source: branches/ALPS/HeuristicLab.Algorithms.ALPS.SteadyState/3.3/AlpsSsGeneticAlgorithmMainLoop.cs @ 12136

#region License Information
/* HeuristicLab
 * Copyright (C) 2002-2015 Heuristic and Evolutionary Algorithms Laboratory (HEAL)
 *
 * This file is part of HeuristicLab.
 *
 * HeuristicLab is free software: you can redistribute it and/or modify
 * it under the terms of the GNU General Public License as published by
 * the Free Software Foundation, either version 3 of the License, or
 * (at your option) any later version.
 *
 * HeuristicLab is distributed in the hope that it will be useful,
 * but WITHOUT ANY WARRANTY; without even the implied warranty of
 * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
 * GNU General Public License for more details.
 *
 * You should have received a copy of the GNU General Public License
 * along with HeuristicLab. If not, see <http://www.gnu.org/licenses/>.
 */
#endregion

using HeuristicLab.Common;
using HeuristicLab.Core;
using HeuristicLab.Data;
using HeuristicLab.Operators;
using HeuristicLab.Optimization.Operators;
using HeuristicLab.Parameters;
using HeuristicLab.Persistence.Default.CompositeSerializers.Storable;
using HeuristicLab.Selection;

namespace HeuristicLab.Algorithms.ALPS.SteadyState {
  [Item("AlpsSsGeneticAlgorithmMainLoop", "An ALPS steady-state genetic algorithm main loop operator.")]
  [StorableClass]
  public class AlpsSsGeneticAlgorithmMainLoop : AlgorithmOperator {
    #region Parameter Properties
    public ValueLookupParameter<BoolValue> MaximizationParameter {
      get { return (ValueLookupParameter<BoolValue>)Parameters["Maximization"]; }
    }
    public ScopeTreeLookupParameter<DoubleValue> QualityParameter {
      get { return (ScopeTreeLookupParameter<DoubleValue>)Parameters["Quality"]; }
    }
    public ILookupParameter<IntValue> MaximumIterationsParameter {
      get { return (ILookupParameter<IntValue>)Parameters["MaximumIterations"]; }
    }
    public ILookupParameter<IOperator> AnalyzerParameter {
      get { return (ILookupParameter<IOperator>)Parameters["Analyzer"]; }
    }
    public ILookupParameter<IOperator> LayerAnalyzerParameter {
      get { return (ILookupParameter<IOperator>)Parameters["LayerAnalyzer"]; }
    }
    #endregion

    [StorableConstructor]
    private AlpsSsGeneticAlgorithmMainLoop(bool deserializing)
      : base(deserializing) { }
    private AlpsSsGeneticAlgorithmMainLoop(AlpsSsGeneticAlgorithmMainLoop original, Cloner cloner)
      : base(original, cloner) { }
    public override IDeepCloneable Clone(Cloner cloner) {
      return new AlpsSsGeneticAlgorithmMainLoop(this, cloner);
    }

    public AlpsSsGeneticAlgorithmMainLoop()
      : base() {
      Parameters.Add(new ValueLookupParameter<BoolValue>("Maximization", "True if the problem is a maximization problem, otherwise false."));
      Parameters.Add(new ScopeTreeLookupParameter<DoubleValue>("Quality", "The value which represents the quality of a solution."));
      Parameters.Add(new LookupParameter<IntValue>("MaximumIterations", "The maximum number of iterations that the algorithm should process."));
      Parameters.Add(new LookupParameter<IOperator>("Analyzer", "The operator used to the analyze all individuals."));
      Parameters.Add(new LookupParameter<IOperator>("LayerAnalyzer", "The operator used to analyze each layer."));

