Modelling of integrated vehicle scheduling and container storage problems in unloading process at an automated container terminal
Modelling of integrated vehicle scheduling and container storage problems in unloading process at an automated container terminal
Effectively scheduling vehicles and allocating storage locations for containers are two important problems in container terminal operations. Early research efforts, however, are devoted to study them separately. This paper investigates the integration of the two problems focusing on the unloading process in an automated container terminal, where all or part of the equipment are built in automation. We formulate the integrated problem as a mixed-integer programming (MIP) model to minimise ship’s berth time. We determine the detailed schedules for all vehicles to be used during the unloading process and the storage location to be assigned for all containers. A series of experiments are carried out for small-sized problems by using commercial software. A genetic algorithm (GA) is designed for solving large-sized problems. The solutions from the GA for the small-sized problems are compared with the optimal solutions obtained from the commercial software to verify the effectiveness of the GA. The computational results show that the model and solution methods proposed in this paper are efficient in solving the integrated unloading problem for the automated container terminal.
integer programming, automated container terminal, vehicle scheduling, container storage, container unloading
32-44
Luo, Jiabin
33f52989-5cd7-4101-928c-dc78e6e3c027
Wu, Yue
e279101b-b392-45c4-b894-187e2ded6a5c
Bergsten Mendes, Andre
fc284c11-eabe-4e53-80d7-81fdba43dfa3
Luo, Jiabin
33f52989-5cd7-4101-928c-dc78e6e3c027
Wu, Yue
e279101b-b392-45c4-b894-187e2ded6a5c
Bergsten Mendes, Andre
fc284c11-eabe-4e53-80d7-81fdba43dfa3
Luo, Jiabin, Wu, Yue and Bergsten Mendes, Andre
(2016)
Modelling of integrated vehicle scheduling and container storage problems in unloading process at an automated container terminal.
Computers & Industrial Engineering, 94, .
(doi:10.1016/j.cie.2016.01.010).
Abstract
Effectively scheduling vehicles and allocating storage locations for containers are two important problems in container terminal operations. Early research efforts, however, are devoted to study them separately. This paper investigates the integration of the two problems focusing on the unloading process in an automated container terminal, where all or part of the equipment are built in automation. We formulate the integrated problem as a mixed-integer programming (MIP) model to minimise ship’s berth time. We determine the detailed schedules for all vehicles to be used during the unloading process and the storage location to be assigned for all containers. A series of experiments are carried out for small-sized problems by using commercial software. A genetic algorithm (GA) is designed for solving large-sized problems. The solutions from the GA for the small-sized problems are compared with the optimal solutions obtained from the commercial software to verify the effectiveness of the GA. The computational results show that the model and solution methods proposed in this paper are efficient in solving the integrated unloading problem for the automated container terminal.
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Accepted/In Press date: 18 January 2016
e-pub ahead of print date: 23 January 2016
Keywords:
integer programming, automated container terminal, vehicle scheduling, container storage, container unloading
Organisations:
Centre of Excellence in Decision, Analytics & Risk Research
Identifiers
Local EPrints ID: 386247
URI: http://eprints.soton.ac.uk/id/eprint/386247
ISSN: 0360-8352
PURE UUID: 9c5a4d7d-f76e-428a-81fc-14edf4b99e9c
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Date deposited: 29 Jan 2016 11:24
Last modified: 15 Mar 2024 03:20
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Author:
Jiabin Luo
Author:
Andre Bergsten Mendes
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