source: branches/ScatterSearch/HeuristicLab.Algorithms.ScatterSearch/3.3/ScatterSearch.cs @ 7771

#region License Information
/* HeuristicLab
 * Copyright (C) 2002-2012 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 System;
using System.Linq;
using HeuristicLab.Analysis;
using HeuristicLab.Common;
using HeuristicLab.Core;
using HeuristicLab.Data;
using HeuristicLab.Operators;
using HeuristicLab.Optimization;
using HeuristicLab.Optimization.Operators;
using HeuristicLab.Parameters;
using HeuristicLab.Persistence.Default.CompositeSerializers.Storable;
using HeuristicLab.Random;
using HeuristicLab.Selection;

namespace HeuristicLab.Algorithms.ScatterSearch {
  /// <summary>
  /// A scatter search algorithm.
  /// </summary>
  [Item("Scatter Search", "A scatter search algorithm.")]
  [Creatable("Algorithms")]
  [StorableClass]
  public sealed class ScatterSearch : HeuristicOptimizationEngineAlgorithm, IStorableContent {
    public string Filename { get; set; }

    #region Problem Properties
    public override Type ProblemType {
      get { return typeof(ISingleObjectiveHeuristicOptimizationProblem); }
    }
    public new ISingleObjectiveHeuristicOptimizationProblem Problem {
      get { return (ISingleObjectiveHeuristicOptimizationProblem)base.Problem; }
      set { base.Problem = value; }
    }
    #endregion

    #region Parameter Properties
    public IValueParameter<MultiAnalyzer> AnalyzerParameter {
      get { return (IValueParameter<MultiAnalyzer>)Parameters["Analyzer"]; }
    }
    public ConstrainedValueParameter<ICrossover> CrossoverParameter {
      get { return (ConstrainedValueParameter<ICrossover>)Parameters["Crossover"]; }
    }
    public ConstrainedValueParameter<ILocalImprovementOperator> ImproverParameter {
      get { return (ConstrainedValueParameter<ILocalImprovementOperator>)Parameters["Improver"]; }
    }
    public ConstrainedValueParameter<DiversityCalculator> DiversityCalculatorParameter {
      get { return (ConstrainedValueParameter<DiversityCalculator>)Parameters["DiversityCalculator"]; }
    }
    public IValueParameter<IntValue> MaximumIterationsParameter {
      get { return (IValueParameter<IntValue>)Parameters["MaximumIterations"]; }
    }
    public IValueParameter<IntValue> NumberOfHighQualitySolutionsParameter {
      get { return (IValueParameter<IntValue>)Parameters["NumberOfHighQualitySolutions"]; }
    }
    public IValueParameter<IntValue> PopulationSizeParameter {
      get { return (IValueParameter<IntValue>)Parameters["PopulationSize"]; }
    }
    public IValueParameter<IntValue> ReferenceSetSizeParameter {
      get { return (IValueParameter<IntValue>)Parameters["ReferenceSetSize"]; }
    }
    public IValueParameter<IntValue> SeedParameter {
      get { return (IValueParameter<IntValue>)Parameters["Seed"]; }
    }
    public IValueParameter<BoolValue> SetSeedRandomlyParameter {
      get { return (IValueParameter<BoolValue>)Parameters["SetSeedRandomly"]; }
    }
    #endregion

