A dynamic truck dispatching problem in marine container terminal

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Chen, Jianjun, Bai, Ruibin, Dong, Haibo, Qu, Rong and Kendall, Graham (2016) A dynamic truck dispatching problem in marine container terminal. In: 2016 IEEE Symposium on Computational Intelligence in Scheduling and Network Design (IEEE SSCI 2016), 6-9 December 2016, Athens, Greece.

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Abstract

In this paper, a dynamic truck dispatching problem of a marine container terminal is described and discussed. In this problem, a few containers, encoded as work instructions, need to be transferred between yard blocks and vessels by a fleet of trucks. Both the yard blocks and the quay are equipped with cranes to support loading/unloading operations. In order to service more vessels, any unnecessary idle time between quay crane (QC) operations need to be minimised to speed up the container transfer process. Due to the unpredictable port situations that can affect routing plans and the short calculation time allowed to generate one, static solution methods are not suitable for this problem. In this paper, we introduce a new mathematical model that minimises both the QC makespan and the truck travelling time. Three dynamic heuristics are proposed and a genetic algorithm hyperheuristic (GAHH) under development is also described. Experiment results show promising capabilities the GAHH may offer.

Item Type: Conference or Workshop Item (Paper)
RIS ID: https://nottingham-repository.worktribe.com/output/835852
Additional Information: © 2016 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.
Schools/Departments: University of Nottingham Ningbo China > Faculty of Science and Engineering > School of Computer Science
University of Nottingham, UK > Faculty of Science > School of Computer Science
Depositing User: Qu, Rong
Date Deposited: 07 Dec 2016 13:05
Last Modified: 04 May 2020 18:26
URI: https://eprints.nottingham.ac.uk/id/eprint/39207

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