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 System.Linq;
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23 | using HeuristicLab.Core;
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24 | using HeuristicLab.Data;
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25 | using HeuristicLab.Encodings.PermutationEncoding;
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26 |
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27 | namespace HeuristicLab.Problems.Scheduling.CFSAP {
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28 | public static class OptimalPolynomialAssignment {
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29 |
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30 | public static int[] MakeAssignment(Permutation order, IntMatrix processingTimes, ItemList<IntMatrix> setupTimes, out int T) {
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31 | var N = order.Length;
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32 |
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33 | int[,,] weights = new int[2, 2 * N, 2 * N];
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34 | int[,] graph = new int[2, N];
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35 | int[,] prevPath = new int[2, N + 1]; //Only for optimal assignment evaluation
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36 | int[] optimalAssignment = new int[N]; //Only for optimal assignment evaluation
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37 |
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38 | //Calculate weights in the graph
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39 | for (int S = 0; S < N; S++) { //Starting point of the arc
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40 | for (int sM = 0; sM < 2; sM++) { //Starting point machine
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41 | int eM = sM == 0 ? 1 : 0;
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42 | weights[sM, S, S + 1] = 0;
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43 |
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44 | for (int E = S + 2; E < S + N; E++)
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45 | weights[sM, S, E] =
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46 | weights[sM, S, E - 1] +
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47 | processingTimes[eM, order[(E - 1) % N]] +
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48 | setupTimes[eM][order[(E - 1) % N], order[E % N]];
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49 |
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50 | for (int E = S + 1; E < S + N; E++)
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51 | weights[sM, S, E] += (
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52 | processingTimes[sM, order[S % N]] +
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53 | setupTimes[sM][order[S % N], order[(E + 1) % N]]
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54 | );
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55 | }
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56 | }
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57 |
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58 | //Determine the shortest path in the graph
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59 | T = int.MaxValue / 2;
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60 | for (int S = 0; S < N - 1; S++) //Start node in graph O(N)
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61 | for (int SM = 0; SM < 2; SM++) { //Start node machine in graph O(1)
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62 | graph[SM, S] = 0;
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63 | graph[SM == 0 ? 1 : 0, S] = int.MaxValue / 2;
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64 | prevPath[SM, 0] = -1;
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65 | for (int E = S + 1; E < N; E++) //Currently calculated node O(N)
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66 | for (int EM = 0; EM < 2; EM++) { //Currently calculated node machine O(1)
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67 | graph[EM, E] = int.MaxValue / 2;
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68 | for (int EC = S; EC < E; EC++) { //Nodes connected to node E O(N)
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69 | int newWeight = graph[EM == 0 ? 1 : 0, EC] + weights[EM == 0 ? 1 : 0, EC, E];
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70 | if (newWeight < graph[EM, E]) {
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71 | graph[EM, E] = newWeight;
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72 | prevPath[EM, E] = EC;
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73 | }
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74 | }
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75 | }
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76 |
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77 | int EP = S + N; //End point.
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78 | int newT = int.MaxValue / 2;
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79 | for (int EC = S + 1; EC < N; EC++) { //Nodes connected to EP O(N)
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80 | int newWeight = graph[SM == 0 ? 1 : 0, EC] + weights[SM == 0 ? 1 : 0, EC, EP];
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81 | if (newWeight < newT) {
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82 | newT = newWeight;
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83 | prevPath[SM, S] = EC;
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84 | }
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85 | }
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86 |
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87 | if (newT < T) {
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88 | T = newT;
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89 | optimalAssignment = MakeAssignment(S, SM, prevPath, order);
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90 | }
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91 | }
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92 |
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93 | //Omitted solutions
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94 | for (int machine = 0; machine < 2; machine++) {
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95 | int[] assignment = Enumerable.Repeat(machine, N).ToArray();
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96 | int newT = CFSAP.EvaluateAssignement(order, assignment, processingTimes, setupTimes);
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97 | if (newT < T) { //New best solution has been found
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98 | T = newT;
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99 | optimalAssignment = assignment;
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100 | }
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101 | }
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102 |
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103 | return optimalAssignment;
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104 | }
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105 |
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106 | private static int[] MakeAssignment(int start, int startMach, int[,] prevPath, Permutation order) {
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107 | var N = order.Length;
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108 | int[] assignment = Enumerable.Repeat(-1, N).ToArray();
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109 | var inverseOrder = new int[N];
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110 |
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111 | for (int i = 0; i < N; i++)
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112 | inverseOrder[order[i]] = i;
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113 |
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114 | int end = start + N;
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115 |
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116 | int currMach = startMach;
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117 | int currNode = start;
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118 | while (true) {
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119 | assignment[inverseOrder[currNode]] = currMach;
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120 | currNode = prevPath[currMach, currNode];
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121 | currMach = currMach == 0 ? 1 : 0;
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122 | if (currNode == start)
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123 | break;
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124 | }
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125 |
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126 | currMach = startMach;
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127 | for (int i = 0; i < N; i++) {
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128 | if (assignment[inverseOrder[i]] != -1)
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129 | currMach = currMach == 0 ? 1 : 0;
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130 | else
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131 | assignment[inverseOrder[i]] = currMach;
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132 | }
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133 |
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134 | return assignment;
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135 | }
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136 | }
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137 | }
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