Resource capacity requirement for multi-terminal cooperation in container ports

Capacity sharing among neighboring terminals offer a means to meet increasing or unexpected demand for cargo-handling without additional capital investment. This study proposes a model for capacity requirement planning of major resources, such as quay cranes (QCs), storage space, and gate, in multit...

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Bibliographic Details
Main Authors: LEE, Byung Kwon, LOW, Mei Wan
Format: text
Language:English
Published: Institutional Knowledge at Singapore Management University 2021
Subjects:
Online Access:https://ink.library.smu.edu.sg/lkcsb_research/6882
https://ink.library.smu.edu.sg/context/lkcsb_research/article/7881/viewcontent/applsci_11_09156_v2_pvoa.pdf
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Institution: Singapore Management University
Language: English
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Summary:Capacity sharing among neighboring terminals offer a means to meet increasing or unexpected demand for cargo-handling without additional capital investment. This study proposes a model for capacity requirement planning of major resources, such as quay cranes (QCs), storage space, and gate, in multiterminal port operations where demand is time dependent. A resource profile simulation is run to generate random events across the terminals and estimate the capacity requirement in the form of workload distributions on port resources over time-shifts. The effects on workload requirement, arising from multiterminal cooperation, are subsequently evaluated in consideration of different container flows among terminals. Experimental results suggest that higher transferring rate between terminals will reduce the QC intensity and storage space requirements but increase gate congestion. Variabilities in the QC intensity and storage space requirements also increase due to shorter stays and more movements in container inventory at the yard. The interaction effect between transferring and trans-shipment rates further shows that the average resource requirements for a terminal can be greatly reduced when the interterminal transferring of containers contributes positively to a more even workload redistribution across terminals. The most significant improvements occur when trans-shipment rate is 85% and transferring rate is 75% for QC intensity; trans-shipment rate is 90% and transferring rate is 60% for storage capacity; and trans-shipment rate is 80% and transferring rate is 75% for gate congestion.