报告摘要和内容： The pandemic time witnessed a significant increase in port congestion, leading to shipping delays and rising costs for shippers. We build a fluid model to investigate how disruptions at one port can affect both the disrupted port and its counterpart in another country in a circulatory system where a stream of fleets transport goods back and forth between the two ports.We provide an analytical expression for the recovery time of the system of two portsand track the evolution of backlogs of goods and ships during the recovery process. We identifya whiplash effect in the outbound backlog level at both ports, which bears a resemblance to the commonly known “bullwhip effect”. Notably, the whiplash effect manifests in three primary features, namely oscillation, attenuation, and lag. Furthermore, we extend our analysis to a network of ports and show that the key findings and insights derived from the two-port model still hold in the multi-port bipartite system. This finding confirms that, despite its parsimony, the two-port system sufficiently captures the impact of port disruptions.We also extend the fluid modelto a diffusion approximation model. Finally, we apply machine learning techniques to predict the time that vessels spend in the Shanghai port and show that our proposed model reduces prediction errors compared to the benchmark, demonstrating the potential and power of our model in helping to predict and mitigate the impact of disruptions in a circulatory transportation system, e.g., those in container shipping and air traveling industries. |
报告人简介： 
Ming Huis the University of Toronto Distinguished Professor of Business Operations and Analytics, a professor of operations management at the Rotman School of Management, and an Amazon Scholar. He was named one of Poets & Quants Best 40 Under 40 business school professors in 2018.He currently serves as the editor-in-chief of NRL, an associate editor of MS, OR, and MSOM, and a senior editor of POM. |
