Randomized approximation schemes for minimizing the weighted makespan on identical parallel machines
Ruiqing Sun ()
Additional contact information
Ruiqing Sun: Yunnan University
Journal of Combinatorial Optimization, 2024, vol. 47, issue 3, No 5, 16 pages
Abstract:
Abstract In this paper, we discuss scheduling problems with m identical machines and n jobs where each job has to be assigned to some machine. The objective is to minimize the weighted makespan of jobs, i.e., the maximum weighted completion time of jobs. This scheduling problem is a generalization of minimizing the makespan on parallel machine scheduling problem. We present a ( $$2-\frac{1}{m}$$ 2 - 1 m )-approximation algorithm and a randomized efficient polynomial time approximation scheme (EPTAS) for the problem. We also design a randomized fully polynomial time approximation scheme (FPTAS) for the special case when the number of machines is fixed.
Keywords: Scheduling; Weighted makespan; Approximation algorithm; Efficient polynomial time approximation scheme; Fully polynomial time approximation scheme (search for similar items in EconPapers)
Date: 2024
References: View references in EconPapers View complete reference list from CitEc
Citations:
Downloads: (external link)
http://link.springer.com/10.1007/s10878-024-01118-w Abstract (text/html)
Access to the full text of the articles in this series is restricted.
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:spr:jcomop:v:47:y:2024:i:3:d:10.1007_s10878-024-01118-w
Ordering information: This journal article can be ordered from
https://www.springer.com/journal/10878
DOI: 10.1007/s10878-024-01118-w
Access Statistics for this article
Journal of Combinatorial Optimization is currently edited by Thai, My T.
More articles in Journal of Combinatorial Optimization from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().