Approximation algorithms for multi-agent scheduling to minimize total weighted completion time

Authors

Kangbok Lee, Leonard N. Stern School of Business
Byung Cheon Choi, Leonard N. Stern School of Business
Joseph Y.T. Leung, Department of Computer Science
Michael L. Pinedo, Leonard N. Stern School of Business

Document Type

Article

Publication Date

7-31-2009

Abstract

We consider a multi-agent scheduling problem on a single machine in which each agent is responsible for his own set of jobs and wishes to minimize the total weighted completion time of his own set of jobs. It is known that the unweighted problem with two agents is NP-hard in the ordinary sense. For this case, we can reduce our problem to a Multi-Objective Shortest-Path (MOSP) problem and this reduction leads to several results including Fully Polynomial Time Approximation Schemes (FPTAS). We also provide an efficient approximation algorithm with a reasonably good worst-case ratio. © 2009 Elsevier B.V. All rights reserved.

Identifier

67649342188 (Scopus)

Publication Title

Information Processing Letters

External Full Text Location

https://doi.org/10.1016/j.ipl.2009.04.018

ISSN

00200190

First Page

913

Last Page

917

Issue

16

Volume

109

Grant

DMI-0555999

Fund Ref

National Science Foundation

Recommended Citation

Lee, Kangbok; Choi, Byung Cheon; Leung, Joseph Y.T.; and Pinedo, Michael L., "Approximation algorithms for multi-agent scheduling to minimize total weighted completion time" (2009). Faculty Publications. 12007.
https://digitalcommons.njit.edu/fac_pubs/12007