In many practical situations one has to make decisions sequentially based on data available at the time of the decision and facing uncertainty of the future. This leads to optimization problems which can be formulated in a framework of multistage stochastic optimization. In this talk we consider risk neutral and risk averse approaches to multistage stochastic programming. We discuss conceptual and computational issues involved in formulation and solving such problems. As an example we give numerical results based on the Stochastic Dual Dynamic Programming method applied to planning of the Brazilian interconnected power system.
Biographie : Dr. Shapiro is Professor in the School of ISyE at Georgia Tech. His research interests include stochastic programming, risk analysis, simulation based optimization, non differentiable optimization, etc. He serves on editorial board of a number of professional journals. In particular, he is currently the Editor-In-Chief of the Mathematical Programming, Series A. In 2004 Dr. Shapiro joined the list of ISI Highly Cited Researchers.
Ce séminaire vous permettra d’échanger avec le conférencier et les chercheurs présents autour de boissons et de collations. L'inscription est interrompue du fait que le nombre d'inscrits dépasse la capacité de la salle du séminaire.
Bienvenue à tous!