Abstract: We  discuss two aspects of  multistage stochastic optimization. In the first part we present several results about approximations of large or even huge problems by simpler ones. The basic continuity result is based on convexity arguments and the notion of the nested distance between scenario processes. We derive upper and lower bounds for the solution of multistage programs and illustrate them with some examples. In the second part of the talk we give a rigorous definition of the time consistency property for risk functionals and for multistage decision problems. We characterize time-consistent functionals. A main result states that non-time consistent decision problem can be made time consistent by enlarging the decision space and replacing the original problem by a minimax problem.  Finally examples from optimal management of thermo and hydro electricity plants are presented. If there is time also pricing principles for flexible energy delivery contracts based on multistage stochastic bilevel optimization are discussed. 

Bio: Georg Pflug is a Professor at the University of Vienna. He is one of the worldwide leading experts in stochastic programming. He is Author of 4books, editor of 5 books, and more than 70 publications in refereed journals, such as: Annals of Statistics, Annals of OR, Probability Theory, J Statist. Planning and Inference, J. ACM, Parallel Computing, The Computer Journal, Math. Programming, Mathematics of Optimization, SIAM J. on Optimization, Computational Optimization and Applications, J. Applied Probability, Stoch. Processes and Applications, Graphs and Combinatorics, J. Theoretical Computer Science, Quantitative Finance etc.