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Arthur M. Geoffrion
Researcher at University of California, Los Angeles
Publications - 66
Citations - 11685
Arthur M. Geoffrion is an academic researcher from University of California, Los Angeles. The author has contributed to research in topics: Modeling language & Linear programming. The author has an hindex of 37, co-authored 66 publications receiving 11391 citations. Previous affiliations of Arthur M. Geoffrion include University of California.
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Journal ArticleDOI
Generalized Benders decomposition
TL;DR: In this paper, the extremal value of the linear program as a function of the parameterizing vector and the set of values of the parametric vector for which the program is feasible were derived using linear programming duality theory.
Journal ArticleDOI
Proper efficiency and the theory of vector maximization
TL;DR: In this paper, the concept of proper efficiency was introduced to eliminate efficient points of a certain anomalous nature in the problem of vector maximization, which is related in spirit to the notion of "proper" efficiency introduced by Kuhn and Tucker in their celebrated paper of 1950.
Book ChapterDOI
Multicommodity Distribution System Design by Benders Decomposition
Arthur M. Geoffrion,G. W. Graves +1 more
TL;DR: In this paper, a multicommodity capacitated single-period version of the problem is formulated as a mixed integer linear program, and a solution technique based on Benders Decomposition is developed, implemented, and successfully applied to a real problem for a major food firm with 17 commodity classes, 14 plants, 45 possible distribution center sites, and 121 customer zones.
Book ChapterDOI
Lagrangian Relaxation for Integer Programming
TL;DR: It is a pleasure to write this commentary because it offers an opportunity to express my gratitude to several people who helped me in ways that turned out to be essential to the birth of [8].
Journal ArticleDOI
Interactive approach for multi-criterion optimization, with an application to the operation of an academic department.
TL;DR: An interactive mathematical programming approach to multi-criterion optimization is developed, and then illustrated by an application to the aggregated operating problem of an academic department.