Computable Bounds on Stationary Expectations for Markov Processes

Peter Glynn
Management Science and Engineering
Stanford University


Wednesday, February 20, 2008
4:30 - 5:30 PM
Terman Engineering Center, Room 453


Abstract:

Many performance engineering and operations research modeling formulations lead to Markov models in which the key performance measure is an expectation defined in terms of the stationary distribution of the process. In models of realistic complexity, it is often difficult to compute such expectations in closed form. In this talk, we will discuss a simple class of bounds for such stationary expectations. This work is joint with Assaf Zeevi.

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Operations Research Colloquia: http://or.stanford.edu/oras_seminars.html