IE 410 - Stochastic Processes and Their Applications

Semesters Offered

Official Description

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.

Prerequisites

Credit in IE 310

Course Description

Modeling and analysis of stochastic processes. Background on probability models. Transient and steady-state behavior of discrete-time Markov chains. Time-reversible Markov chains, Markov decision processes. Applications of Markov chains. Branching processes. Homogeneous and inhomogeneous Poisson processes. Selected topics. Same as CS 481. 3 undergraduate hours. 4 graduate hours. Prerequisite: IE 310.

Documents

Last updated

8/23/2016