Curso - 25 aulas.

This IMPA Master and PhD course will consist of 40 hours of lectures and 20 hours of computational practice on the topics below: 1. Stochastic Programming, motivation 2. Revision of topics on convex analysis, measure and probability theory 3. Two-Stage Programming: Theory and Algorithms 4. Multi-Stage Programming: Theory and Algorithms 5. Risk Averse Optimization 6. State-of-the-art methods References: Lectures on Stochastic Programming: Modeling and Theory, by Alexander Shapiro, Darinka Dentcheva and Andrezj Ruszczynski,SIAM, Philadelphia, 2009. (Available for download on the authors webpage) Stochastic Programming, vol 10 of Handbooks in Operations Research and Management Sciences, by Alexander Shapiro and Andrezj Ruszczynski, Elsevier, 2003. Stochastic programming, by Peter Kall, Stein W. Wallace, Wiley, 1994 Selected related papers will be suggested along the course .