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IE 410 OG - Adv Stochastic Process & Appl

Campus: Urbana-Champaign


Modeling and analysis of stochastic processes. Transient and steady-state behavior of continuous-time Markov chains; renewal processes; models of queuing systems (birth-and-death models, embedded-Markov-chain models, queuing networks); reliability models; inventory models. Familiarity with discrete-time Markov chains, Poisson processes, and birth-and-death processes is assumed. Course Information: Same as CS 481. 3 undergraduate hours. 4 graduate hours. Prerequisite: IE 310.

Option 1

Number of Required Visit(s): 0

Course Level: Graduate

Credit: 0

Term(s): Fall

Option 2

Number of Required Visit(s): 0

Course Level: Graduate

Credit: 4

Term(s): Fall


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