Single-Machine Scheduling with Learning Effects and Maintenance: A Methodological Note on Some Polynomial-Time Solvable Cases. (8th August 2017)

• Record Type: Journal Article
• Authors: Ying, Kuo-Ching; Lu, Chung-Cheng; Lin, Shih-Wei; Chen, Jie-Ning
• Other Names: Mula Josefa Academic Editor.
• Is Part Of: Mathematical problems in engineering. Volume 2017(2017)
• Publication Date: 2017-08-08
• Subjects: Engineering mathematics -- Periodicals; 510.2462
• DOI: 10.1155/2017/7532174
• Languages: English
• ISSNs: 1024-123X

Abstract

Abstract : This work addresses four single-machine scheduling problems (SMSPs) with learning effects and variable maintenance activity. The processing times of the jobs are simultaneously determined by a decreasing function of their corresponding scheduled positions and the sum of the processing times of the already processed jobs. Maintenance activity must start before a deadline and its duration increases with the starting time of the maintenance activity. This work proposes a polynomial-time algorithm for optimally solving two SMSPs to minimize the total completion time and the total tardiness with a common due date.