Network Disruptions and Ripple Effects: Queueing Model, Simulation, and Data Analysis of Port Congestion

Abstract

Disruptions often happen to ports and cause varying degrees of port congestion. This study employs a queueing model to investigate network disruption and the resultant ripple effects in the global transportation system. We first propose an algorithm to solve the queueing model. Based on the queueing model, we obtain analytical results or propose hypotheses regarding the mechanism under disruptions. We further conduct simulations to examine the analytical results and hypotheses. Three key findings in this study are: (1) disruptions in the small port lead to a longer round-trip time compared to those in the large port; (2) herding behavior in the transportation system causes heavier congestion and also produces more emissions; and (3) major-rare disruptions cause a longer waiting time at both the port under disruption and other ports of call in the transportation system. These insights can help operators understand the mechanism of disruptions and put in place countermeasures.