Abstract
Process-network synthesis is the determination of the optimal network structure of a process system together with optimal configurations and capacities of the operating units incorporated into the system. The aim of developing more and more sophisticated solver algorithms is to find the optimum as fast as possible and increase the circle of practically solvable process synthesis problems. The P-graph framework can effectively reduce the number of structures to be examined and accelerate the computation searching for the optimum due to the exploitation of combinatorial characteristics of candidate solution structures. A cooperative parallel implementation of P-graph algorithms have been published recently to exploit the capabilities of multi-core and multiprocessor systems (Bartos and Bertok in De Gruyter Ser Logic Appl 1:303–313, 2015). The parallel implementation has increased performance significantly but this can be further improved by fine tuning the parameters of the parallel algorithm. Outcomes of experiments on parameter optimization are to be presented herein.














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Notes
p-graph.org, “P-Graph Studio”, Available: http://p-graph.org.
p-graph.org, “test base.zip”, Available: http://p-graph.org/wp-content/uploads/2017/12/test_base.zip.
projects.coin-or.org, “COIN-OR Branch-and-Cut MIP-Solver”, http://projects.coin-or.org/Cbc.
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Acknowledgements
This publication has been supported by the ÚNKP-17-3 (IV-PE-1) New National Excellence Program of the Ministry of Human Capacities. The authors acknowledge the financial support of Széchenyi 2020 under the EFOP-3.6.1-16-2016-00015.
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Appendix
Appendix
Test base available at “p-graph.org”.
Test base properties:
Name | # of op.units | # of materials | Difficulty | Name | # of op.units | # of materials | Difficulty | Name | # of op.units | # of materials | Difficulty |
---|---|---|---|---|---|---|---|---|---|---|---|
0 | 9 | 14 | 6 | 50 | 18 | 27 | 7 | 100 | 50 | 81 | 7 |
1 | 10 | 20 | 4 | 51 | 18 | 31 | 0 | 101 | 50 | 95 | 14 |
2 | 10 | 25 | 6 | 52 | 18 | 30 | 12 | 102 | 50 | 85 | 8 |
3 | 10 | 18 | 4 | 53 | 24 | 48 | 9 | 103 | 50 | 80 | 9 |
4 | 10 | 15 | 5 | 54 | 24 | 37 | 1 | 104 | 50 | 82 | 0 |
5 | 10 | 14 | 6 | 55 | 29 | 46 | 0 | 105 | 50 | 86 | 12 |
6 | 11 | 14 | 4 | 56 | 29 | 52 | 0 | 106 | 50 | 101 | 0 |
7 | 11 | 21 | 3 | 57 | 30 | 57 | 9 | 107 | 50 | 85 | 0 |
8 | 11 | 17 | 1 | 58 | 30 | 55 | 5 | 108 | 50 | 80 | 8 |
9 | 11 | 18 | 7 | 59 | 30 | 49 | 9 | 109 | 50 | 90 | 0 |
10 | 12 | 23 | 7 | 60 | 30 | 50 | 10 | 110 | 50 | 86 | 0 |
