Maximizing the minimum load for selfish agents

Leah Epstein, Rob Van Stee

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

Abstract

We consider the problem of maximizing the minimum load for machines that are controlled by selfish agents, who are only interested in maximizing their own profit. Unlike the classical load balancing problem, this problem has not been considered for selfish agents until now. For a constant number of machines, m, we show a monotone polynomial time approximation scheme (PTAS) with running time that is linear in the number of jobs. It uses a new technique for reducing the number of jobs while remaining close to the optimal solution. We also present an FPTAS for the classical problem, i.e., where no selfish agents are involved (the previous best result for this case was a PTAS) and use this to give a monotone FPTAS. Additionally, we give a monotone approximation algorithm with approximation ratio where can be chosen arbitrarily small and s i is the (real) speed of machine i. Finally we give improved results for two machines.

Original languageEnglish
Title of host publicationLATIN 2008
Subtitle of host publicationTheoretical Informatics - 8th Latin American Symposium, Proceedings
Pages264-275
Number of pages12
DOIs
StatePublished - 2008
Event8th Latin American TheoreticalINformatics Symposium, LATIN 2008 - Buzios, Brazil
Duration: 7 Apr 200811 Apr 2008

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume4957 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference8th Latin American TheoreticalINformatics Symposium, LATIN 2008
Country/TerritoryBrazil
CityBuzios
Period7/04/0811/04/08

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science (all)

Fingerprint

Dive into the research topics of 'Maximizing the minimum load for selfish agents'. Together they form a unique fingerprint.

Cite this