      var variableCreator = new VariableCreator() { Name = "Initialize" };
      var randomScopeProcessor = new RandomLayerProcessor() { Name = "Select a layer" }; // TODO LayerSubScopeProcessor for Array conversion
      var isLayerZeroComperator = new Comparator() { Name = "IsLayerZero = Layer == 0" };
      var isLayerZeroBranch = new ConditionalBranch() { Name = "IsLayerZero?" };
      var isDoInitBranch = new ConditionalBranch() { Name = "DoInit?" };
      var setTargetIndedxToNextInit = new Assigner() { Name = "TargetIndex = NextInit" };
      var incrementNextInit = new IntCounter() { Name = "Incr. NextInit" };
      var checkInitFinished = new Comparator() { Name = "DoInit = NextInit >= PopulationSize" };
      var createWorkingScope = new BestSelector();
      var workingScopeProcessor = new SubScopesProcessor() { Name = "Working Scope Processor" };
      var createRandomIndividual = new SolutionsCreator() { Name = "Create random Individual" };
      var initializeAgeProcessor = new UniformSubScopesProcessor();
      var initializeAge = new Assigner() { Name = "Initialize Age" };
      var selectRandomTargetIndex = new RandomIntAssigner();
      var copyLayer = new BestSelector();
      var copyLayerProcessor = new SubScopesProcessor();
      var matingPoolCreator = new SteadyStateMatingPoolCreator() { Name = "Create MatingPool" };
      var matingPoolSize = new SubScopesCounter() { Name = "MatingPoolSize" };
      var matingPoolSizeMin2 = new Comparator() { Name = "ValidParents = MatingPoolSize >= 2" };
      var validParentsBranch = new ConditionalBranch() { Name = "ValidParents?" };
      var mainOperator = new EmptyOperator(); // TODO
      var reactivateInit = new Assigner() { Name = "DoInit = true" };
      var resetNextIndex = new Assigner() { Name = "NextInit = 1" };
      var resetTargetIndex = new Assigner() { Name = "TargetIndex = 0" };
      var clearMatingPool = new SubScopesRemover() { Name = "Clear WorkingScope" };
      var tryMoveUp = new EmptyOperator() { Name = "Try Move Up" }; // TODO
      var setNewIndividual = new EmptyOperator() { Name = "Set New Individual" };
      var iterationsComparator = new Comparator() { Name = "Iterations >= MaximumIterations" };
      var terminateBranch = new ConditionalBranch() { Name = "Terminate?" };


      OperatorGraph.InitialOperator = variableCreator;

      variableCreator.CollectedValues.Add(new ValueParameter<BoolValue>("DoInit", new BoolValue(false)));
      variableCreator.CollectedValues.Add(new ValueParameter<IntValue>("NextInit", new IntValue(0)));
      variableCreator.CollectedValues.Add(new ValueParameter<IntValue>("OpenLayers", new IntValue(1)));
      variableCreator.CollectedValues.Add(new ValueParameter<IntValue>("TargetIndex", new IntValue(0)));
      variableCreator.Successor = randomScopeProcessor;

      randomScopeProcessor.Operator = isLayerZeroComperator;

      isLayerZeroComperator.LeftSideParameter.ActualName = "Layer";
      isLayerZeroComperator.RightSideParameter.Value = new IntValue(0);
      isLayerZeroComperator.ResultParameter.ActualName = "IsLayerZero";
      isLayerZeroComperator.Comparison = new Comparison(ComparisonType.Equal);
      isLayerZeroComperator.Successor = isLayerZeroBranch;

      isLayerZeroBranch.ConditionParameter.ActualName = "IsLayerZero";
      isLayerZeroBranch.TrueBranch = isDoInitBranch;
      isLayerZeroBranch.FalseBranch = selectRandomTargetIndex;
      isLayerZeroBranch.Successor = tryMoveUp;

      isDoInitBranch.ConditionParameter.ActualName = "DoInit";
      isDoInitBranch.TrueBranch = setTargetIndedxToNextInit;
      isDoInitBranch.FalseBranch = selectRandomTargetIndex;

      setTargetIndedxToNextInit.LeftSideParameter.ActualName = "TargetIndex";
      setTargetIndedxToNextInit.RightSideParameter.ActualName = "NextInit";
      setTargetIndedxToNextInit.Successor = incrementNextInit;

