Spring 2005 Seminar Series

DATE: Thursday, March 17, 2005
LOCATION: E40-298
TIME: 4:15pm
Reception immediately following in the Philip M. Morse Reading Room, E40-106

SPEAKER:
Garud Iyengar
Associate Professor
Department of Industrial Engineering and Operations Research
Columbia University

TITLE
Uncertainty, Learning, and Robust Optimization

ABSTRACT
Parameter uncertainties that are inevitable in decision models. Optimization problems are especially susceptible to these errors since, in trying to maximally exploit the constraints, the optimal solutions typically amplify these errors several fold. In the robust optimization framework the perturbations are modeled as unknown, but bounded, and the solutions are computed assuming worst case behavior of these perturbations. This talk will begin with a brief introduction to robust optimization. We will use robust portfolio selection problems as the motivating application. Next, we introduce adjustably robust optimization problems and discuss its application in modeling staffing and routing decisions in call centers. The talk will conclude with a discussion of ambiguous chance constrained problem.Joint work with Donald Goldfarb and Emre Erdogan.