Positioning a Handshake Bay for Twin Stacking Cranes in an Automated Container Terminal Yard Block
At automated container terminals (ACTs), twin automated stacking cranes (ASCs) can carry out the tasks—store and retrieve containers simultaneously in a yard block using a handshake bay, where a primary ASC stacks the container at the handshake bay and the other crane carries it to the destination b...
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| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Wiley
2022-01-01
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| Series: | Journal of Advanced Transportation |
| Online Access: | http://dx.doi.org/10.1155/2022/5738254 |
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| _version_ | 1832561566136926208 |
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| author | Zhi-Hua Hu Xi-Dan Tian Yu-Qi Yin Chen Wei |
| author_facet | Zhi-Hua Hu Xi-Dan Tian Yu-Qi Yin Chen Wei |
| author_sort | Zhi-Hua Hu |
| collection | DOAJ |
| description | At automated container terminals (ACTs), twin automated stacking cranes (ASCs) can carry out the tasks—store and retrieve containers simultaneously in a yard block using a handshake bay, where a primary ASC stacks the container at the handshake bay and the other crane carries it to the destination bay. Although the handshake bay increases the degree of crane utilization, the ASCs will interfere with each other at the bay, decreasing the stacking efficiency. This study formulates a mixed-integer linear program (MILP) to position the handshake bay and simultaneously schedule the twin ASCs to minimize the tasks’ makespan. The proposed formulation considers the safe time interval to avoid crane collisions during adjacent crane movements. To solve the model, we developed a random-key genetic algorithm with a priority-based decoding scheme to optimize the task sequences and tasks assigned to the cranes. The priority-based GA can always generate feasible solutions by ranking the container-handling tasks. Numerical experiments prove that the safe temporal interval affects the makespan and the handshake bay’s position. An optimal handshake bay reduces 35% of the makespan compared with a nonoptimal bay, and the proposed algorithm is competitive compared with the on-the-shelf MILP solver and can solve medium- and large-scale instances in short computing time with gaps lower than 5% compared with ideal solutions. |
| format | Article |
| id | doaj-art-5fc3a2e53c934f55b3db771cda3c8b77 |
| institution | Kabale University |
| issn | 2042-3195 |
| language | English |
| publishDate | 2022-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Journal of Advanced Transportation |
| spelling | doaj-art-5fc3a2e53c934f55b3db771cda3c8b772025-02-03T01:24:44ZengWileyJournal of Advanced Transportation2042-31952022-01-01202210.1155/2022/5738254Positioning a Handshake Bay for Twin Stacking Cranes in an Automated Container Terminal Yard BlockZhi-Hua Hu0Xi-Dan Tian1Yu-Qi Yin2Chen Wei3Qingdao InstituteQingdao InstituteLogistics Research CenterLogistics Research CenterAt automated container terminals (ACTs), twin automated stacking cranes (ASCs) can carry out the tasks—store and retrieve containers simultaneously in a yard block using a handshake bay, where a primary ASC stacks the container at the handshake bay and the other crane carries it to the destination bay. Although the handshake bay increases the degree of crane utilization, the ASCs will interfere with each other at the bay, decreasing the stacking efficiency. This study formulates a mixed-integer linear program (MILP) to position the handshake bay and simultaneously schedule the twin ASCs to minimize the tasks’ makespan. The proposed formulation considers the safe time interval to avoid crane collisions during adjacent crane movements. To solve the model, we developed a random-key genetic algorithm with a priority-based decoding scheme to optimize the task sequences and tasks assigned to the cranes. The priority-based GA can always generate feasible solutions by ranking the container-handling tasks. Numerical experiments prove that the safe temporal interval affects the makespan and the handshake bay’s position. An optimal handshake bay reduces 35% of the makespan compared with a nonoptimal bay, and the proposed algorithm is competitive compared with the on-the-shelf MILP solver and can solve medium- and large-scale instances in short computing time with gaps lower than 5% compared with ideal solutions.http://dx.doi.org/10.1155/2022/5738254 |
| spellingShingle | Zhi-Hua Hu Xi-Dan Tian Yu-Qi Yin Chen Wei Positioning a Handshake Bay for Twin Stacking Cranes in an Automated Container Terminal Yard Block Journal of Advanced Transportation |
| title | Positioning a Handshake Bay for Twin Stacking Cranes in an Automated Container Terminal Yard Block |
| title_full | Positioning a Handshake Bay for Twin Stacking Cranes in an Automated Container Terminal Yard Block |
| title_fullStr | Positioning a Handshake Bay for Twin Stacking Cranes in an Automated Container Terminal Yard Block |
| title_full_unstemmed | Positioning a Handshake Bay for Twin Stacking Cranes in an Automated Container Terminal Yard Block |
| title_short | Positioning a Handshake Bay for Twin Stacking Cranes in an Automated Container Terminal Yard Block |
| title_sort | positioning a handshake bay for twin stacking cranes in an automated container terminal yard block |
| url | http://dx.doi.org/10.1155/2022/5738254 |
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