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Title : Global Optimization Approaches for a Class of Discrete Optimization Problems on Graphs
Date : Nov 26, 2007
Speaker : Sergiy Butenko, Assistant Professor
Affiliation : Department of Industrial and Systems Engineering, Texas A&M University
Abstract
One of the most promising directions in global optimization research deals with continuous (nonconvex) approaches to discrete optimization problems on graphs. Bridging the continuous and discrete domains may reveal surprising connections between problems of seemingly different nature and lead to new developments in both discrete and continuous optimization. In this talk we will concentrate on methodological aspects of continuous-based approaches to discrete optimization problems. In particular, we will present common ways of formulating discrete problems as continuous box-constrained programs and developing optimality conditions for discrete problems based on their continuous formulations. We will also discuss related computational complexity issues, lower and upper bounds based on nonlinear formulations, as well as numerical solution strategies. In addition, we will highlight some interesting directions for future research.
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Dr . Butenko received B.S. and M.S. degrees from Kyiv Taras Shevchenko University ( Ukraine ) in 1998 and 1999, respectively, and M.S. and Ph.D. degrees from the University of Florida in 2001 and 2003, respectively. His research concentrates mainly on global and discrete optimization and their applications. In particular, he is interested in theoretical and computational aspects of continuous global optimization approaches for solving discrete optimization problems on graphs. Applications of interest include network-based data mining, computational biology, social networks and remote sensing.
