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Joint Scheduling of Yard Crane, Yard Truck, and Quay Crane for Container Terminal Considering Vessel Stowage Plan: An Integrated Simulation-Based Optimization Approach

Author

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  • Hsien-Pin Hsu

    (Department of Supply Chain Management, National Kaohsiung University of Science and Technology, Kaohsiung 81157, Taiwan)

  • Chia-Nan Wang

    (Department of Industrial Engineering and Management, National Kaohsiung University of Science and Technology, Kaohsiung 80778, Taiwan)

  • Hsin-Pin Fu

    (Department of Marketing and Distribution Management, National Kaohsiung University of Science and Technology, Kaohsiung 824, Taiwan)

  • Thanh-Tuan Dang

    (Department of Industrial Engineering and Management, National Kaohsiung University of Science and Technology, Kaohsiung 80778, Taiwan
    Department of Logistics and Supply Chain Management, Hong Bang International University, Ho Chi Minh 723000, Vietnam)

Abstract

The joint scheduling of quay cranes (QCs), yard cranes (YCs), and yard trucks (YTs) is critical to achieving good overall performance for a container terminal. However, there are only a few such integrated studies. Especially, those who have taken the vessel stowage plan (VSP) into consideration are very rare. The VSP is a plan assigning each container a stowage position in a vessel. It affects the QC operations directly and considerably. Neglecting this plan will cause problems when loading/unloading containers into/from a ship or even congest the YT and YC operations in the upstream. In this research, a framework of simulation-based optimization methods have been proposed firstly. Then, four kinds of heuristics/metaheuristics has been employed in this framework, such as sort-by-bay (SBB), genetic algorithm (GA), particle swarm optimization (PSO), and multiple groups particle swarm optimization (MGPSO), to deal with the yard crane scheduling problem (YCSP), yard truck scheduling problem (YTSP), and quay crane scheduling problem (QCSP) simultaneously for export containers, taking operational constraints into consideration. The objective aims to minimize makespan. Each of the simulation-based optimization methods includes three components, load-balancing heuristic, sequencing method, and simulation model. Experiments have been conducted to investigate the effectiveness of different simulation-based optimization methods. The results show that the MGPSO outperforms the others.

Suggested Citation

  • Hsien-Pin Hsu & Chia-Nan Wang & Hsin-Pin Fu & Thanh-Tuan Dang, 2021. "Joint Scheduling of Yard Crane, Yard Truck, and Quay Crane for Container Terminal Considering Vessel Stowage Plan: An Integrated Simulation-Based Optimization Approach," Mathematics, MDPI, vol. 9(18), pages 1-28, September.
    • Handle: RePEc:gam:jmathe:v:9:y:2021:i:18:p:2236-:d:633732
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    References listed on IDEAS

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    Cited by:

    1. Buddhi A. Weerasinghe & H. Niles Perera & Xiwen Bai, 2024. "Optimizing container terminal operations: a systematic review of operations research applications," Maritime Economics & Logistics, Palgrave Macmillan;International Association of Maritime Economists (IAME), vol. 26(2), pages 307-341, June.
    2. van Twiller, Jaike & Sivertsen, Agnieszka & Pacino, Dario & Jensen, Rune Møller, 2024. "Literature survey on the container stowage planning problem," European Journal of Operational Research, Elsevier, vol. 317(3), pages 841-857.

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