    #region Properties
    private MultiAnalyzer Analyzer {
      get { return AnalyzerParameter.Value; }
      set { AnalyzerParameter.Value = value; }
    }
    private ICrossover Crossover {
      get { return CrossoverParameter.Value; }
      set { CrossoverParameter.Value = value; }
    }
    private ILocalImprovementOperator Improver {
      get { return ImproverParameter.Value; }
      set { ImproverParameter.Value = value; }
    }
    private DiversityCalculator DiversityCalculator {
      get { return DiversityCalculatorParameter.Value; }
      set { DiversityCalculatorParameter.Value = value; }
    }
    private IntValue MaximumIterations {
      get { return MaximumIterationsParameter.Value; }
      set { MaximumIterationsParameter.Value = value; }
    }
    private IntValue NumberOfHighQualitySolutions {
      get { return NumberOfHighQualitySolutionsParameter.Value; }
      set { NumberOfHighQualitySolutionsParameter.Value = value; }
    }
    private IntValue PopulationSize {
      get { return PopulationSizeParameter.Value; }
      set { PopulationSizeParameter.Value = value; }
    }
    private IntValue ReferenceSetSize {
      get { return ReferenceSetSizeParameter.Value; }
      set { ReferenceSetSizeParameter.Value = value; }
    }
    private IntValue Seed {
      get { return SeedParameter.Value; }
      set { SeedParameter.Value = value; }
    }
    private BoolValue SetSeedRandomly {
      get { return SetSeedRandomlyParameter.Value; }
      set { SetSeedRandomlyParameter.Value = value; }
    }
    public RandomCreator RandomCreator {
      get { return (RandomCreator)OperatorGraph.InitialOperator; }
    }
    public SolutionsCreator SolutionsCreator {
      get { return (SolutionsCreator)RandomCreator.Successor; }
    }
    public ScatterSearchMainLoop MainLoop {
      get { return FindMainLoop(SolutionsCreator.Successor); }
    }

    [Storable]
    private BestAverageWorstQualityAnalyzer qualityAnalyzer;
    #endregion

    [StorableConstructor]
    private ScatterSearch(bool deserializing) : base(deserializing) { }
    [StorableHook(HookType.AfterDeserialization)]
    private void AfterDeserialization() {
      Initialize();
    }
    private ScatterSearch(ScatterSearch original, Cloner cloner)
      : base(original, cloner) {
      qualityAnalyzer = cloner.Clone(original.qualityAnalyzer);
      Initialize();
    }
    public override IDeepCloneable Clone(Cloner cloner) {
      return new ScatterSearch(this, cloner);
    }
    public ScatterSearch()
      : base() {
      #region Create parameters
      Parameters.Add(new ValueParameter<MultiAnalyzer>("Analyzer", "The operator used to analyze the solution and moves.", new MultiAnalyzer()));
      Parameters.Add(new ConstrainedValueParameter<ICrossover>("Crossover", "The operator used to combine solutions."));
      Parameters.Add(new ConstrainedValueParameter<ILocalImprovementOperator>("Improver", "The operator used to improve solutions."));
      Parameters.Add(new ConstrainedValueParameter<DiversityCalculator>("DiversityCalculator", "The operator used to calculate the diversity of two solutions."));
      Parameters.Add(new ValueParameter<IntValue>("MaximumIterations", "The maximum number of generations which should be processed.", new IntValue(100)));
      Parameters.Add(new ValueParameter<IntValue>("NumberOfHighQualitySolutions", "The number of high quality solutions that should be added to the reference set.", new IntValue(10)));
      Parameters.Add(new ValueParameter<IntValue>("PopulationSize", "The size of the population.", new IntValue(300)));
      Parameters.Add(new ValueParameter<IntValue>("ReferenceSetSize", "The size of the reference set.", new IntValue(100)));
      Parameters.Add(new ValueParameter<IntValue>("Seed", "The random seed used to initialize the new pseudo random number generator.", new IntValue(0)));
      Parameters.Add(new ValueParameter<BoolValue>("SetSeedRandomly", "True if the random seed should be set to a random value, otherwise false.", new BoolValue(true)));
      #endregion

      #region Create operators
      RandomCreator randomCreator = new RandomCreator();
      SolutionsCreator solutionsCreator = new SolutionsCreator();
      UniformSubScopesProcessor uniformSubScopesProcessor = new UniformSubScopesProcessor();
      Placeholder solutionEvaluator = new Placeholder();
      Placeholder solutionImprover = new Placeholder();
      BestSelector bestSelector = new BestSelector();
      VariableCreator variableCreator = new VariableCreator();
      ResultsCollector resultsCollector = new ResultsCollector();
      ScatterSearchMainLoop mainLoop = new ScatterSearchMainLoop();
      #endregion

