Abstract:Container seaport congestion is a challenging problem in improving the service level and optimizing evacuating container vessels after congestion. There is a lack of research on container vessel evacuation strategies for continuous terminals. In this article, the weight of the objective function is regarded as the index for the service priority of vessels. The effects of the service priority on the continuous terminal are analyzed by establishing a mixed integer programming model. The model minimizes the total… Show more
“…In the past several years, various disruptions have happened to port operations, and severe port congestion has been observed and frequently reported in the headlines of newspapers [1]. In early 2020, the COVID-19 pandemic began to spread rapidly in China, leading to labor shortages and reduced port capacity and causing significant disruptions to Chinese ports [2]; in March 2022, Shanghai implemented a lockdown to control the spread of COVID-19, which caused a large amount of congestion in Shanghai Port, the world's busiest container port.…”
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.
“…In the past several years, various disruptions have happened to port operations, and severe port congestion has been observed and frequently reported in the headlines of newspapers [1]. In early 2020, the COVID-19 pandemic began to spread rapidly in China, leading to labor shortages and reduced port capacity and causing significant disruptions to Chinese ports [2]; in March 2022, Shanghai implemented a lockdown to control the spread of COVID-19, which caused a large amount of congestion in Shanghai Port, the world's busiest container port.…”
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.
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