Theoretical Results on Single Machine Scheduling to Minimize the Number of Tardy Jobs with Periodic Maintenance

Feifeng Zheng (1) , Zhaojie Wang (1) , Ming Liu (2) , Yinfeng Xu (1) , Feng Chu (3)

1 Glorious Sun School of Business & Management
2 School of Economics and Management
3 IBISC - Informatique, BioInformatique, Systèmes Complexes

In the last two decades, maintenance as an essential method to prevent machine breakdown has achieved undoubted importance in process industries and manufacturing systems. With ever increasing high-quality products demand, the number of tool change or machine maintenance become quite remarkable. Besides, industry 4.0 supports manufacturing enterprises to explore more efficient and intelligent scheduling modes. Machine periodic maintenance has a significant impact on the scheduling of many manufacturing companies, it therefore has become one of the factors they must consider. Despite this, theoretical analysis for the machine scheduling problem with periodic maintenance has not received considerable critical attention in previous studies. Motivated by scheduling practice, this work revisits a single machine scheduling problem with periodic maintenance to minimize the number of tardy jobs. First, a polynomial-time solvable case is identified. Then we propose a dynamic programming algorithm to solve the general case. At last, the non-approximability is proven.

Keywords: Number of tardy jobs; Periodic maintenance; Scheduling; Single machine

Domains: Operations Research [math.OC]

Feifeng Zheng, Zhaojie Wang, Ming Liu, Yinfeng Xu, Feng Chu. Theoretical Results on Single Machine Scheduling to Minimize the Number of Tardy Jobs with Periodic Maintenance. 18th IEEE International Conference on Networking, Sensing and Control (ICNSC 2021), Dec 2021, Xiamen, China. pp.1-6, ⟨10.1109/ICNSC52481.2021.9702187⟩. ⟨hal-03628636⟩