[15493] | 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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[15533] | 28 | public static class OptimalPolynomialAssignment {
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[15493] | 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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[15533] | 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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[15493] | 37 |
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| 38 | //Calculate weights in the graph
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[15533] | 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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[15493] | 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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[15533] | 89 | optimalAssignment = MakeAssignment(S, SM, prevPath, order);
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[15493] | 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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[15533] | 106 | private static int[] MakeAssignment(int start, int startMach, int[,] prevPath, Permutation order) {
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[15493] | 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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