Single-Machine Scheduling with Learning Effects and Maintenance: A Methodological Note on Some Polynomial-Time Solvable Cases

Kuo-Ching Ying, Chung-Cheng Lu, Shih-Wei Lin and Jie-Ning Chen

Mathematical Problems in Engineering, 2017, vol. 2017, 1-6

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.

Date: 2017
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Persistent link: https://EconPapers.repec.org/RePEc:hin:jnlmpe:7532174

DOI: 10.1155/2017/7532174

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