Speaker: Bernardo K. Pagnoncelli

I will give a brief introduction to chance-constrained programming showing an example and motivating the subject. Then I will present a chance-constrained portfolio problem with random returns. Under normality, the problem can be efficiently solved, but in more general situations we have to rely on approximations. We apply different approximation schemes to the portfolio problem and we present the computational results. The talk will be aimed at a broad audience and no previous knowledge of chance-constrained programming is required.
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Bernardo K. Pagnoncelli has an B.S. and a M.Sc. in Mathematics from the Pontifical Catholic University of Rio de Janeiro, Brazil, and is a Ph.D. candidate in Mathematics at the same institution.

He was invited by Professor Shabbir Ahmed to spend one year as a Research Scholar at ISyE, working on Stochastic Programming.