporary store of the offspring population."));
     73      Parameters.Add(new LookupParameter<IntValue>("OffspringPopulationWinners", "Temporary store the number of successful offspring in the offspring population."));
     74      Parameters.Add(new ScopeTreeLookupParameter<BoolValue>("SuccessfulOffspring", "True if the offspring was more successful than its parents.", 2));
    7175      Parameters.Add(new OperatorParameter("OffspringCreator", "The operator used to create new offspring."));
    7276    }
     
    7781      IScope scope = ExecutionContext.Scope;
    7882      IScope parents = scope.SubScopes[0];
    79       IScope children = scope.SubScopes[1];
     83      IScope offspring = scope.SubScopes[1];
    8084      int populationSize = parents.SubScopes.Count;
     85      int offspringSize = offspring.SubScopes.Count;
    8186
    8287      // retrieve actual selection pressure and success ratio
     
    9297      }
    9398
    94       // retrieve winners and lucky losers
    95       ItemList<IScope> winners = WinnersParameter.ActualValue;
    96       if (winners == null) {
    97         winners = new ItemList<IScope>();
    98         WinnersParameter.ActualValue = winners;
     99      // retrieve next population
     100      ItemList<IScope> population = OffspringPopulationParameter.ActualValue;
     101      IntValue successfulOffspring;
     102      if (population == null) {
     103        population = new ItemList<IScope>();
     104        OffspringPopulationParameter.ActualValue = population;
    99105        selectionPressure.Value = 0; // initialize selection pressure for this round
    100106        currentSuccessRatio.Value = 0; // initialize current success ratio for this round
     107        successfulOffspring = new IntValue(0);
     108        OffspringPopulationWinnersParameter.ActualValue = successfulOffspring;
     109      } else successfulOffspring = OffspringPopulationWinnersParameter.ActualValue;
     110     
     111      int worseOffspringNeeded = (int)((1 - successRatio) * populationSize) - (population.Count - successfulOffspring.Value);
     112      int successfulOffspringAdded = 0;
     113
     114      // implement the ActualValue fetch here - otherwise the parent scope would also be included, given that there may be 1000 or more parents, this is quite unnecessary
     115      string tname = SuccessfulOffspringParameter.TranslatedName;
     116      double tmpSelPress = selectionPressure.Value, tmpSelPressInc = 1.0 / populationSize;
     117      for (int i = 0; i < offspringSize; i++) {
     118        // fetch value
     119        IVariable tmpVar;
     120        if (!offspring.SubScopes[i].Variables.TryGetValue(tname, out tmpVar)) throw new InvalidOperationException(Name + ": Could not determine if an offspring was successful or not.");
     121        BoolValue tmp = (tmpVar.Value as BoolValue);
     122        if (tmp == null) throw new InvalidOperationException(Name + ": The variable that indicates whether an offspring is successful or not must contain a BoolValue.");
     123
     124        // add to population
     125        if (tmp.Value) {
     126          population.Add(offspring.SubScopes[i]);
     127          successfulOffspringAdded++;
     128        } else if (worseOffspringNeeded > 0 || tmpSelPress >= maxSelPress) {
     129          population.Add(offspring.SubScopes[i]);
     130          worseOffspringNeeded--;
     131        }
     132        tmpSelPress += tmpSelPressInc;
     133        if (population.Count == populationSize) break;
    101134      }
    102       ItemList<IScope> luckyLosers = LuckyLosersParameter.ActualValue;
    103       if (luckyLosers == null) {
    104         luckyLosers = new ItemList<IScope>();
    105         LuckyLosersParameter.ActualValue = luckyLosers;
    106       }
    107 
    108       // separate new offspring in winners and lucky losers, the unlucky losers are discarded, sorry guys
    109       int winnersCount = 0;
    110       int losersCount = 0;
    111       ScopeList offspring = children.SubScopes[1].SubScopes; // the winners
    112       winnersCount += offspring.Count;
    113       winners.AddRange(offspring);
    114       offspring = children.SubScopes[0].SubScopes; // the losers
    115       losersCount += offspring.Count;
    116       while (offspring.Count > 0 && ((1 - successRatio) * populationSize > luckyLosers.Count ||
    117             selectionPressure.Value >= maxSelPress)) {
    118         luckyLosers.Add(offspring[0]);
    119         offspring.RemoveAt(0);
    120       }
     135      successfulOffspring.Value += successfulOffspringAdded;
    121136
    122137      // calculate actual selection pressure and success ratio
    123       selectionPressure.Value += (winnersCount + losersCount) / ((double)populationSize);
    124       currentSuccessRatio.Value = winners.Count / ((double)populationSize);
     138      selectionPressure.Value += offspringSize / (double)populationSize;
     139      currentSuccessRatio.Value = successfulOffspring.Value / ((double)populationSize);
    125140
    126141      // check if enough children have been generated
    127142      if (((selectionPressure.Value < maxSelPress) && (currentSuccessRatio.Value < successRatio)) ||
    128           ((winners.Count + luckyLosers.Count) < populationSize)) {
     143          (population.Count < populationSize)) {
    129144        // more children required -> reduce left and start children generation again
    130145        scope.SubScopes.Remove(parents);
    131         scope.SubScopes.Remove(children);
     146        scope.SubScopes.Remove(offspring);
    132147        while(parents.SubScopes.Count > 0)
    133148          scope.SubScopes.Add(parents.SubScopes[0]);
     
    138153      } else {
    139154        // enough children generated
    140         children.SubScopes.Clear();
    141         while (children.SubScopes.Count < populationSize) {
    142           if (winners.Count > 0) {
    143             children.SubScopes.Add((IScope)winners[0]);
    144             winners.RemoveAt(0);
    145           } else {
    146             children.SubScopes.Add((IScope)luckyLosers[0]);
    147             luckyLosers.RemoveAt(0);
    148           }
    149         }
     155        offspring.SubScopes.Clear();
     156        offspring.SubScopes.AddRange(population);
    150157
    151         scope.Variables.Remove(WinnersParameter.ActualName);
    152         scope.Variables.Remove(LuckyLosersParameter.ActualName);
     158        scope.Variables.Remove(OffspringPopulationParameter.ActualName);
     159        scope.Variables.Remove(OffspringPopulationWinnersParameter.ActualName);
    153160        return base.Apply();
    154161      }
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