This course provides an overview of asymptotic models and methods used in various areas of operations management. It includes traditional heavy traffic asymptotics for queueing networks, the Halfin-Whitt regime, the supermarket model, inventory theory, revenue management, applications of measure-valued processes in queues, and applications of mean field equilibrium models in matching markets and auctions for ad exchanges. The lectures will focus on modeling and performance analysis, and not on convergence proofs. Prerequisites: Statistics OIT 217 and OIT 218, or consent of instructor; some prior exposure to stochastic models in general, and queueing theory in particular, is useful but not essential.
3 units · GSB Student Option LTR/PF
This course provides an overview of asymptotic models and methods used in various areas of operations management. It includes traditional heavy traffic asymptotics for queueing networks, the Halfin-Whitt regime, the supermarket model, inventory theory, revenue management, applications of measure-valued processes in queues, and applications of mean field equilibrium models in matching markets and auctions for ad exchanges. The lectures will focus on modeling and performance analysis, and not on convergence proofs. Prerequisites: Statistics 217 and 218, or consent of instructor; some prior exposure to stochastic models in general, and queueing theory in particular, is useful but not essential.
Offered in Spring 2026 at Stanford University.