Best Paper of 2000
New algorithms for nonlinear generalized disjunctive programming: Sangbum Lee and Ignacio E. Grossmann, Department of Chemical Engineering, Carnegie Mellon University, Pittsburgh, PA 15213, USA

https://doi.org/10.1016/S0098-1354(02)00269-7Get rights and content

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About the authors

Sangbum Lee is a Ph.D. student in Chemical Engineering Department at Carnegie Mellon University. He obtained his B.S. degree in Chemical Engineering at Seoul National University, Seoul, Korea in 1994 and joined Professor Ignacio E. Grossmann's group in January 1998. He will obtain his Ph.D. degree in May 2002. Sangbum Lee is a member of the American Institute of Chemical Engineers, Institute for Operations Research and Management Science, and Korean Institute of Chemical Engineers.

The research

Abstract

See Vol. 24, No. 9–10, pp. 2125–2141 (2000) for the full paper.

Over the last decade Mixed Integer Nonlinear Programming (MINLP) models have been widely used in chemical engineering for modeling 0–1/continuous optimization problems. MINLP problems arise, for instance, in process synthesis (e.g. superstructure optimization of reactor networks, distillation sequences, heat exchanger networks), in the planning of process networks, and in the scheduling of batch and continuous multiproduct plants.

Editorial note

The Editorial Advisory Board of the Journal has assessed the papers published in Volume 24 by means of a three stage process consisting of nomination, first round elimination, and final round balloting. The winner of this process was the paper by Sangbum Lee and Ignacio Grossmann.

This paper was cited for presenting an innovative method for the solution of an important class of mixed integer nonlinear programming problems. The continuous relaxation of the underlying generalized disjunctive

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