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Estimating vessel waiting time using queuing models
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AI
DOI：10.1057/s41278-025-00319-2.png)
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Abstract
En 中文
In the complex network of international trade, ports act as critical nodes facilitating the smooth movement of goods. The efficiency of port operations, particularly the estimation of vessel waiting times, has significant implications for various stakeholders. This study aims to improve vessel waiting time predictions, addressing critical gaps in port planning and investment decisions. This study scrutinizes the efficacy of advanced queuing models, specifically the Pointwise Stationary Approximation (PSA) and M/G/c\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$M/G/c$$\end{document} models, in accurately estimating vessel waiting times in port. The analysis, utilizing empirical data from the Port of Busan, reveals that the advanced models perform better than the conventional models. Our findings show that conventional models often misrepresent waiting times, with significant implications for capacity expansion programs, both in long-haul and intraregional terminals. Our improved approach can prevent overinvestment while ensuring adequate capacity, ultimately strengthening logistics competitiveness.
Keywords:
Queuing models
Vessel waiting time
Ports
Container terminals
Time dependency
Pointwise stationary approximation
General distribution
M/G/c
Journal
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4.8
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494
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