Syllabus
Rutgers University
College of Engineering
Department of Industrial Engineering
IE 481 Applied Queuing
Instructor: Dr. M. B. Gürsoy
Office: CoRE 218
Phone: X-5465
Email: gursoy@soe.rutgers.edu
COURSE OUTLINE
 
Topics to be covered:
    1. Review of Stochastic Processes: Markov chains; continuous time Markov chains; Poisson processes; birth and death processes, reversibility, generating functions (S. Ross, Ch. 4, 5 and 6).

    2. Renewal Processes; semi-Markov processes (S. Ross, Ch. 7).

    3. Introduction to queueing systems; Little’s theorem; birth and death queues; Jackson type networks (S. Ross, Ch. 8).

    4. Steady-state relations: DAASSP (departures and arrivals see same picture) theorem; ROSTA (random observer sees time averages); PASTA (Poisson arrivals see time averages).

    5. The random modification (remaining work in service); work conservation and work conserving disciplines.

    6. M/G/1 queue: busy period characteristics; non-preemptive priority queue; optimal priority policies; infinite server queues.

    7. Generalized M/G/1 queues; server’s breakdowns and vacations; Markov modulated arrivals and service; stochastic decomposition; preemptive repeat and resume priorities.

    8. Tandem queues; networks of queues; product form (Kelly type) networks; optimal ordering of stations.

    9. Applications of queueing models: service systems; traffic and transportation; communications; supply-chains.
References:
    1. S. Ross, Introduction to Probability Models, 8th Ed. Academic Press, 2003.

    2. L. Kleinrock, Queueing Systems, Vol. 1: Theory, Wiley&Sons, 1975.

    3. D. Gross and C. M. Harris, Fundamentals of Queueing Theory, Wiley&Sons, 1974.

    4. W. Wolff, Stochastic Modeling and the Theory of Queues, Prentice Hall, 1989.

※ All exams are closed book closed notes, no electronic or hard copy cheat sheets are allowed. Please go over the Rutgers Academic Integrity Policy.