      #region Create operator graph
      OperatorGraph.InitialOperator = randomCreator;
      randomCreator.RandomParameter.ActualName = "Random";
      randomCreator.SeedParameter.ActualName = SeedParameter.Name;
      randomCreator.SetSeedRandomlyParameter.ActualName = SetSeedRandomlyParameter.Name;
      randomCreator.Successor = solutionsCreator;

      solutionsCreator.Name = "DiversificationGenerationMethod";
      solutionsCreator.NumberOfSolutionsParameter.ActualName = "PopulationSize";
      solutionsCreator.Successor = uniformSubScopesProcessor;

      uniformSubScopesProcessor.Operator = solutionImprover;
      uniformSubScopesProcessor.Successor = bestSelector;

      solutionImprover.Name = "SolutionImprover";
      solutionImprover.OperatorParameter.ActualName = "Improver";
      solutionImprover.Successor = solutionEvaluator;

      solutionEvaluator.Name = "SolutionEvaluator";
      solutionEvaluator.OperatorParameter.ActualName = "Evaluator";
      solutionEvaluator.Successor = null;

      bestSelector.NumberOfSelectedSubScopesParameter.ActualName = NumberOfHighQualitySolutionsParameter.Name;
      bestSelector.CopySelected = new BoolValue(false);
      bestSelector.Successor = variableCreator;

      variableCreator.CollectedValues.Add(new ValueParameter<IntValue>("Iterations", new IntValue(0)));
      variableCreator.CollectedValues.Add(new ValueParameter<BoolValue>("NewSolutions", new BoolValue(false)));
      variableCreator.Successor = resultsCollector;

      resultsCollector.CollectedValues.Add(new LookupParameter<IntValue>("Iterations"));
      resultsCollector.ResultsParameter.ActualName = "Results";
      resultsCollector.Successor = mainLoop;

      mainLoop.MaximumIterationsParameter.ActualName = MaximumIterationsParameter.Name;
      mainLoop.RandomParameter.ActualName = randomCreator.RandomParameter.ActualName;
      mainLoop.ResultsParameter.ActualName = "Results";
      mainLoop.AnalyzerParameter.ActualName = AnalyzerParameter.Name;
      mainLoop.IterationsParameter.ActualName = "Iterations";
      mainLoop.CrossoverParameter.ActualName = CrossoverParameter.Name;
      mainLoop.PopulationSizeParameter.ActualName = PopulationSizeParameter.Name;
      mainLoop.NumberOfHighQualitySolutionsParameter.ActualName = NumberOfHighQualitySolutionsParameter.Name;
      mainLoop.Successor = null;
      #endregion

      qualityAnalyzer = new BestAverageWorstQualityAnalyzer();
      ParameterizeAnalyzers();
      UpdateAnalyzers();

      Initialize();
    }

    public override void Prepare() {
      base.Prepare();
    }

    #region Events
    protected override void OnProblemChanged() {
      ParameterizeStochasticOperator(Problem.SolutionCreator);
      ParameterizeStochasticOperator(Problem.Evaluator);
      foreach (IOperator op in Problem.Operators) ParameterizeStochasticOperator(op);
      ParameterizeAnalyzers();
      ParameterizeMainLoop();
      ParameterizeSolutionsCreator();
      UpdateAnalyzers();
      UpdateCrossovers();
      UpdateDiversityCalculators();
      UpdateImprovers();
      UpdateDiversityCalculators();
      Problem.Evaluator.QualityParameter.ActualNameChanged += new EventHandler(Evaluator_QualityParameter_ActualNameChanged);
      base.OnProblemChanged();
    }
    protected override void Problem_SolutionCreatorChanged(object sender, EventArgs e) {
      ParameterizeStochasticOperator(Problem.SolutionCreator);
      ParameterizeSolutionsCreator();
      base.Problem_SolutionCreatorChanged(sender, e);
    }
    protected override void Problem_EvaluatorChanged(object sender, EventArgs e) {
      ParameterizeStochasticOperator(Problem.Evaluator);
      ParameterizeSolutionsCreator();
      ParameterizeMainLoop();
      ParameterizeAnalyzers();
      Problem.Evaluator.QualityParameter.ActualNameChanged += new EventHandler(Evaluator_QualityParameter_ActualNameChanged);
      base.Problem_EvaluatorChanged(sender, e);
    }
    protected override void Problem_OperatorsChanged(object sender, EventArgs e) {
      foreach (IOperator op in Problem.Operators) ParameterizeStochasticOperator(op);
      UpdateAnalyzers();
      UpdateCrossovers();
      UpdateDiversityCalculators();
      UpdateImprovers();
      ParameterizeMainLoop();
      ParameterizeAnalyzers();
      base.Problem_OperatorsChanged(sender, e);
    }
    private void Evaluator_QualityParameter_ActualNameChanged(object sender, EventArgs e) {
      ParameterizeMainLoop();
      ParameterizeAnalyzers();
    }
    #endregion

