Stochastic Models in Operations Research

A graduate-level course on modeling systems that evolve randomly over time and deciding how to act when the future is uncertain. You'll work through Markov chains, Markov decision processes, renewal and queueing models, and stochastic dynamic programming for inventory and production, mostly via four problem sets plus a midterm and final that push you to formulate real systems and compute their long-run performance. It builds on undergraduate probability and IE 400-level optimization, and sits at the analytical core of OR, feeding directly into queueing networks, simulation, supply chain analytics, and most operations-focused PhD research.