Yuan Zhong
Associate Professor of Operations Management
Associate Professor of Operations Management
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.
REVISION: Cloud Computing Value Chains: Research from the Operations Management Perspective
Date Posted:Fri, 10 Jun 2022 07:23:14 -0500
Problem definition: Cloud computing has been recognized as a critical driver of Information-Technology enabled innovations. The Operations Management (OM) community, however, has not been exposed enough to the essential operations problems that arise from the management of cloud value chains. In this paper, we examine recent research on cloud value chains and explore future research opportunities from an OM perspective. In particular, we focus on major operations management challenges facing a cloud provider in three problem domains: (1) cloud computing resource management, (2) pricing in the cloud computing marketplaces, and (3) capacity planning and management of cloud supply chains.
Methodology and Results: We describe prevalent business models and management practices in the cloud value chains, discuss recent research from OM that falls into each of the three problem domains mentioned above, and point out opportunities for future research. We note that cloud computing ...
Designing Sparse Graphs for Stochastic Matching with an Application to Middle-Mile Transportation Management
Date Posted:Tue, 07 Jun 2022 15:04:12 -0500
Given an input graph Gin =(V,E_in), we consider the problem of designing a sparse subgraph G = (V, E) with E ? E_in that supports a large matching after some nodes in V are randomly deleted. We study three families of sparse graph designs (namely, Clusters, Rings, Chains, and Erd?s-R?nyi graphs) and show both theoretically and numerically that their performance is close to the optimal one achieved by a complete graph. Our interest in the stochastic sparse graph design problem is primarily motivated by a collaboration with a leading e-commerce retailer in the context of its middle-mile delivery operations. We test our theoretical results using real data from our industry partner and conclude that adding a little flexibility to the routing network can significantly reduce transportation costs.
New: Designing Sparse Graphs for Stochastic Matching with an Application to Middle-Mile Transportation Management
Date Posted:Tue, 07 Jun 2022 06:11:25 -0500
Given an input graph Gin =(V,E_in), we consider the problem of designing a sparse subgraph G = (V, E) with E ? E_in that supports a large matching after some nodes in V are randomly deleted. We study three families of sparse graph designs (namely, Clusters, Rings, and Erdos-Rényi graphs) and show both theoretically and numerically that their performance is close to the optimal one achieved by a complete graph. Our interest in the stochastic sparse graph design problem is primarily motivated by a collaboration with a leading e-commerce retailer in the context of its middle-mile delivery operations. We test our theoretical results using real data from our industry partner and conclude that adding a little flexibility to the routing network can significantly reduce transportation costs.
REVISION: Cloud Computing Value Chains: Research from the Operations Management Perspective
Date Posted:Thu, 10 Mar 2022 17:14:29 -0600
Problem definition: Cloud computing has been recognized as a critical driver of Information-Technology enabled innovations. The Operations Management (OM) community, however, has not been exposed enough to the essential operations problems that arise from the management of cloud value chains. In this paper, we examine recent research on cloud value chains and explore future research opportunities from an OM perspective. In particular, we focus on major operations management challenges facing a cloud provider in three problem domains: (1) cloud computing resource management, (2) pricing in the cloud computing marketplaces, and (3) capacity planning and management of cloud supply chains.
Methodology and Results: We describe prevalent business models and management practices in the cloud value chains, discuss recent research from OM that falls into each of the three problem domains mentioned above, and point out opportunities for future research. We note that cloud computing ...
Cloud Computing Value Chains: Research from the Operations Management Perspective
Date Posted:Thu, 18 Feb 2021 15:38:36 -0600
Problem definition: Cloud computing has been recognized as a critical driver of Information-Technology enabled innovations. The Operations Management (OM) community, however, has not been exposed enough to the essential operations problems that arise from the management of cloud value chains. In this paper, we examine recent research on cloud value chains and explore future research opportunities from an OM perspective. In particular, we focus on major operations management challenges facing a cloud provider in three problem domains: (1) cloud computing resource management, (2) pricing in the cloud computing marketplaces, and (3) capacity planning and management of cloud supply chains.
Methodology and Results: We describe prevalent business models and management practices in the cloud value chains, discuss recent research from OM that falls into each of the three problem domains mentioned above, and point out opportunities for future research. We note that cloud computing operations are driven by demand that exhibits the distinct characteristics including complex workflow, demand redundancy, multi- featured characteristics, multi-dimensional resource requirement, and non-stationarity. On the supply side, cloud computing operations also exhibit distinct characteristics including heterogeneous resources, packing constraints, bundled supply, technology risks, and cost uncertainty. These characteristics of demand and supply are not all prevalent in other operations.
