Generalized Networks, Generalized Upper Bounding and Decomposition of the Convex Simplex Method

David P. Rutenberg
Additional contact information
David P. Rutenberg: Graduate School of Industrial Administration, Carnegie-Mellon University

Management Science, 1970, vol. 16, issue 5, 388-401

Abstract: If the constraint matrix of a linear program has special structure it may be possible to speed computation. Techniques have been developed to take advantage of such special structures as generalized networks, generalized upper bounding, and decomposition. For these matrix structures, it is shown in this paper how to extend the techniques to Zangwill's mathematical programming algorithm, the convex simplex method.

Date: 1970
References: Add references at CitEc
Citations:

Downloads: (external link)
http://dx.doi.org/10.1287/mnsc.16.5.388 (application/pdf)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:inm:ormnsc:v:16:y:1970:i:5:p:388-401

Access Statistics for this article

More articles in Management Science from INFORMS Contact information at EDIRC.
Bibliographic data for series maintained by Chris Asher ().