Vector assignment problems: A general framework

Leah Epstein, Tamir Tassa

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


We present a general framework for vector assignment problems. In such problems one aims at assigning n input vectors to m machines such that the value of a given target function is minimized. While previous approaches concentrated on simple target functions such as max-max, the general approach presented here enables us to design a PTAS for a wide class of target functions. In particular we are able to deal with non-monotone target functions and asymmetric settings where the cost functions per machine may be different for different machines. This is done by combining a graph-based technique and a new technique of preprocessing the input vectors.

Original languageEnglish
Title of host publicationAlgorithms - ESA 2002 - 10th Annual European Symposium, Proceedings
EditorsRolf Möhring, Rajeev Raman
PublisherSpringer Verlag
Number of pages13
ISBN (Electronic)3540441808, 9783540441809
StatePublished - 2002
Externally publishedYes
Event10th Annual European Symposium on Algorithms, ESA 2002 - Rome, Italy
Duration: 17 Sep 200221 Sep 2002

Publication series

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


Conference10th Annual European Symposium on Algorithms, ESA 2002

Bibliographical note

Publisher Copyright:
© Springer-Verlag Berlin Heidelberg 2002.

ASJC Scopus subject areas

  • Theoretical Computer Science
  • General Computer Science


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