Access

You are not currently logged in.

Access your personal account or get JSTOR access through your library or other institution:

login

Log in to your personal account or through your institution.

A Combinatorial Approach to Dynamic Scheduling Problems

Zaw-Sing Su and Kenneth C. Sevcik
Operations Research
Vol. 26, No. 5, Operations Research/Computer Science Interface (Sep. - Oct., 1978), pp. 836-844
Published by: INFORMS
Stable URL: http://www.jstor.org/stable/170079
Page Count: 9
  • Download ($30.00)
  • Cite this Item
A Combinatorial Approach to Dynamic Scheduling Problems
Preview not available

Abstract

We introduce a combinatorial approach for studying multiple-processor scheduling problems that involve the preemptive scheduling of independent jobs. Unlike most combinatorial models used for studying scheduling problems, ours assumes that jobs arrive over time but that scheduling decisions must be made without knowledge of what jobs will arrive in the future. We seek dynamic algorithms that make scheduling decisions based on changing information. An algorithm is considered to be "optimal" only if it consistently produces schedules no worse than those produced by any omniscient algorithm that has exact knowledge of attributes of all jobs in advance. Measures of performance examined include the maxima and means of completion time, flow time, and lateness. "Optimal" algorithms are established in a few cases, while it is determined in other cases that such "optimal" algorithms require more information than the model provides.

Page Thumbnails

  • Thumbnail: Page 
836
    836
  • Thumbnail: Page 
837
    837
  • Thumbnail: Page 
838
    838
  • Thumbnail: Page 
839
    839
  • Thumbnail: Page 
840
    840
  • Thumbnail: Page 
841
    841
  • Thumbnail: Page 
842
    842
  • Thumbnail: Page 
843
    843
  • Thumbnail: Page 
844
    844