11 | 12 | 20 | 0 | 61 | 30 | 53 | 11 | 111 | 50 | 68 | 5 |
12 | 13 | 16 | 5 | 62 | 30 | 53 | 4 | 112 | 54 | 74 | 25 |
13 | 13 | 22 | 0 | 63 | 30 | 48 | 16 | 113 | 55 | 97 | 3 |
14 | 13 | 26 | 2 | 64 | 30 | 48 | 3 | 114 | 68 | 102 | 5 |
15 | 13 | 20 | 6 | 65 | 30 | 49 | 8 | 115 | 70 | 101 | 30 |
16 | 14 | 22 | 7 | 66 | 30 | 54 | 19 | 116 | 70 | 109 | 24 |
17 | 14 | 25 | 0 | 67 | 30 | 53 | 12 | 117 | 70 | 117 | 0 |
18 | 14 | 28 | 7 | 68 | 30 | 53 | 10 | 118 | 70 | 120 | 13 |
19 | 14 | 14 | 6 | 69 | 30 | 58 | 13 | 119 | 70 | 111 | 2 |
20 | 15 | 27 | 3 | 70 | 30 | 50 | 0 | 120 | 70 | 108 | 15 |
21 | 15 | 28 | 10 | 71 | 30 | 51 | 0 | 121 | 70 | 115 | 11 |
22 | 15 | 26 | 10 | 72 | 30 | 40 | 0 | 122 | 70 | 115 | 14 |
23 | 15 | 24 | 7 | 73 | 30 | 44 | 13 | 123 | 70 | 123 | 0 |
24 | 15 | 31 | 3 | 74 | 30 | 41 | 0 | 124 | 70 | 104 | 19 |
25 | 15 | 23 | 8 | 75 | 30 | 48 | 0 | 125 | 70 | 113 | 18 |
26 | 15 | 24 | 6 | 76 | 30 | 50 | 0 | 126 | 70 | 112 | 30 |
27 | 15 | 27 | 8 | 77 | 35 | 56 | 3 | 127 | 70 | 108 | 20 |
28 | 15 | 31 | 5 | 78 | 35 | 57 | 3 | 128 | 70 | 117 | 18 |
29 | 15 | 31 | 4 | 79 | 38 | 65 | 17 | 129 | 70 | 107 | 19 |
30 | 15 | 22 | 2 | 80 | 38 | 55 | 15 | 130 | 70 | 113 | 6 |
31 | 15 | 26 | 6 | 81 | 40 | 55 | 14 | 131 | 70 | 115 | 4 |
32 | 15 | 22 | 5 | 82 | 43 | 74 | 7 | 132 | 70 | 109 | 4 |
33 | 15 | 33 | 5 | 83 | 46 | 67 | 9 | 133 | 70 | 115 | 14 |
34 | 15 | 29 | 5 | 84 | 46 | 68 | 0 | 134 | 70 | 101 | 26 |
35 | 15 | 29 | 7 | 85 | 47 | 77 | 20 | 135 | 70 | 102 | 7 |
36 | 15 | 24 | 7 | 86 | 50 | 78 | 0 | 136 | 90 | 140 | 5 |
37 | 15 | 30 | 3 | 87 | 50 | 84 | 8 | 137 | 90 | 158 | 13 |
38 | 15 | 27 | 0 | 88 | 50 | 93 | 15 | 138 | 90 | 143 | 3 |
39 | 15 | 26 | 0 | 89 | 50 | 81 | 2 | 139 | 90 | 160 | 26 |
40 | 15 | 25 | 0 | 90 | 50 | 84 | 15 | 140 | 90 | 133 | 4 |
41 | 15 | 29 | 0 | 91 | 50 | 80 | 7 | 141 | 90 | 148 | 3 |
42 | 15 | 22 | 0 | 92 | 50 | 79 | 9 | 142 | 90 | 140 | 1 |
43 | 15 | 23 | 0 | 93 | 50 | 90 | 8 | 143 | 90 | 155 | 41 |
44 | 15 | 26 | 0 | 94 | 50 | 81 | 10 | 144 | 90 | 142 | 23 |
45 | 15 | 25 | 0 | 95 | 50 | 87 | 21 | 145 | 90 | 149 | 28 |
46 | 15 | 23 | 0 | 96 | 50 | 78 | 5 | 146 | 90 | 136 | 4 |
47 | 15 | 33 | 6 | 97 | 50 | 83 | 19 | 147 | 90 | 143 | 2 |
48 | 15 | 21 | 8 | 98 | 50 | 87 | 13 | 148 | 90 | 149 | 3 |
49 | 17 | 28 | 1 | 99 | 50 | 73 | 12 | 149 | 90 | 143 | 8 |
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Bartos, A., Bertok, B. Parameter tuning for a cooperative parallel implementation of process-network synthesis algorithms. Cent Eur J Oper Res 27, 551–572 (2019). https://doi.org/10.1007/s10100-018-0576-1
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DOI: https://doi.org/10.1007/s10100-018-0576-1