Identifying port congestion and evaluating its impact on maritime logistics

ABSTRACT

Port congestion is an obstacle to smooth energy supply chain management. This research identifies and quantifies the economic implications of congestion in a real-time framework, in which the temporal and geospatial port congestion status is analysed using the vessel tracking information captured by satellites, the Automatic Identification System. A Density-Based Spatial Clustering of Applications with Noise (DBSCAN) algorithm is proposed to automatically identify vessel clusters at ports and quantify port turnaround time, and thus real-time port congestion status. A framework is then outlined to analyze the economic implications of congestion for various stakeholders in the system. A case study is conducted on Indian LPG ports, where congestion frequently occurs. The analysis has important implications for the industrial participants engaged in energy transportation to assess the impact, and for policymakers in a better network design.

KEYWORDS:

• Congestion
• clustering
• AIS
• liquified petroleum gas (LPG)
• VLGC

Disclosure statement

No potential conflict of interest was reported by the author(s).

Notes

1. In this paper, seaport and port is used interchangeably.

Additional information

Funding

This work was partially supported by the National Natural Science Foundation of China [Project No. 72001123] and partially supported by the Norwegian Research Council under the project Smart Digital Contract and Commercial Management [grant number 280684].