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Answers delayed are answers denied

Answers delayed are answers denied Modern Linear Programming (LP) models have become so large that the data management system that loads the data and reports the results requires as much attention as the selection of the optimizer. Two philosophically different approaches to LP data management are reviewed in this paper; (1) using a general purpose programming language (e.g. PL/I) and (2) using a special purpose language (perversely called "matrix generator" in the trade) designed specifically to support LP models. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png ACM SIGMAP Bulletin Association for Computing Machinery

Answers delayed are answers denied

ACM SIGMAP Bulletin , Volume (27) – Jul 1, 1979

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Publisher
Association for Computing Machinery
Copyright
Copyright © 1979 by ACM Inc.
ISSN
0163-5786
DOI
10.1145/1111246.1111248
Publisher site
See Article on Publisher Site

Abstract

Modern Linear Programming (LP) models have become so large that the data management system that loads the data and reports the results requires as much attention as the selection of the optimizer. Two philosophically different approaches to LP data management are reviewed in this paper; (1) using a general purpose programming language (e.g. PL/I) and (2) using a special purpose language (perversely called "matrix generator" in the trade) designed specifically to support LP models.

Journal

ACM SIGMAP BulletinAssociation for Computing Machinery

Published: Jul 1, 1979

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