AI Chat Paper
Note: Please note that the following content is generated by AMiner AI. SciOpen does not take any responsibility related to this content.
{{lang === 'zh_CN' ? '文章概述' : 'Summary'}}
{{lang === 'en_US' ? '中' : 'Eng'}}
Chat more with AI
PDF (225 KB)
Collect
Submit Manuscript AI Chat Paper
Show Outline
Outline
Show full outline
Hide outline
Outline
Show full outline
Hide outline
Research Article | Open Access

Online scheduling on a single machine with one restart for all jobs to minimize the weighted makespan

Xiaoxiao LiangLingfa Lu( )Xueke SunXue YuLili Zuo
School of Mathematics and Statistics, Zhengzhou University, Zhengzhou, Henan 450001, China
Show Author Information

Abstract

In this paper, we consider the online scheduling problem on a single machine to minimize the weighted makespan. In this problem, all jobs arrive over time and they are allowed to be restarted only once. For the general case when the processing times of all jobs are arbitrary, we show that there is no online algorithm with a competitive ratio of less than 2, which matches the lower bound of the problem without restart. That is, only one restart for all jobs is invalid for improving the competitive ratio in the general case. For the special case when all jobs have the same processing time, we present the best possible online algorithm with a competitive ratio of 1.4656, which improves the competitive ratio of 1 + 5 2 1.618 for the problem without restart.

CLC number: 90B35, 68M20, 68Q17

References

【1】
【1】
 
 
AIMS Mathematics
Pages 2518-2529

{{item.num}}

Comments on this article

Go to comment

< Back to all reports

Review Status: {{reviewData.commendedNum}} Commended , {{reviewData.revisionRequiredNum}} Revision Required , {{reviewData.notCommendedNum}} Not Commended Under Peer Review

Review Comment

Close
Close
Cite this article:
Liang X, Lu L, Sun X, et al. Online scheduling on a single machine with one restart for all jobs to minimize the weighted makespan. AIMS Mathematics, 2024, 9(1): 2518-2529. https://doi.org/10.3934/math.2024124

5

Views

0

Downloads

0

Crossref

0

Web of Science

0

Scopus

Received: 23 October 2023
Revised: 04 December 2023
Accepted: 13 December 2023
Published: 15 January 2024
©2024 the Author(s), licensee AIMS Press.

This is an open access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0)