Stochastic Optimization. 3 credits

Catalog description

Provides an introduction to stochastic optimization, more specifically, stochastic programming. The objectives are (i) to provide students with the ability to model and solve optimization problems under uncertainty, and (ii) to make students familar with the state-of-the-art of stochastic programming. Homework will be used to reinforce and supplement information in each section. Through the semester we will be reading research papers to supplement the material in the text book. Papers and other course material will be provided on Blackboard. Students should be proficient with one programming language (e.g. MATLAB, Python, Java, C++) and should be able to become familiar with a math programming solver (e.g. Cplex, Gurobi.) Offered by Systems Engr & Operations Rsch . May not be repeated for credit.