A distributed pool architecture for genetic algorithms

Gautam Roy, Hyunyoung Lee, Jennifer L. Welch, Yuan Zhao, Vijitashwa Pandey, Deborah Thurston

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

The genetic algorithm (GA) paradigm is a wellknown heuristic for solving many problems in science and engineering. As problem sizes increase, a natural question is how to exploit advances in distributed and parallel computing to speed up the execution of GAs. This paper proposes a new distributed architecture for GAs, based on distributed storage of the individuals in a persistent pool. Processors extract individuals from the pool in order to perform the computations and then insert the resulting individuals back into the pool. Unlike previously proposed approaches, the new approach is tailored for distributed systems in which processors are loosely coupled, failure-prone and can run at different speeds. Proofof- concept simulation results are presented indicating that the approach can deliver improved performance due to the distribution and tolerates a large fraction of crash failures.

Original languageEnglish (US)
Title of host publication2009 IEEE Congress on Evolutionary Computation, CEC 2009
Pages1177-1184
Number of pages8
DOIs
StatePublished - 2009
Event2009 IEEE Congress on Evolutionary Computation, CEC 2009 - Trondheim, Norway
Duration: May 18 2009May 21 2009

Publication series

Name2009 IEEE Congress on Evolutionary Computation, CEC 2009

Other

Other2009 IEEE Congress on Evolutionary Computation, CEC 2009
CountryNorway
CityTrondheim
Period5/18/095/21/09

ASJC Scopus subject areas

  • Artificial Intelligence
  • Computational Theory and Mathematics
  • Theoretical Computer Science

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