A Robust Single-Machine Scheduling Problem with Two Job Parameter Scenarios

Gang Xuan, Win-Chin Lin, Shuenn-Ren Cheng, Wei-Lun Shen, Po-An Pan, Chih-Ling Kuo and Chin-Chia Wu
Additional contact information
Gang Xuan: School of Administration Business, Zhejiang University of Finance and Economics Dongfang College, Haining 314408, China
Win-Chin Lin: Department of Statistics, Feng Chia University, Taichung City 40724, Taiwan
Shuenn-Ren Cheng: Department of E-Sport Technology Management, Cheng Shiu University, Kaohsiung City 83347, Taiwan
Wei-Lun Shen: Department of Statistics, Feng Chia University, Taichung City 40724, Taiwan
Po-An Pan: Department of Statistics, Feng Chia University, Taichung City 40724, Taiwan
Chih-Ling Kuo: Department of Food and Beverage Management, Cheng Shiu University, Kaohsiung City 83347, Taiwan
Chin-Chia Wu: Department of Statistics, Feng Chia University, Taichung City 40724, Taiwan

Mathematics, 2022, vol. 10, issue 13, 1-17

Abstract: In many real-world environments, machine breakdowns or worker performance instabilities cause uncertainty in job processing times, while working environment changes or transportation delays will postpone finished production for customers. The factors that impact the task processing times and/or deadlines vary. In view of the uncertainty, job processing times and/or job due dates cannot be fixed numbers. Inspired by this fact, we introduce a scenario-dependent processing time and due date concept into a single-machine environment. The measurement minimizes the total job tardiness in the worst case. The same problem without the presence of processing time uncertainty has been an NP-hard problem. First, to solve this difficult model, an exact method, including a lower bound and some dominance properties, is proposed. Next, three scenario-dependent heuristic algorithms are proposed. Additionally, a population-based iterated greedy algorithm is proposed in the hope of increasing the diversity of the solutions. The results of all related algorithms are determined and compared using the appropriate statistical tools.

Keywords: iterated greedy; scheduling; total tardiness; scenario-dependent (search for similar items in EconPapers)
JEL-codes: C (search for similar items in EconPapers)
Date: 2022
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

Downloads: (external link)
https://www.mdpi.com/2227-7390/10/13/2176/pdf (application/pdf)
https://www.mdpi.com/2227-7390/10/13/2176/ (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:10:y:2022:i:13:p:2176-:d:845099

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 ().