A hybrid ant algorithm for scheduling independent jobs in heterogeneous computing environments

G. Ritchie, J. Levine

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

55 Downloads (Pure)

Abstract

The efficient scheduling of independent computational jobs in a heterogeneous computing (HC) environment is an important problem in domains such as grid computing. Finding optimal schedules for such an environment is (in general) an
NP-hard problem, and so heuristic approaches must be used. In this paper we describe an ant colony optimisation (ACO) algorithm that, when combined with local and tabu search, can find shorter schedules on benchmark problems than other techniques found in the literature.
Original languageEnglish
Title of host publicationProceedings of the 23rd Workshop of the UK Planning and Scheduling Special Interest Group
Number of pages7
Publication statusPublished - 1 Dec 2004

Keywords

  • hybrid ant algorithm
  • heterogeneous computing environments
  • ant colony optimization

Fingerprint

Dive into the research topics of 'A hybrid ant algorithm for scheduling independent jobs in heterogeneous computing environments'. Together they form a unique fingerprint.

Cite this