1 | #region License Information
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2 | /* HeuristicLab
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3 | * Copyright (C) 2002-2017 Heuristic and Evolutionary Algorithms Laboratory (HEAL)
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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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22 | using HeuristicLab.Common;
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23 | using HeuristicLab.Core;
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24 | using HeuristicLab.Persistence.Default.CompositeSerializers.Storable;
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25 | using ILOG.CPLEX;
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26 | using ILOG.OPL;
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27 |
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28 | namespace HeuristicLab.Problems.GeneralizedQuadraticAssignment.Algorithms.CPLEX {
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29 | [Item("KB-Linearization CPLEX (GQAP)", "")]
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30 | [StorableClass]
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31 | [Creatable(CreatableAttribute.Categories.Algorithms)]
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32 | public sealed class GQAP_KB : CplexSolver {
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33 |
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34 | [StorableConstructor]
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35 | private GQAP_KB(bool deserializing) : base(deserializing) { }
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36 | private GQAP_KB(GQAP_KB original, Cloner cloner)
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37 | : base(original, cloner) {
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38 | }
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39 | public GQAP_KB() {
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40 |
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41 | }
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42 |
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43 | public override IDeepCloneable Clone(Cloner cloner) {
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44 | return new GQAP_KB(this, cloner);
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45 | }
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46 |
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47 | protected override OplModel GetModel(OplFactory factory, OplSettings settings, Cplex cplex) {
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48 | using (var modelSource = factory.CreateOplModelSourceFromString(model, "gqap_kb"))
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49 | using (var def = factory.CreateOplModelDefinition(modelSource, settings))
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50 | return factory.CreateOplModel(def, cplex);
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51 | }
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52 |
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53 | private const string model = @"/*********************************************
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54 | * OPL 12.7.0.0 Model
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55 | * Author: Andreas Beham
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56 | * Creation Date: 31.10.2017 at 14:30:01
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57 | *********************************************/
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58 |
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59 | int EQUIPMENTS = ...;
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60 | int LOCATIONS = ...;
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61 | float TC = ...;
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62 |
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63 | range N = 1..EQUIPMENTS;
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64 | range M = 1..LOCATIONS;
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65 |
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66 | float weights[N][N] = ...;
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67 | float distances[M][M] = ...;
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68 | float install[N][M] = ...;
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69 | float demands[N] = ...;
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70 | float capacities[M] = ...;
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71 |
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72 | float v[i in N][k in M] = sum(j in N, h in M) (weights[i][j] * distances[k][h]);
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73 |
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74 | dvar int+ x[N][M] in 0..1;
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75 | dvar float+ y[N][M];
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76 |
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77 | dexpr float installCosts = sum(i in N, k in M) x[i][k] * install[i][k];
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78 | dexpr float flowCosts = TC * sum(i in N, k in M) y[i][k];
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79 |
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80 | minimize installCosts + flowCosts;
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81 |
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82 | subject to {
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83 |
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84 | forall (i in N)
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85 | AllAssigned:
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86 | sum(k in M) x[i][k] == 1;
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87 |
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88 | forall (k in M)
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89 | Capacity:
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90 | sum(i in N) x[i][k] * demands[i] <= capacities[k];
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91 |
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92 | forall (i in N, k in M)
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93 | v[i][k] * ( x[i][k] - 1 ) + sum(j in N, h in M) (x[j][h] * weights[i][j] * distances[k][h]) <= y[i][k];
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94 |
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95 | }
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96 |
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97 | ";
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98 | }
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99 | }
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