A parallel approximation algorithm for positive linear programming

Michael Luby, Noam Nisan

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

130 Scopus citations

Abstract

We introduce a fast parallel approximation algorithm for the positive linear programming optimization problem, i.e. the special case of the linear programming optimization problem where the input constraint matrix and constraint vector consist entirely of positive entries. The algorithm is elementary, and has a simple parallel implementation that runs in polylog time using a linear number of processors.

Original languageAmerican English
Title of host publicationProceedings of the 25th Annual ACM Symposium on Theory of Computing, STOC 1993
PublisherAssociation for Computing Machinery
Pages448-457
Number of pages10
ISBN (Electronic)0897915917
DOIs
StatePublished - 1 Jun 1993
Event25th Annual ACM Symposium on Theory of Computing, STOC 1993 - San Diego, United States
Duration: 16 May 199318 May 1993

Publication series

NameProceedings of the Annual ACM Symposium on Theory of Computing
VolumePart F129585
ISSN (Print)0737-8017

Conference

Conference25th Annual ACM Symposium on Theory of Computing, STOC 1993
Country/TerritoryUnited States
CitySan Diego
Period16/05/9318/05/93

Bibliographical note

Publisher Copyright:
© 1993 ACM.

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