Wuqin Lin
Wuqin Lin

MANAGERIAL ECONOMICS & DECISION SCIENCES; OPERATIONS
Assistant Professor of Managerial Economics & Decision Sciences

Print Overview
Wuqin Lin joined Managerial Economics and Decision Sciences in 2005, after receiving his PhD in Industrial Engineering from Georgia Tech. His research interests include performance analysis, optimal control, and capacity management of queuing and stochastic processing networks that arise in manufacturing, service, and information systems. His current work is on queuing models of hospital emergency departments, with a focus on the main causes of emergency department overcrowding, as well as capacity planning of emergency departments.

Areas of Expertise
Optimization
Queuing Systems
Print Vita
Education
PhD, 2005, Industrial and Systems Engineering, Georgia Institute of Technology
MPhil, 2001, Engineering Management, Industrial Engineering, Hong Kong University of Science and Technology
BS, 1998, Electronic Communication, Shanghai Jiao Tong University, China

Academic Positions
Assistant Professor of Managerial Economics and Decision Sciences, Kellogg School of Management, Northwestern University, 2006-present
Donald P. Jacobs Scholar in Managerial Economics and Decision Sciences, Kellogg School of Management, Northwestern University, 2005-2006

 
Print Research
Research Interests
Stochastic process, applied probability, optimization, stochastic processing networks, logistics and supply chain management

Articles
Allon, Gad, Sarang Deo and Wuqin Lin. 2013. The Impact of Size and Occupancy of Hospital on the Extent of Ambulance Diversion: Theory and Evidence. Operations Research.
Dai, Jim and Wuqin Lin. 2009. Asymptotic Optimality of Maximum Pressure Policies in Stochastic Processing Networks. Annals of Applied Probability. 18: 2239-2299.
Ata, Baris and Wuqin Lin. 2008. Heavy Traffic Analysis of Maximum Pressure Policies for Stochastic Processing Networks with Multiple Bottlenecks. Queueing Systems: Theory and Applications. 59: 191-235.
Lin, Wuqin, Zhen Liu and Li Zhang. 2005. Optimal capacity allocation for web systems with end-to-end delay guarantees. Performance Evaluation. 62: 400-416.
Dai, Jim and Wuqin Lin. 2005. Maximum Pressure Policies in Stochastic Processing Networks. Operations Research. 53(2): 197-218.
Cheung, Raymond, Chung-Lun Li and Wuqin Lin. 2002. Interblock Crane Deployment in Container Terminals. Transportation Science. 36(1): 79-93.
Working Papers
Lin, Wuqin. 2012. Risk Aversion and the Single Server Queue.

 
Print Teaching
Teaching Interests
Stochastics, operations management
Full-Time / Part-Time MBA
Analytical Decision Modeling (OPNS-450-0)

This course counts toward the following majors: Decision Sciences, Managerial Analytics, Operations.

This course focuses on structuring, analyzing and solving managerial decision problems on Excel spreadsheets. We address problems of resource allocation (how to use available resources optimally), risk analysis (how to simulate the effects of uncertainty in problem parameters), decision analysis (how to analyze sequential decisions involving uncertainty), data analysis (how to synthesize the available data into useful information) and forecasting (how to extrapolate past observations into the future). In each area, we pose specific problems from operations, finance and marketing, structure them on Excel spreadsheets, and analyze and solve them using the available Excel commands, tools and add-ins. The course involves a hands-on, in-class learning experience in modeling and analyzing a variety of business decision problems on a common spreadsheet platform. It should, therefore, enhance one's problem-solving capabilities as well as spreadsheet skills. A good working knowledge of Microsoft Excel is required. Prerequisites: OPNS-430 and FINC-430/FINC-440. May be taken concurrently.

Doctoral
Stochastic Calculus and Control with Applications (formerly OPNS-462-0) (OPNS-510-0)
Stochastic Calculus and Control With Applications

Queueing Networks: Performance Analysis (OPNS-522-0)
The course is to introduce the basic methods that are often used for analyzing performance in queueing network models. The students will learn how to characterize various queueing performance measures and apply to managerial decision making. Students should have familiarity with Markov process.