Abstract
We study shared multi-processor scheduling problem where each job can be executed on its private processor and simultaneously on one of many processors shared by all jobs in order to reduce the job’s completion time due to processing time overlap. The total weighted overlap of all jobs is to be maximized. The problem models subcontracting scheduling in supply chains and divisible load scheduling in computing. We show that synchronized schedules that complete each job at the same time on its private and shared processor, if any is actually used by the job, include optimal schedules. We prove that the problem is NP-hard in the strong sense for jobs with arbitrary weights, and we give an efficient, polynomial-time algorithm for the problem with equal weights.
Citations
-
8
CrossRef
-
0
Web of Science
-
7
Scopus
Authors (2)
Cite as
Full text
full text is not available in portal
Keywords
Details
- Category:
- Articles
- Type:
- artykuł w czasopiśmie wyróżnionym w JCR
- Published in:
-
EUROPEAN JOURNAL OF OPERATIONAL RESEARCH
no. 261,
edition 2,
pages 503 - 514,
ISSN: 0377-2217 - Language:
- English
- Publication year:
- 2017
- Bibliographic description:
- Dereniowski D., Kubiak W.: Shared multi-processor scheduling// EUROPEAN JOURNAL OF OPERATIONAL RESEARCH. -Vol. 261, iss. 2 (2017), s.503-514
- DOI:
- Digital Object Identifier (open in new tab) 10.1016/j.ejor.2017.03.002
- Verified by:
- Gdańsk University of Technology
seen 119 times