source: branches/1614_GeneralizedQAP/HeuristicLab.Problems.GeneralizedQuadraticAssignment/3.3/Moves/ExhaustiveOneMoveGenerator.cs @ 16724

#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
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 * GNU General Public License for more details.
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#endregion

using System;
using System.Collections.Generic;
using HeuristicLab.Common;
using HeuristicLab.Core;
using HeuristicLab.Encodings.IntegerVectorEncoding;
using HeuristicLab.Optimization;
using HeuristicLab.Parameters;
using HeuristicLab.Persistence.Default.CompositeSerializers.Storable;
using HeuristicLab.Random;

namespace HeuristicLab.Problems.GeneralizedQuadraticAssignment {
  [Item("Exhaustive 1-Move MoveGenerator", "Exhaustively generates all possible 1-moves.")]
  [StorableClass]
  public class ExhaustiveOneMoveGenerator : GQAPNMoveGenerator, IStochasticOperator, IExhaustiveMoveGenerator {
    
    public ILookupParameter<IRandom> RandomParameter {
      get { return (ILookupParameter<IRandom>)Parameters["Random"]; }
    }

    [StorableConstructor]
    protected ExhaustiveOneMoveGenerator(bool deserializing) : base(deserializing) { }
    protected ExhaustiveOneMoveGenerator(ExhaustiveOneMoveGenerator original, Cloner cloner) : base(original, cloner) { }
    public ExhaustiveOneMoveGenerator()
      : base() {
      Parameters.Add(new LookupParameter<IRandom>("Random", "The random number generator that should be used."));
      NParameter.Value.Value = 1;
      NParameter.Hidden = true;
    }

    public override IDeepCloneable Clone(Cloner cloner) {
      return new ExhaustiveOneMoveGenerator(this, cloner);
    }

    public static IEnumerable<NMove> Generate(IntegerVector assignment, GQAPInstance problemInstance) {
      var equipments = problemInstance.Demands.Length;
      var locations = problemInstance.Capacities.Length;
      var tmp = new int[equipments];
      for (var e = 0; e < equipments; e++) {
        var indices = new List<int> { e };
        for (var l = 0; l < locations; l++) {
          if (assignment[e] == l) continue;
          var reassign = (int[])tmp.Clone();
          reassign[e] = l + 1;
          yield return new NMove(reassign, indices);
        }
      }
    }

    public static IEnumerable<NMove> GenerateAllNxM(GQAPInstance problemInstance) {
      var equipments = problemInstance.Demands.Length;
      var locations = problemInstance.Capacities.Length;
      var tmp = new int[equipments];
      for (var e = 0; e < equipments; e++) {
        var indices = new List<int> { e };
        for (var l = 0; l < locations; l++) {
          var reassign = (int[])tmp.Clone();
          reassign[e] = l + 1;
          yield return new NMove(reassign, indices);
        }
      }
    }

    public override IEnumerable<NMove> GenerateMoves(IntegerVector assignment, int n, GQAPInstance problemInstance) {
      if (n != 1) throw new ArgumentException("N must be equal to 1 for the exhaustive 1-move generator.");
      var random = RandomParameter.ActualValue;
      return Generate(assignment, problemInstance).Shuffle(random);
    }
  }
}