Table 4 Results of the algorithm with fifteen months of real-world data
From: Heuristic approaches for the car sequencing problems with block batches
Problem | Manual method | R&F + F&O | ||||||||
|---|---|---|---|---|---|---|---|---|---|---|
n | o | m | \(p_o{:}q_o\) | Vio cost | Opn con | Vio cost | Opn con | Cost sv (%) | Opt gap (%) | CPU time (s) |
200 | 18 | 80 | 4:6 | 876 | 12.12 | 847 | 12.63 | 9.21 | 2.61 | 1.75 |
200 | 22 | 80 | 4:6 | 1132 | 10.83 | 1095 | 11.37 | 10.33 | 7.92 | 1.82 |
200 | 22 | 80 | 5:7 | 918 | 11.51 | 901 | 11.88 | 8.74 | 5.77 | 1.93 |
200 | 22 | 75 | 4:6 | 1315 | 9.60 | 1274 | 11.61 | 11.35 | 8.01 | 2.07 |
200 | 20 | 80 | 4:6 | 916 | 11.29 | 874 | 11.90 | 5.89 | 5.91 | 1.15 |
400 | 22 | 80 | 3:6 | 779 | 12.82 | 771 | 13.12 | 5.74 | 2.62 | 5.20 |
400 | 22 | 70 | 4:6 | 824 | 12.25 | 817 | 12.39 | 6.38 | 3.68 | 5.32 |
400 | 22 | 80 | 4:6 | 785 | 12.38 | 761 | 12.56 | 4.81 | 2.57 | 5.22 |
400 | 16 | 80 | 2:4 | 741 | 13.52 | 731 | 13.52 | 5.14 | 2.61 | 5.10 |
400 | 22 | 80 | 4:6 | 897 | 10.84 | 852 | 11.97 | 8.67 | 5.73 | 5.35 |
600 | 19 | 80 | 4:6 | 892 | 11.90 | 850 | 12.59 | 7.49 | 5.66 | 11.74 |
600 | 20 | 65 | 4:8 | 853 | 12.31 | 842 | 12.41 | 6.32 | 4.75 | 11.10 |
600 | 22 | 80 | 4:6 | 922 | 11.32 | 897 | 12.13 | 6.91 | 6.83 | 11.08 |
600 | 22 | 80 | 3:5 | 1235 | 11.76 | 1195 | 11.91 | 9.77 | 8.94 | 11.66 |
600 | 21 | 80 | 4:6 | 1201 | 11.73 | 1175 | 12.17 | 9.36 | 9.91 | 11.31 |
Avg | 952.40 | 11.75 | 925.47 | 12.27 | 7.74 | 5.57 | 6.12 | |||