source: branches/2457_ExpertSystem/HeuristicLab.Problems.GeneralizedQuadraticAssignment.Algorithms/3.3/LAHC/LAHC.cs @ 17717

#region License Information
/* HeuristicLab
 * Copyright (C) 2002-2017 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 System.Threading;
using HEAL.Attic;
using HeuristicLab.Common;
using HeuristicLab.Core;
using HeuristicLab.Data;
using HeuristicLab.Encodings.IntegerVectorEncoding;
using HeuristicLab.Optimization;
using HeuristicLab.Parameters;

namespace HeuristicLab.Problems.GeneralizedQuadraticAssignment.Algorithms.LAHC {
  [Item("LAHC (GQAP)", "Late-acceptance hill climber for the GQAP.")]
  [Creatable(CreatableAttribute.Categories.SingleSolutionAlgorithms)]
  [StorableType("41FABEE1-506A-45FE-A6D3-57932036AEC8")]
  public sealed class LAHC : StochasticAlgorithm<LAHCContext, IntegerVectorEncoding> {

    public override bool SupportsPause {
      get { return true; }
    }

    public override Type ProblemType {
      get { return typeof(GQAP); }
    }

    public new GQAP Problem {
      get { return (GQAP)base.Problem; }
      set { base.Problem = value; }
    }

    [Storable]
    private FixedValueParameter<IntValue> memorySizeParameter;
    public IFixedValueParameter<IntValue> MemorySizeParameter {
      get { return memorySizeParameter; }
    }

    public int MemorySize {
      get { return memorySizeParameter.Value.Value; }
      set { memorySizeParameter.Value.Value = value; }
    }

    [StorableConstructor]
    private LAHC(StorableConstructorFlag _) : base(_) { }
    private LAHC(LAHC original, Cloner cloner)
      : base(original, cloner) {
      memorySizeParameter = cloner.Clone(original.memorySizeParameter);
    }
    public LAHC() {
      Parameters.Add(memorySizeParameter = new FixedValueParameter<IntValue>("MemorySize", "The size of the memory, the shorter the more greedy LAHC performs.", new IntValue(100)));

      Problem = new GQAP();
    }
    
    public override IDeepCloneable Clone(Cloner cloner) {
      return new LAHC(this, cloner);
    }

    protected override void Initialize(CancellationToken token) {
      base.Initialize(token);

      Context.Problem = Problem;
      Context.LastSuccess = 0;
      
      var assign = new IntegerVector(Problem.ProblemInstance.Demands.Length, Context.Random, 0, Problem.ProblemInstance.Capacities.Length);
      var eval = Problem.ProblemInstance.Evaluate(assign);
      var fit = Problem.ProblemInstance.ToSingleObjective(eval);
      Context.EvaluatedSolutions++;

      var candidate = new GQAPSolution(assign, eval);
      
      Context.ReplaceIncumbent(Context.ToScope(candidate, fit));
      Context.BestQuality = fit;
      Context.BestSolution = (GQAPSolution)candidate.Clone();
      
      Context.Memory = new DoubleArray(Enumerable.Repeat(Context.BestQuality, MemorySize).ToArray());

      Results.Add(new Result("Iterations", new IntValue(Context.Iterations)));
      Results.Add(new Result("EvaluatedSolutions", new IntValue(Context.EvaluatedSolutions)));
      Results.Add(new Result("BestQuality", new DoubleValue(Context.BestQuality)));
      Results.Add(new Result("BestSolution", Context.BestSolution));

      try {
        Context.RunOperator(Analyzer, token);
      } catch (OperationCanceledException) { }
    }

    protected override void Run(CancellationToken cancellationToken) {
      base.Run(cancellationToken);
      var lastUpdate = ExecutionTime;
      while (!StoppingCriterion()) {
        var move = StochasticNMoveSingleMoveGenerator.GenerateOneMove(Context.Random,
          Context.Incumbent.Solution.Assignment, Problem.ProblemInstance.Capacities);
        var moveEval = GQAPNMoveEvaluator.Evaluate(move,
          Context.Incumbent.Solution.Assignment,
          Context.Incumbent.Solution.Evaluation, Problem.ProblemInstance);
        if (Context.Iterations % Problem.ProblemInstance.Demands.Length == 0)
          Context.EvaluatedSolutions++;
        var nextFit = Problem.ProblemInstance.ToSingleObjective(moveEval);
        var nextVec = new IntegerVector(Context.Incumbent.Solution.Assignment);
        NMoveMaker.Apply(nextVec, move);
        
        var v = Context.Iterations % Context.Memory.Length;
        Context.Iterations++;
        var prevFit = Context.Memory[v];

        var accept = nextFit <= Context.Incumbent.Fitness
                  || nextFit <= prevFit;

        if (accept && nextFit < Context.Incumbent.Fitness)
          Context.LastSuccess = Context.Iterations;

        if (accept) {
          Context.ReplaceIncumbent(Context.ToScope(new GQAPSolution(nextVec, moveEval), nextFit));
          if (nextFit < Context.BestQuality) {
            Context.BestSolution = (GQAPSolution)Context.Incumbent.Solution.Clone();
            Context.BestQuality = nextFit;
          }
        }

        if (Context.Incumbent.Fitness < prevFit)
          Context.Memory[v] = Context.Incumbent.Fitness;

        IResult result;
        if (ExecutionTime - lastUpdate > TimeSpan.FromSeconds(1)) {
          if (Results.TryGetValue("Iterations", out result))
            ((IntValue)result.Value).Value = Context.Iterations;
          else Results.Add(new Result("Iterations", new IntValue(Context.Iterations)));
          if (Results.TryGetValue("EvaluatedSolutions", out result))
            ((IntValue)result.Value).Value = Context.EvaluatedSolutions;
          else Results.Add(new Result("EvaluatedSolutions", new IntValue(Context.EvaluatedSolutions)));
          lastUpdate = ExecutionTime;
        }
        if (Results.TryGetValue("BestQuality", out result))
          ((DoubleValue)result.Value).Value = Context.BestQuality;
        else Results.Add(new Result("BestQuality", new DoubleValue(Context.BestQuality)));
        if (Results.TryGetValue("BestSolution", out result))
          result.Value = Context.BestSolution;
        else Results.Add(new Result("BestSolution", Context.BestSolution));

        try {
          Context.RunOperator(Analyzer, cancellationToken);
        } catch (OperationCanceledException) { }

        if (cancellationToken.IsCancellationRequested) break;
      }
      IResult result2;
      if (Results.TryGetValue("Iterations", out result2))
        ((IntValue)result2.Value).Value = Context.Iterations;
      else Results.Add(new Result("Iterations", new IntValue(Context.Iterations)));
      if (Results.TryGetValue("EvaluatedSolutions", out result2))
        ((IntValue)result2.Value).Value = Context.EvaluatedSolutions;
      else Results.Add(new Result("EvaluatedSolutions", new IntValue(Context.EvaluatedSolutions)));
    }
  }
}