Research Article
Hybrid Deep Neural Network Scheduler for Job-Shop Problem Based on Convolution Two-Dimensional Transformation
Table 9
Comparison of HDNNS with other methods on traditional datasets.
| | Optimal | HDNNS (our) | DQN | DEEPRM | ANN (1D) | ANN (all) | STPT | SPT |
| ft10 (10 10) | MAKESPAN | 930 | 1023 | 1023 | 1025 | 1154 | 1054 | 1152 | 1169 | Scheduling score | — | 90.91 | 90.9 | 90.7 | 80.5 | 88.2 | 80.7 | 79.5 | Training time | — | 1804.5 | 13321.7 | 12212.2 | 426.1 | 3245.6 | — | — | Scheduling time | — | 3.6 | 3.9 | 3.8 | 1.2 | 4.7 | 1.0 | 1.0 |
| ft20 (20 10) | MAKESPAN | 1165 | 1391 | 1342 | 1317 | 1524 | 1504 | 1434 | 1544 | Scheduling score | — | 83.7 | 86.8 | 88.4 | 76.4 | 77.4 | 81.2 | 75.4 | Training time | — | 3954.1 | 16532.1 | 17548.3 | 436.5 | 4689.5 | — | — | Scheduling time | — | 7.6 | 7.4 | 7.2 | 2.4 | 9.2 | 1.9 | 1.9 |
| la24 (20 10) | MAKESPAN | 935 | 1056 | 1088 | 1071 | 1564 | 1564 | 1580 | 1569 | Scheduling score | — | 88.5 | 85.9 | 87.30 | 59.7 | 59.7 | 59.1 | 59.5 | Training time | — | 3976.5 | 16844.3 | 16254.5 | 487.6 | 4684.4 | — | — | Scheduling time | — | 7.6 | 8.2 | 7.3 | 2.5 | 2.5 | 1.9 | 1.9 |
| la36 (15 15) | MAKESPAN | 1268 | 1318 | 1465 | 1465 | 1721 | 1721 | 1729 | 1729 | Scheduling score | — | 96.2 | 86.55 | 86.5 | 73.6 | 73.6 | 73.3 | 73.3 | Training time | — | 15318.1 | 63172.0 | 62251.4 | 578.5 | 21688.1 | — | — | Scheduling time | — | 38.4 | 39.3 | 39.2 | 3.3 | 42.5 | 8.3 | 7.2 |
| abz7 (20 15) | MAKESPAN | 665 | 726 | 739 | 720 | 940 | 940 | 980 | 1026 | Scheduling score | — | 91.6 | 89.9 | 92.3 | 70.7 | 70.7 | 67.8 | 64.8 | Training time | — | 22124.2 | 90584.4 | 92584.4 | 683.4 | 29258.3 | — | — | Scheduling time | — | 51.3 | 48.3 | 50.24 | 4.8 | 89.5 | 13.3 | 12.3 |
| yn1 (20 20) | MAKESPAN | 886 | 995 | 1183 | 1067 | 1183 | 1183 | 1208 | 1207 | Scheduling score | — | 89.0 | 74.8 | 83.04 | 74.8 | 74.8 | 73.3 | 73.4 | Training time | — | 30688.8 | 126689.2 | 125845.4 | 536.0 | 35648.2 | — | — | Scheduling time | — | 177.2 | 188.0 | 184.5 | 65.4 | 194.5 | 78.4 | 73.5 |
| Average | MAKESPAN | 974.83 | 1084.83 | 1140.0 | 1110.8 | 1347.6 | 1327.6 | 1347.1 | 1374.0 | Scheduling score | — | 90.01 | 85.5 | 88.0 | 72.6 | 74.1 | 72.6 | 71.0 | Training time | — | 12977.7 | 54523.9 | 54449.4 | 524.7 | 16535.7 | — | — | Scheduling time | — | 47.6 | 49.1 | 48.7 | 13.3 | 57.1 | 17.5 | 16.3 |
| MAKESPAN rank | 1 | 3 | 2 | 5 | 4 | 6 | 7 | Training time | 2 | 4 | 3 | 1 | 5 | — | — | Scheduling time RANK | 4 | 6 | 5 | 1 | 7 | 3 | 2 |
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