We are all familiar with waiting in lines – in the grocery store, on the telephone, at the airport, on the road. Queueing theory is the mathematical study of lines. Fundamental questions in queueing theory are: What are the stochastic characteristics of delay? For example, what is the average delay? What is the probability that delay exceeds some threshold? What fraction of customers are turned away? What system capacity (e.g., what number of servers) is needed to achieve a specified quality of service? Answers to these questions provide decision makers a way to efficiently allocate resources to reduce delay. This course provides a survey of quantitative models used to analyze queueing systems. The focus is both on mathematical analyses of such models as well as practical issues in using such models to represent real problems. The course assumes prior knowledge of calculus-based probability. Knowledge of continuous-time Markov chains (CTMCs) is very helpful, but not required (key aspects of CTMCs will be presented briefly in class). The pre-requisite for this course is OR 542 (Stochastic Models), or STAT 544 (Applied Probability), or permission of the instructor.

Class Hours: Spring 2011, Mon 7:20 - 10:00 pm, Innovation, room 316

Prerequisite: OR 542 (stochastic models), or STAT 544 (applied probability), or permission of instructor

Instructor: John Shortle, , 703-993-3571, Engineering Building, rm 2210

Office Hours (Spring 2011): Mon 11:00-noon, 6:15-7:15 pm.

Textbook: Gross, Shortle, Thompson, Harris, Fundamentals of Queueing Theory, Fourth Edition.

General Course Information

• Course Overview