      incrementNextInit.ValueParameter.ActualName = "NextInit";
      incrementNextInit.Increment = new IntValue(1);
      incrementNextInit.Successor = checkInitFinished;

      checkInitFinished.LeftSideParameter.ActualName = "NextInit";
      checkInitFinished.RightSideParameter.ActualName = "PopulationSize";
      checkInitFinished.Comparison = new Comparison(ComparisonType.GreaterOrEqual);
      checkInitFinished.ResultParameter.ActualName = "DoInit";
      checkInitFinished.Successor = createWorkingScope;

      createWorkingScope.NumberOfSelectedSubScopesParameter.Value = new IntValue(0);
      createWorkingScope.CopySelected = new BoolValue(false);
      createWorkingScope.Successor = workingScopeProcessor;

      workingScopeProcessor.Operators.Add(createRandomIndividual);
      workingScopeProcessor.Operators.Add(new EmptyOperator());

      createRandomIndividual.NumberOfSolutions = new IntValue(1);
      createRandomIndividual.Successor = initializeAgeProcessor;

      initializeAgeProcessor.Operator = initializeAge;

      initializeAge.LeftSideParameter.ActualName = "EvalsCreated";
      initializeAge.RightSideParameter.ActualName = "EvaluatedSolutions";

      selectRandomTargetIndex.LeftSideParameter.ActualName = "TargetIndex";
      selectRandomTargetIndex.MinimumParameter.Value = new IntValue(0);
      selectRandomTargetIndex.MaximumParameter.ActualName = "PopulationSize";
      selectRandomTargetIndex.Successor = copyLayer;

      copyLayer.NumberOfSelectedSubScopesParameter.ActualName = "LayerPopulationSize";
      copyLayer.CopySelected = new BoolValue(true);
      copyLayer.Successor = copyLayerProcessor;

      copyLayerProcessor.Operators.Add(new EmptyOperator());
      copyLayerProcessor.Operators.Add(matingPoolCreator);

      matingPoolCreator.Successor = matingPoolSize;

      matingPoolSize.ValueParameter.ActualName = "MatingPoolSize";
      matingPoolSize.Successor = matingPoolSizeMin2;

      matingPoolSizeMin2.LeftSideParameter.ActualName = "MatingPoolSize";
      matingPoolSizeMin2.RightSideParameter.Value = new IntValue(2);
      matingPoolSizeMin2.Comparison = new Comparison(ComparisonType.GreaterOrEqual);
      matingPoolSizeMin2.ResultParameter.ActualName = "ValidParents";
      matingPoolSizeMin2.Successor = validParentsBranch;

      validParentsBranch.TrueBranch = mainOperator;
      validParentsBranch.FalseBranch = reactivateInit;

      reactivateInit.Successor = resetNextIndex;
      reactivateInit.LeftSideParameter.ActualName = "DoInit";
      reactivateInit.RightSideParameter.Value = new BoolValue(true);

      resetNextIndex.Successor = resetTargetIndex;
      resetNextIndex.LeftSideParameter.ActualName = "NextIndex";
      resetNextIndex.RightSideParameter.Value = new IntValue(1);

      resetTargetIndex.Successor = clearMatingPool;
      resetTargetIndex.LeftSideParameter.ActualName = "TargetIndex";
      resetTargetIndex.RightSideParameter.Value = new IntValue(0);

      clearMatingPool.Successor = createRandomIndividual;

      tryMoveUp.Successor = setNewIndividual;

      setNewIndividual.Successor = iterationsComparator;

      iterationsComparator.Comparison = new Comparison(ComparisonType.GreaterOrEqual);
      iterationsComparator.LeftSideParameter.ActualName = "Iterations";
      iterationsComparator.RightSideParameter.ActualName = MaximumIterationsParameter.Name;
      iterationsComparator.ResultParameter.ActualName = "Terminate";
      iterationsComparator.Successor = terminateBranch;

      terminateBranch.ConditionParameter.ActualName = "Terminate";
      terminateBranch.FalseBranch = randomScopeProcessor;


    }

  }
}