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Global Optimization with Branch-and-Reduce

We describe theoretical and algorithmic components of the branch-and-reduce approach to the global optimization of continuous, integer, and mixed-integer nonlinear programs. These include: a theory of convex extensions for the construction of closed form expressions of convex envelopes of nonlinear functions, an entirely linear-programming-based approach to global optimization, a theory of domain reduction, and proofs of finiteness for certain branching schemes. Applications from a variety of application areas will be reviewed and extensive computational results with BARON will be reported.
Type of Seminar:
Public Seminar
Prof. Nick Sahinidis
Department of Chemical and Biomolecular Engineering / University of Illinois at Urbana-Champaign
May 29, 2006   16:30 (coffee at 16:00)

ETH Zentrum, Main Building, Room HG E41
Contact Person:

Prof. Manfred Morari
No downloadable files available.
Biographical Sketch:
Nick Sahinidis is a Professor of Chemical and Biomolecular Engineering at the University of Illinois at Urbana, where he is also affiliated with Bioengineering, Computer Science, and Industrial Engineering. He obtained his Ph.D. from Carnegie Mellon University in 1990 and has been at the University of Illinois since 1991. Nick’s current research interests are at the interface between computer science and operations research, with applications in chemical, biological, and engineering systems. His research has focused heavily on the development of theory, algorithms, and software for global optimization of mixed-integer nonlinear programs. His BARON global optimization software has found applications in fields ranging from computational chemistry to energy modeling. Nick has served on eight editorial boards, including the Journal of Global Optimization and Optimization and Engineering. He is active in several professional societies, including AIChE, INFORMS, and the Mathematical Programming Society. His research activities have been recognized by several awards, including the 2004 INFORMS Computing Society Prize.