Two-Agent Pareto-Scheduling of Minimizing Total Weighted Completion Time and Total Weighted Late Work

Yuan Zhang, Zhichao Geng and Jinjiang Yuan
Additional contact information
Yuan Zhang: School of Mathematics and Statistics, Zhengzhou University, Zhengzhou 450001, China
Zhichao Geng: School of Mathematics and Statistics, Zhengzhou University, Zhengzhou 450001, China
Jinjiang Yuan: School of Mathematics and Statistics, Zhengzhou University, Zhengzhou 450001, China

Mathematics, 2020, vol. 8, issue 11, 1-17

Abstract: We investigate the Pareto-scheduling problem with two competing agents on a single machine to minimize the total weighted completion time of agent A ’s jobs and the total weighted late work of agent B ’s jobs, the B -jobs having a common due date. Since this problem is known to be NP-hard, we present two pseudo-polynomial-time exact algorithms to generate the Pareto frontier and an approximation algorithm to generate a ( 1 + ? ) -approximate Pareto frontier. In addition, some numerical tests are undertaken to evaluate the effectiveness of our algorithms.

Keywords: scheduling; two agents; pareto frontier; approximation algorithms (search for similar items in EconPapers)
JEL-codes: C (search for similar items in EconPapers)
Date: 2020
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

Downloads: (external link)
https://www.mdpi.com/2227-7390/8/11/2070/pdf (application/pdf)
https://www.mdpi.com/2227-7390/8/11/2070/ (text/html)

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:gam:jmathe:v:8:y:2020:i:11:p:2070-:d:448030

Access Statistics for this article

Mathematics is currently edited by Ms. Emma He

More articles in Mathematics from MDPI
Bibliographic data for series maintained by MDPI Indexing Manager ().