期刊
TRANSPORTATION RESEARCH PART E-LOGISTICS AND TRANSPORTATION REVIEW
卷 168, 期 -, 页码 -出版社
PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.tre.2022.102938
关键词
Automated container terminal; Inbound containers; Remarshaling; Integer linear programming; Eulerian graph
类别
资金
- National Natural Science Foundation of China [72101160, 72171153, 71771154]
- Stable Support Plan Program of Shenzhen Natural Science Fund, China [20200810160835003]
- Guangdong Basic and Applied Basic Research Foundation, China [2020A1515011272]
This study addresses the inbound container remarshaling problem in an automated container terminal and proposes two new integer linear programming models that outperform existing models. One of the models demonstrates high computational efficiency and can obtain optimal solutions in just a few hundred milliseconds.
In the container terminal yard, operators typically rearrange containers during the idle time of the yard cranes (so-called remarshaling operation) to improve the efficiency of future container retrieval. In this study, we address the inbound container remarshaling problem in an automated container terminal, which is aimed at determining the optimal container movement sequence during the remarshaling operation to minimize the expected time for retrieving all containers in the future. The randomness of the inbound containers' future retrieval order and the maximum available time of the remarshaling operation are both considered. Two new integer linear programming models are proposed to formulate the problem. Numerical experiments show the outperformance of the proposed models over the existing mixed-integer programming model in the literature. Especially, one of the proposed models demonstrates considerably high computational efficiency, which is capable of solving practical-sized instances to optimality in just a few hundred of milliseconds. In addition, we investigate the bi-objective remarshaling problem in order to examine the relationship between the minimum future retrieval time and the maximum available remarshaling time.
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