    #region Helpers
    private void Initialize() {
      if (Problem != null) {
        Problem.Evaluator.QualityParameter.ActualNameChanged += new EventHandler(Evaluator_QualityParameter_ActualNameChanged);
      }
    }
    private void UpdateAnalyzers() {
      Analyzer.Operators.Clear();
      if (Problem != null) {
        foreach (IAnalyzer analyzer in Problem.Operators.OfType<IAnalyzer>()) {
          foreach (IScopeTreeLookupParameter param in analyzer.Parameters.OfType<IScopeTreeLookupParameter>())
            param.Depth = 1;
          Analyzer.Operators.Add(analyzer, analyzer.EnabledByDefault);
        }
      }
      Analyzer.Operators.Add(qualityAnalyzer, qualityAnalyzer.EnabledByDefault);
    }
    private void UpdateCrossovers() {
      ICrossover oldCrossover = CrossoverParameter.Value;
      CrossoverParameter.ValidValues.Clear();
      ICrossover defaultCrossover = Problem.Operators.OfType<ICrossover>().FirstOrDefault();

      CrossoverParameter.ValidValues.Add(new TravelingSalesman.TravelingSalesmanPathRelinker());
      CrossoverParameter.ValidValues.Add(new Knapsack.KnapsackPathRelinker());

      foreach (ICrossover crossover in Problem.Operators.OfType<ICrossover>().OrderBy(x => x.Name))
        CrossoverParameter.ValidValues.Add(crossover);

      foreach (var crossover in CrossoverParameter.ValidValues.OfType<Knapsack.INBinaryVectorCrossover>())
        crossover.ParentsParameter.ActualName = "KnapsackSolution"; // temporary solution for the knapsack problem

      if (oldCrossover != null) {
        ICrossover crossover = CrossoverParameter.ValidValues.FirstOrDefault(x => x.GetType() == oldCrossover.GetType());
        if (crossover != null) CrossoverParameter.Value = crossover;
        else oldCrossover = null;
      }
      if (oldCrossover == null && defaultCrossover != null)
        CrossoverParameter.Value = defaultCrossover;
    }
    private void UpdateDiversityCalculators() {
      DiversityCalculator oldDiversityCalculator = DiversityCalculatorParameter.Value;
      DiversityCalculatorParameter.ValidValues.Clear();
      DiversityCalculator defaultDiversityCalculator = Problem.Operators.OfType<DiversityCalculator>().FirstOrDefault();

      DiversityCalculatorParameter.ValidValues.Add(new Knapsack.BinaryVectorDiversityCalculator());
      DiversityCalculatorParameter.ValidValues.Add(new TravelingSalesman.PermutationDiversityCalculator());

      foreach (DiversityCalculator diversityCalculator in Problem.Operators.OfType<DiversityCalculator>().OrderBy(x => x.Name))
        DiversityCalculatorParameter.ValidValues.Add(diversityCalculator);

      if (oldDiversityCalculator != null) {
        DiversityCalculator diversityCalculator = DiversityCalculatorParameter.ValidValues.FirstOrDefault(x => x.GetType() == oldDiversityCalculator.GetType());
        if (diversityCalculator != null) DiversityCalculatorParameter.Value = diversityCalculator;
        else oldDiversityCalculator = null;
      }
      if (oldDiversityCalculator == null && defaultDiversityCalculator != null)
        DiversityCalculatorParameter.Value = defaultDiversityCalculator;
    }
    private void UpdateImprovers() {
      ILocalImprovementOperator oldImprover = ImproverParameter.Value;
      ImproverParameter.ValidValues.Clear();
      ILocalImprovementOperator defaultImprover = Problem.Operators.OfType<ILocalImprovementOperator>().FirstOrDefault();

