IE 370 - Stochastic Processes & Applic
Introduction to stochastic processes with applications in decision-making under uncertainty. Topics include newsvendor problem, discrete-time Markov chain (including classification of states, stationary distribution, absorbing states), Poisson processes (including time-homogenous, time-nonhomogeneous, thinning Poisson), continuous-time Markov chain (including Markov property, generator matrix, stationary distribution), queuing theory (including M/M/k queue, open Jackson network), and Markov decision processes (including finite-horizon models, infinite-horizon models). Course Information: Prerequisite: IE 300 and IE 310.
|Stochastic Processes & Applic||SP||66991||OLC||3||1700 - 1820||T R||Alexander Stolyar|