A new vocation queuing model to optimize truck appointments and yard handling-equipment use in dual transactions systems of container terminals

Na Li, Hercules Haralambides (), Haotian Sheng and Zhihong Jin
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Na Li: Dalian Maritime University
Hercules Haralambides: Dalian Maritime University, CES - Centre d'économie de la Sorbonne - UP1 - Université Paris 1 Panthéon-Sorbonne - CNRS - Centre National de la Recherche Scientifique
Haotian Sheng: Dalian Maritime University
Zhihong Jin: Dalian Maritime University

Université Paris1 Panthéon-Sorbonne (Post-Print and Working Papers) from HAL

Abstract: In a dual transaction at a marine terminal, an external truck drops off one container and picks up another on a single trip. To ensure a successful dual transaction operation and smooth external truck arrivals, a bi-objective mixed integer programming model is developed that optimizes the allocation of appointment quotas simultaneously with the deployment of (yard) cargo handling equipment. Our model addresses the challenges posed by the different types of truck movement in the terminal, i.e., delivery, pickup, and dual transaction. These require different handling equipment, various deadlines, and multiple priorities. To estimate the queuing length of external trucks in single or dual transactions (as well as that of internal trucks), a novel three-level vocation queuing model is set up. For the bi-objectives optimization, we propose a revised non-dominated genetic algorithm to obtain the approximate optimal solution. Experimental results prove the efficiency and effectiveness of the method. It shows that the newly built vocation queuing model can estimate the prioritized queuing process more effectively in three respects: a) the 3-level queuing; b) discrete truck arrivals in the queuing system; c) non-interruption of servers. Our quota optimization design improves the model's applicability to real cases, especially in the case of dual transactions. It is demonstrated that the method proposed in the paper could help terminal operators allocate quotas and simultaneously match the capacity of yard handling, thus improving truck services and terminal profitability.

Date: 2022-07
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Published in Computers & Industrial Engineering, 2022, 169, pp.108216. ⟨10.1016/j.cie.2022.108216⟩

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Persistent link: https://EconPapers.repec.org/RePEc:hal:cesptp:hal-04046268

DOI: 10.1016/j.cie.2022.108216

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