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Title : Some Recent Developments in Stochastic Programming
Date : February 18, 2008
Speaker : Alexander Shapiro, Professor
Affiliation : School of Industrial and Systems Engineering, Georgia Institute of Technology
Abstract
One often has to make decisions in conditions of uncertainty. The uncertainty can appear in various forms and can be modeled in different ways. Stochastic programming suggests an approach to making optimal decisions under uncertainty. It was introduced more than 50 years ago and originated in the development of linear programming. In this talk we first discuss basic concepts and then take a critical view on the foundations of stochastic programming.
Biosketch
Alexander Shapiro is a Professor in the School of Industrial and Systems Engineering at Georgia Institute of Technology. He received his Ph.D. at Ben-Gurion University , Israel , in Applied Mathematics-Statistics in 1981, and M.Sc. at Moscow University in Mathematics in 1971. His areas of interest include: Stochastic Programming, Simulation-based Optimization of Stochastic Systems and Multivariate Statistical Analysis. He has published more than 100 research articles in peer review journals and is a coauthor of several books (see below). His research is widely cited and he is listed as an ISI Highly Cited Researcher in 2004 on http://isihighlycited.com/ (ISI = Institute for Scientific Information). He is on the editorial board of several professional journals, including Mathematics of Operations Research and Mathematical Programming. His research has been supported by National Science Foundation. He is currently supported by NSF awards: Multistage Stochastic Convex Optimization; Tractable Approximations of Chance Constrained Optimization Problems.
