Abstract
Although research on traditional terminals has been well developed, research concerning automated terminals and especially the yard space management is at the early stage. Backgrounded by the application of the upgrading automated technology, yard allocation requires compatible methods to interpret the emerging features of automated container terminals and coordinate with other operational systems. Considering the mixed stacking of import and export containers in one block and the cooperation among multiple yard cranes, this study provides the dynamic yard allocation method for automated container terminals. In this paper the space allocation problem of automated yard is examined through two stages. In Stage-I a bi-objective model is established to balance the workload between seaside and landside in each time window and optimize the total moving distances of containers from the yard to the berth. In Stage-II, by minimizing the moving distances of yard cranes from seaside, the specific allocation of the bay position in each time window is determined. Furthermore, by the application of the real-life cases of the automated terminal operations, it is verified that the proposed method and mathematical models are efficient to allocate the yard space which improve the yard management for the automated container terminal.
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Acknowledgements
This work is sponsored by the National Natural Science Foundation of China [grant number 72072112, 72001135, 72002125]; Shanghai Rising-Star Program [grant number 19QA1404200]; Shanghai Sailing Program [grant number 20YF1416600, 19YF1418800].
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Appendix
Appendix
A1 Container volume to be allocated in each time window (TEUs)
t | |||||||||
|---|---|---|---|---|---|---|---|---|---|
Category | 9 | 10 | 11 | 12 | 13 | 14 | 15 | 16 | 17 |
Import container | 2000 | 2000 | 2000 | 4000 | 2000 | 2000 | 4000 | 4000 | 2000 |
Export container | 2200 | 3200 | 3000 | 2600 | 3200 | 2800 | 1800 | 1000 | 1000 |
A2 Container volume to be allocated in each time window (Bays)
t | |||||||||
|---|---|---|---|---|---|---|---|---|---|
Category | 9 | 10 | 11 | 12 | 13 | 14 | 15 | 16 | 17 |
Import container | 40 | 40 | 40 | 80 | 40 | 40 | 80 | 80 | 40 |
Export container | 44 | 64 | 60 | 52 | 64 | 56 | 36 | 20 | 20 |
A3 Distance from vessel berth to each block (m)
s | ||||||||
|---|---|---|---|---|---|---|---|---|
i | 1 | 2 | 3 | 4 | 5 | 6 | 7 | 8 |
Block1 | 115 | 315 | 195 | 435 | 115 | 195 | 435 | 315 |
Block2 | 155 | 275 | 155 | 395 | 155 | 155 | 395 | 275 |
Block3 | 115 | 235 | 115 | 355 | 115 | 115 | 355 | 235 |
Block4 | 115 | 195 | 115 | 315 | 115 | 115 | 315 | 195 |
Block5 | 155 | 155 | 155 | 275 | 155 | 155 | 275 | 155 |
Block6 | 195 | 115 | 115 | 235 | 195 | 115 | 235 | 115 |
Block7 | 235 | 115 | 115 | 195 | 235 | 115 | 195 | 115 |
Block8 | 275 | 155 | 155 | 155 | 275 | 155 | 155 | 155 |
Block9 | 315 | 115 | 195 | 115 | 315 | 195 | 115 | 115 |
Block10 | 355 | 115 | 235 | 115 | 355 | 235 | 115 | 115 |
A4 Dynamic distribution of container capacity in each container block (Bays)
t | |||||||||
|---|---|---|---|---|---|---|---|---|---|
i | 9 | 10 | 11 | 12 | 13 | 14 | 15 | 16 | 17 |
Block1 | 22 | 29 | 41 | 37 | 49 | 51 | 44 | 48 | 31 |
Block2 | 26 | 30 | 38 | 52 | 41 | 35 | 38 | 44 | 34 |
Block3 | 24 | 33 | 35 | 33 | 42 | 41 | 40 | 34 | 30 |
Block4 | 22 | 29 | 29 | 46 | 49 | 52 | 44 | 32 | 32 |
Block5 | 22 | 30 | 31 | 45 | 50 | 43 | 31 | 33 | 31 |
Block6 | 25 | 31 | 35 | 39 | 43 | 41 | 43 | 25 | 9 |
Block7 | 26 | 30 | 30 | 28 | 29 | 26 | 30 | 22 | 6 |
Block8 | 23 | 28 | 28 | 29 | 28 | 46 | 32 | 34 | 25 |
Block9 | 22 | 28 | 34 | 26 | 33 | 28 | 38 | 44 | 60 |
Block10 | 22 | 30 | 35 | 25 | 22 | 29 | 40 | 44 | 60 |
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He, J., Xiao, X., Yu, H. et al. Dynamic yard allocation for automated container terminal. Ann Oper Res (2022). https://doi.org/10.1007/s10479-021-04458-6
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DOI: https://doi.org/10.1007/s10479-021-04458-6