      ImproverParameter.ValidValues.Add(new Knapsack.KnapsackImprovementOperator());
      ImproverParameter.ValidValues.Add(new TravelingSalesman.TravelingSalesmanImprovementOperator());

      foreach (ILocalImprovementOperator improver in Problem.Operators.OfType<ILocalImprovementOperator>().OrderBy(x => x.Name))
        ImproverParameter.ValidValues.Add(improver);

      foreach (var improver in ImproverParameter.ValidValues.OfType<IScatterSearchTargetProcessor>())
        improver.TargetParameter.ActualName = "KnapsackSolution"; // temporary solution for the knapsack problem

      if (oldImprover != null) {
        ILocalImprovementOperator improver = ImproverParameter.ValidValues.FirstOrDefault(x => x.GetType() == oldImprover.GetType());
        if (improver != null) ImproverParameter.Value = improver;
        else oldImprover = null;
      }
      if (oldImprover == null && defaultImprover != null)
        ImproverParameter.Value = defaultImprover;
    }
    private void ParameterizeSolutionsCreator() {
      SolutionsCreator.EvaluatorParameter.ActualName = Problem.EvaluatorParameter.Name;
      SolutionsCreator.SolutionCreatorParameter.ActualName = Problem.SolutionCreatorParameter.Name;
    }
    private void ParameterizeMainLoop() {
      if (Problem != null) {
        MainLoop.BestKnownQualityParameter.ActualName = Problem.BestKnownQualityParameter.Name;
        MainLoop.MaximizationParameter.ActualName = Problem.MaximizationParameter.Name;
        MainLoop.QualityParameter.ActualName = Problem.Evaluator.QualityParameter.ActualName;
      }
    }
    private void ParameterizeStochasticOperator(IOperator op) {
      if (op is IStochasticOperator) {
        IStochasticOperator stOp = (IStochasticOperator)op;
        stOp.RandomParameter.ActualName = RandomCreator.RandomParameter.ActualName;
        stOp.RandomParameter.Hidden = true;
      }
    }
    //private void ParameterizeScatterSearchTargetProcessor(IOperator op) {
    //  if (op is IScatterSearchTargetProcessor) {
    //    IScatterSearchTargetProcessor ssOp = (IScatterSearchTargetProcessor)op;
    //    ssOp.TargetParameter.ActualName = "KnapsackSolution"; // temporary solution for the knapsack problem
    //    ssOp.TargetParameter.Hidden = true;
    //  }
    //}
    private void ParameterizeAnalyzers() {
      qualityAnalyzer.ResultsParameter.ActualName = "Results";
      qualityAnalyzer.ResultsParameter.Hidden = true;
      if (Problem != null) {
        qualityAnalyzer.MaximizationParameter.ActualName = Problem.MaximizationParameter.Name;
        qualityAnalyzer.MaximizationParameter.Hidden = true;
        qualityAnalyzer.QualityParameter.Hidden = false;
        qualityAnalyzer.BestKnownQualityParameter.ActualName = Problem.BestKnownQualityParameter.Name;
        qualityAnalyzer.BestKnownQualityParameter.Hidden = true;
      } else {
        qualityAnalyzer.MaximizationParameter.Hidden = false;
        qualityAnalyzer.BestKnownQualityParameter.Hidden = false;
      }
    }
    private ScatterSearchMainLoop FindMainLoop(IOperator start) {
      IOperator mainLoop = start;
      while (mainLoop != null && !(mainLoop is ScatterSearchMainLoop))
        mainLoop = ((SingleSuccessorOperator)mainLoop).Successor;
      if (mainLoop == null) return null;
      else return (ScatterSearchMainLoop)mainLoop;
    }
    #endregion
  }
}