All-norm approximation for scheduling on identical machines

Yossi Azar, Shai Taub

Research output: Chapter in Book/Report/Conference proceedingChapterpeer-review

Abstract

We consider the problem of assigning jobs to m identical machines. The load of a machine is the sum of the weights of jobs assigned to it. The goal is to minimize the norm of the resulting load vector. It is known that for any fixed norm there is a PTAS. On the other hand, it is also known that there is no single assignment which is optimal for all norms. We show that there exists one assignment which simultaneously guarantees a 1.388-approximation of the optimal assignments for all norms. This improves the 1.5 approximation given by Chandra and Wong in 1975.

Original languageEnglish
Title of host publicationLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
EditorsTorben Hagerup, Jyrki Katajainen
PublisherSpringer Verlag
Pages298-310
Number of pages13
ISBN (Electronic)3540223398, 9783540223399
DOIs
StatePublished - 2004

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume3111
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

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