Course Description

In the first six weeks, we will discuss the stochastic programming methodology. We will cover two-stage models, L-shaped method, multi-stage models, decomposition methods, and chance-constrained models. In the next three weeks, we will discuss stochastic dynamic programming methodology. We will cover finite horizon models, backward induction and monotone optimal policy. In the last three weeks, we will discuss the robust optimization methodology. We will cover uncertainty sets, two-stage models and multi-stage models.