Dr. John R. Birge
Hobart W. Williams Distinguished Service Professor of Operations Management, Booth School of Business, University of Chicago
Title: Optimization and Estimation in High Dimensions
Abstract : Many decision models involve both parameter estimation and optimization over a set of decision variables. Asymptotic properties of the estimators are often used to justify a model’s validity, but these results may not be applicable in high dimensions. This talk will discuss the potential bias that arises in these optimization settings and potential approaches to remove this bias in high-dimensional models.
Dr. Nick Sahinidis
Gary C. Butler Family Chair and Professor, The H. Milton Stewart School of Industrial and Systems Engineering, Georgia Tech
Title: Global black-box optimization
Abstract: This talk presents a new optimization algorithm for black-box optimization problems for which optimization must be performed in the absence of an algebraic formulation, i.e., by utilizing only data originating from simulations or experiments. Our approach combines model-based search with a dynamic domain partition strategy that guarantees convergence to a global optimum. Equipped with a clustering algorithm for balancing global and local search, the proposed approach outperforms existing derivative-free optimization algorithms on a large collection of problems.
*Keynote speakers are sponsored by the University of Florida Office of Research