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題目：A Queueing-theoretic Framework for Evaluating Transmission Risks in Service Facilities During a Pandemic

主講人：Kang Kang Ph.D. Candidate, Department of Industrial & Systems Engineering, University of Minnesota – Twin Cities, Minneapolis, MN

時(shí)間：11月12日（周五） 8:30-10:30

地點(diǎn)：bwin必贏唯一官網(wǎng)302室

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Abstract: We propose a new modeling framework for evaluating the risk of disease transmission during a pandemic in small-scale settings driven by stochasticity in the arrival and service processes, i.e., congestion-prone confined-space service facilities, such as grocery stores. We propose a novel metric inspired by R0, the "basic reproduction number" concept from epidemiology, which measures the transmissibility of infectious diseases. We derive our metric for various queueing models of service facilities by leveraging a novel queueing-theoretic notion: sojourn time overlaps. We showcase how our metric can be used to explore the efficacy of a variety of interventions aimed at curbing the spread of disease inside service facilities. Specifically, we focus on some prevalent interventions employed during the COVID-19 pandemic: limiting the occupancy of service facilities, protecting high-risk customers (via prioritization or designated time windows), and increasing the service speed (or limiting patronage duration). We discuss a variety of directions for adapting our transmission model to incorporate some more nuanced features of disease transmission, including heterogeneity in the population immunity level, varying levels of mask usage, and spatial considerations in disease transmission.  This talk is based on joint-work with Professor Doroudi and Ph.D. student Alexander Wickeham at the University of Minnesota and Professor Mohammad Delasay at Stony Brook University.

主講人介紹：

Kang Kang is a Ph.D. candidate in the Department of Industrial and Systems Engineering (ISyE) at the University of Minnesota (UMN), advised by Dr. Sherwin Doroudi; previously he received a B.S. in Mathematics & Applied Mathematics and a BEcon in Actuarial Science from Jilin University in China. His research interests are in service operations. Methodologically,he relies on techniques drawn from stochastic modeling and applied probability. His research is focused on modeling, analyzing, and designing service systems that perform well with respect to efficiency, fairness, and safety by leveraging and reinventing the quantitative techniques offered by the mathematical area of queueing theory. He is interested in a broad range of applications, particularly focused on applications in healthcare and emerging service system. Kang's work as a teaching assistant was recognized by being granted the John Bowers Excellence in Teaching Assistance Award; this award is offered to only one or two teaching assistants in the entire College of Science and Engineering at the University of Minnesota each year.