[7407] | 1 | #region License Information
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| 2 | /* HeuristicLab
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[16728] | 3 | * Copyright (C) 2002-2018 Heuristic and Evolutionary Algorithms Laboratory (HEAL)
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[7407] | 4 | *
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| 5 | * This file is part of HeuristicLab.
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| 6 | *
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| 7 | * HeuristicLab is free software: you can redistribute it and/or modify
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| 8 | * it under the terms of the GNU General Public License as published by
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| 9 | * the Free Software Foundation, either version 3 of the License, or
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| 10 | * (at your option) any later version.
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| 11 | *
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| 12 | * HeuristicLab is distributed in the hope that it will be useful,
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| 13 | * but WITHOUT ANY WARRANTY; without even the implied warranty of
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| 14 | * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
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| 15 | * GNU General Public License for more details.
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| 16 | *
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| 17 | * You should have received a copy of the GNU General Public License
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| 18 | * along with HeuristicLab. If not, see <http://www.gnu.org/licenses/>.
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| 19 | */
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| 20 | #endregion
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| 21 |
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[15562] | 22 | using System;
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[7407] | 23 | using System.Collections.Generic;
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| 24 | using HeuristicLab.Common;
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| 25 | using HeuristicLab.Core;
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| 26 | using HeuristicLab.Encodings.IntegerVectorEncoding;
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| 27 | using HeuristicLab.Optimization;
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| 28 | using HeuristicLab.Parameters;
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| 29 | using HeuristicLab.Persistence.Default.CompositeSerializers.Storable;
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[15562] | 30 | using HeuristicLab.Random;
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[16728] | 31 | using HEAL.Attic;
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[7407] | 32 |
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| 33 | namespace HeuristicLab.Problems.GeneralizedQuadraticAssignment {
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[15562] | 34 | [Item("Exhaustive 1-Move MoveGenerator", "Exhaustively generates all possible 1-moves.")]
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[16728] | 35 | [StorableType("A200C3BE-D761-4F82-9CA9-44A7BB2AB0DD")]
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[15562] | 36 | public class ExhaustiveOneMoveGenerator : GQAPNMoveGenerator, IStochasticOperator, IExhaustiveMoveGenerator {
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[15504] | 37 |
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[7407] | 38 | public ILookupParameter<IRandom> RandomParameter {
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| 39 | get { return (ILookupParameter<IRandom>)Parameters["Random"]; }
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| 40 | }
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| 41 |
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| 42 | [StorableConstructor]
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[16728] | 43 | protected ExhaustiveOneMoveGenerator(StorableConstructorFlag _) : base(_) { }
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[15562] | 44 | protected ExhaustiveOneMoveGenerator(ExhaustiveOneMoveGenerator original, Cloner cloner) : base(original, cloner) { }
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| 45 | public ExhaustiveOneMoveGenerator()
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[7407] | 46 | : base() {
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| 47 | Parameters.Add(new LookupParameter<IRandom>("Random", "The random number generator that should be used."));
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[15562] | 48 | NParameter.Value.Value = 1;
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| 49 | NParameter.Hidden = true;
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[7407] | 50 | }
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| 51 |
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| 52 | public override IDeepCloneable Clone(Cloner cloner) {
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[15562] | 53 | return new ExhaustiveOneMoveGenerator(this, cloner);
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[7407] | 54 | }
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| 55 |
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[15562] | 56 | public static IEnumerable<NMove> Generate(IntegerVector assignment, GQAPInstance problemInstance) {
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| 57 | var equipments = problemInstance.Demands.Length;
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| 58 | var locations = problemInstance.Capacities.Length;
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| 59 | var tmp = new int[equipments];
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| 60 | for (var e = 0; e < equipments; e++) {
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| 61 | var indices = new List<int> { e };
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| 62 | for (var l = 0; l < locations; l++) {
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| 63 | if (assignment[e] == l) continue;
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| 64 | var reassign = (int[])tmp.Clone();
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| 65 | reassign[e] = l + 1;
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| 66 | yield return new NMove(reassign, indices);
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| 67 | }
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| 68 | }
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[7407] | 69 | }
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| 70 |
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[15562] | 71 | public static IEnumerable<NMove> GenerateAllNxM(GQAPInstance problemInstance) {
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| 72 | var equipments = problemInstance.Demands.Length;
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| 73 | var locations = problemInstance.Capacities.Length;
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| 74 | var tmp = new int[equipments];
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| 75 | for (var e = 0; e < equipments; e++) {
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| 76 | var indices = new List<int> { e };
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| 77 | for (var l = 0; l < locations; l++) {
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| 78 | var reassign = (int[])tmp.Clone();
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| 79 | reassign[e] = l + 1;
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| 80 | yield return new NMove(reassign, indices);
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| 81 | }
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| 82 | }
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| 83 | }
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| 84 |
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[15504] | 85 | public override IEnumerable<NMove> GenerateMoves(IntegerVector assignment, int n, GQAPInstance problemInstance) {
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[15562] | 86 | if (n != 1) throw new ArgumentException("N must be equal to 1 for the exhaustive 1-move generator.");
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| 87 | var random = RandomParameter.ActualValue;
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| 88 | return Generate(assignment, problemInstance).Shuffle(random);
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[7407] | 89 | }
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| 90 | }
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| 91 | }
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