REVISION: Process Flexibility for Multi-Period Production Systems
Date Posted:Mon, 23 Jul 2018 06:16:59 -0500
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 plus 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. The proof provides a simple and efficient algorithm for finding such sparse structures. Also, we show that the requirement of m plus n arcs is tight, by explicitly constructing systems in which even the best flexibility structure with m plus n minus 1 arcs cannot achieve the same asymptotic performance as full flexibility. The goal of this paper is to make progress towards the ...
REVISION: Process Flexibility for Multi-Period Production Systems
Date Posted:Sat, 21 Apr 2018 08:18:22 -0500
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 plus 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. The proof provides a simple and efficient algorithm for finding such sparse structures. Also, we show that the requirement of m plus n arcs is tight, by explicitly constructing systems in which even the best flexibility structure with m plus n minus 1 arcs cannot achieve the same asymptotic performance as full flexibility. The goal of this paper is to make progress towards the ...
REVISION: Process Flexibility for Multi-Period Production Systems
Date Posted:Wed, 17 Jan 2018 21:05:02 -0600
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 ...
REVISION: Process Flexibility for Multi-Period Production Systems
Date Posted:Fri, 06 Oct 2017 11:06:10 -0500
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 ...
REVISION: Process Flexibility for Multi-Period Production Systems
Date Posted:Sat, 08 Jul 2017 10:21:25 -0500
We develop a theory for the design of process flexibility in a multi-period production system. We propose and formalize a notion of "effective chaining" termed the Generalized Chaining Condition (GCC), which includes the chaining structure put forth by cite {JG95} as a special case. We show that any partial flexibility structure that satisfies GCC is near-optimal under a class of policies called the Max-Weight policies, i.e., gaining nearly as much benefit as a fully flexible system. Furthermore, we show that GCC can be satisfied using very sparse flexibility structures, and we provide an efficient algorithm for finding such structures. Our numerical study confirms insights from our theoretical results. The goal of this paper is to make progress towards the better understanding of the key design principles of process flexibility structures in a multi-period environment, the study of which has been limited due to its inherent complexity.
REVISION: Process Flexibility for Multi-Period Production Systems
Date Posted:Sun, 06 Sep 2015 00:53:07 -0500
We develop a theory for the design of process flexibility in a multi-period production system. We propose and formalize a notion of "effective chaining" termed the Generalized Chaining Condition (GCC), which includes the chaining structure put forth by \cite{JG95} as a special case. We show that any partial flexibility structure that satisfies GCC is near-optimal under a class of policies called the Max-Weight policies, i.e., gaining nearly as much benefit as a fully flexible system. Furthermore, we show that GCC can be satisfied using very sparse flexibility structures, and we provide an efficient algorithm for finding such structures. Our numerical study confirms insights from our theoretical results. The goal of this paper is to make progress towards the better understanding of the key design principles of process flexibility structures in a multi-period environment, the study of which has been limited due to its inherent complexity.
Process Flexibility for Multi-Period Production Systems
Date Posted:Sat, 05 Sep 2015 19:13:32 -0500
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 plus 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. The proof provides a simple and efficient algorithm for finding such sparse structures. Also, we show that the requirement of m plus n arcs is tight, by explicitly constructing systems in which even the best flexibility structure with m plus n minus 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 the key design principles of process flexibility structures in a multi-period environment.
REVISION: Process Flexibility for Multi-Period Production Systems
Date Posted:Sat, 05 Sep 2015 10:13:32 -0500
We develop a theory for the design of process flexibility in a multi-period production system. We propose and formalize a notion of ``effective chaining" termed the Generalized Chaining Condition (GCC), which includes the chaining structure put forth by \cite{JG95} as a special case. We show that any partial flexibility structure that satisfies GCC is near-optimal under a class of policies called the Max-Weight policies, i.e., gaining nearly as much benefit as a fully flexible system. Furthermore, we show that GCC can be satisfied using very sparse flexibility structures, and we provide an efficient algorithm for finding such structures. Our numerical study confirms insights from our theoretical results. The goal of this paper is to make progress towards the better understanding of the key design principles of process flexibility structures in a multi-period environment, the study of which has been limited due to its inherent complexity.
Number | Course Title | Quarter |
---|---|---|
40000 | Operations Management: Business Process Fundamentals | 2025 (Spring) |