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

Last change on this file since 16724 was 15572, checked in by abeham, 7 years ago

#1614:

  • fixed a bug in GRASP where solutions in the elite set would be mutated
  • introduced termination criteria when reaching best-known quality
  • tweaked generating random numbers in StochasticNMoveSingleMoveGenerator
  • changed DiscreteLocationCrossover to use an allele from one of the parents instead of introducing a mutation in case no feasible insert location is found
  • changed OSGA maxselpress to 500
  • slight change to contexts, introduced single-objectiveness much earlier in the class hierachy
    • limited ContextAlgorithm to SingleObjectiveBasicProblems (doesn't matter here)
File size: 4.7 KB
Line 
1#region License Information
2/* HeuristicLab
3 * Copyright (C) 2002-2017 Heuristic and Evolutionary Algorithms Laboratory (HEAL)
4 *
5 * This file is part of HeuristicLab.
6 *
7 * HeuristicLab is free software: you can redistribute it and/or modify
8 * it under the terms of the GNU General Public License as published by
9 * the Free Software Foundation, either version 3 of the License, or
10 * (at your option) any later version.
11 *
12 * HeuristicLab is distributed in the hope that it will be useful,
13 * but WITHOUT ANY WARRANTY; without even the implied warranty of
14 * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
15 * GNU General Public License for more details.
16 *
17 * You should have received a copy of the GNU General Public License
18 * along with HeuristicLab. If not, see <http://www.gnu.org/licenses/>.
19 */
20#endregion
21
22using System;
23using System.Collections.Generic;
24using System.Linq;
25using HeuristicLab.Common;
26using HeuristicLab.Core;
27using HeuristicLab.Data;
28using HeuristicLab.Encodings.IntegerVectorEncoding;
29using HeuristicLab.Optimization;
30using HeuristicLab.Parameters;
31using HeuristicLab.Persistence.Default.CompositeSerializers.Storable;
32using HeuristicLab.Random;
33
34namespace HeuristicLab.Problems.GeneralizedQuadraticAssignment {
35  [Item("Stochastic N-Move SingleMoveGenerator", "Randomly samples a single N-Move.")]
36  [StorableClass]
37  public class StochasticNMoveSingleMoveGenerator : GQAPNMoveGenerator, IStochasticOperator, ISingleMoveGenerator {
38   
39    public ILookupParameter<IRandom> RandomParameter {
40      get { return (ILookupParameter<IRandom>)Parameters["Random"]; }
41    }
42
43    [StorableConstructor]
44    protected StochasticNMoveSingleMoveGenerator(bool deserializing) : base(deserializing) { }
45    protected StochasticNMoveSingleMoveGenerator(StochasticNMoveSingleMoveGenerator original, Cloner cloner) : base(original, cloner) { }
46    public StochasticNMoveSingleMoveGenerator()
47      : base() {
48      Parameters.Add(new LookupParameter<IRandom>("Random", "The random number generator that should be used."));
49    }
50
51    public override IDeepCloneable Clone(Cloner cloner) {
52      return new StochasticNMoveSingleMoveGenerator(this, cloner);
53    }
54
55    public static NMove GenerateUpToN(IRandom random, IntegerVector assignment, int n, DoubleArray capacities) {
56      return GenerateExactlyN(random, assignment, random.Next(n) + 1, capacities);
57    }
58
59    public static NMove GenerateOneMove(IRandom random, IntegerVector assignment, DoubleArray capacities) {
60      var locations = capacities.Length;
61      if (locations <= 1) throw new ArgumentException("There must be at least two locations.");
62      var dim = assignment.Length;
63      var equip = random.Next(dim);
64      var equipments = new List<int>(1) { equip };
65
66      var reassignment = new int[dim];
67      reassignment[equip] = 1 + (assignment[equip] + random.Next(1, locations)) % locations;
68
69      return new NMove(reassignment, equipments);
70    }
71
72    public static NMove GenerateTwoMove(IRandom random, IntegerVector assignment, DoubleArray capacities) {
73      var locations = capacities.Length;
74      if (locations <= 1) throw new ArgumentException("There must be at least two locations.");
75      var dim = assignment.Length;
76      var equipments = new List<int>(2) { random.Next(dim) };
77      equipments.Add((equipments[0] + random.Next(1, dim)) % dim);
78
79      var reassignment = new int[dim];
80      for (var i = 0; i < 2; i++) {
81        var equip = equipments[i];
82        reassignment[equip] = 1 + (assignment[equip] + random.Next(1, locations)) % locations;
83      }
84      return new NMove(reassignment, equipments);
85    }
86
87    public static NMove GenerateExactlyN(IRandom random, IntegerVector assignment, int n, DoubleArray capacities) {
88      if (n == 1) return GenerateOneMove(random, assignment, capacities);
89      if (n == 2) return GenerateTwoMove(random, assignment, capacities);
90      var locations = capacities.Length;
91      if (locations <= 1) throw new ArgumentException("There must be at least two locations.");
92      var dim = assignment.Length;
93      var equipments = Enumerable.Range(0, dim).SampleRandomWithoutRepetition(random, n, dim).ToList();
94
95      var reassignment = new int[dim];
96      for (var i = 0; i < n; i++) {
97        var equip = equipments[i];
98        reassignment[equip] = 1 + (assignment[equip] + random.Next(1, locations)) % locations;
99      }
100      return new NMove(reassignment, equipments);
101    }
102
103    public override IEnumerable<NMove> GenerateMoves(IntegerVector assignment, int n, GQAPInstance problemInstance) {
104      yield return GenerateUpToN(RandomParameter.ActualValue, assignment, n, problemInstance.Capacities);
105    }
106  }
107}
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