Resources Planning for Container Terminal in a Maritime Supply Chain Using Multiple Particle Swarms Optimization (MPSO)

Hsien-Pin Hsu and Chia-Nan Wang
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Hsien-Pin Hsu: Department of Supply Chain Management, National Kaohsiung University of Science and Technology, Kaohsiung 80778, Taiwan
Chia-Nan Wang: Department of Industrial Engineering and Management, National Kaohsiung University of Science and Technology, Kaohsiung 81157, Taiwan

Mathematics, 2020, vol. 8, issue 5, 1-31

Abstract: Resources planning is an important task in a supply chain in order to achieve a good result. The better the utilization of resources, especially scarce resources, the better the performance of a supply chain. This research focuses on allocating two scarce resources, i.e., berth and quay cranes (QCs), to ships that call at a container terminal in a maritime supply chain. As global container shipments continue to grow, improving the efficiency of container terminals is important. A two-stage approach is used to find the optimal/near-optimal solution, in which the first stage is devoted to generating alternative ship placement sequences as inputs to the second stage that subsequently employs an event-based heuristic to place ships, resolve overlaps of ships, and assign/adjust QCs so as to develop a feasible solution. For identifying a better approach, various heuristics/metaheuristics, including first-come first-served (FCFS), particle swarm optimization (PSO), improved PSO (PSO2), and multiple PSO (MPSO), have been employed in the first stage, respectively. The experimental results show that combining the MPSO with the event-based heuristic leads to a better result.

Keywords: berth allocation problem (BAP); quay crane assignment problem (QCAP); metaheuristic; multiple particle swarms optimization (MPSO) (search for similar items in EconPapers)
JEL-codes: C (search for similar items in EconPapers)
Date: 2020
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