Faculty & Research

Yuan Zhong

Assistant Professor of Operations Management

Phone :
1-773-702-3313
Address :
5807 South Woodlawn Avenue
Chicago, IL 60637

Yuan Zhong researches applied probability, as well as modeling and analysis of large-scale stochastic systems, with business and engineering applications. More recently his research interests have extended to applications in data centers and cloud computing. Zhong’s research has been published in several journals including Queueing Systems and The Annals of Applied Probability.

Prior to Booth, Zhong was an assistant professor at Columbia University in the Department of Industrial Engineering and Operations Research. At Columbia he taught courses in stochastic networks, simulation, and probability models. Before joining Columbia in 2013, Zhong spent one year as a Postdoctoral Scholar in the Computer Science Department at UC Berkeley.

Zhong received a PhD in operations research from MIT in2012, an MA in mathematics from Caltech in 2008, and a BA in mathematics from the University of Cambridge in 2006.

 

2017 - 2018 Course Schedule

Number Name Quarter
36600 Workshop in Operations/Management Science 2017 (Fall)
36600 Workshop in Operations/Management Science 2018 (Spring)
40000 Operations Management: Business Process Fundamentals 2018 (Winter)
40907 Healthcare Operations 2018 (Spring)

REVISION: Process Flexibility for Multi-Period Production Systems
Date Posted: Oct  06, 2017
We develop a theory for the design of process flexibility in a multi-period make-to-order production system. We propose and formalize a notion of ``effective chaining" termed the Generalized Chaining Gap (GCG), which can be viewed as a natural extension of classical chaining structure from the process flexibility literature. Using the GCG, we prove that in a general system with high capacity utilization, one only needs a sparse flexibility structure with m n arcs to achieve similar performance as full flexibility, where m and n are equal to the number of plants and products in the system, respectively. We also provide a simple and efficient algorithm for finding such sparse structures. Moreover, we show that the requirement of m n arcs is tight, by explicitly constructing systems in which even the best flexibility structure with m n-1 arcs cannot achieve the same asymptotic performance as full flexibility. The goal of this paper is to make progress towards the better understanding of ...