The single machine scheduling problem with bio-mathematical fatigue constraints.
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| Title: | The single machine scheduling problem with bio-mathematical fatigue constraints. |
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| Authors: | Wang, Zhaotong1 (AUTHOR), Deng, Tianhu1 (AUTHOR) deng13@tsinghua.edu.cn, Meng, Yize2 (AUTHOR), Guo, Han3 (AUTHOR) |
| Source: | International Journal of Production Research. Aug2025, Vol. 63 Issue 15, p5649-5670. 22p. |
| Subjects: | Fatigue (Physiology), Scheduling, Production management (Manufacturing), Safety, Biomathematics, Manufacturing industries, Linear programming, Heuristic |
| Abstract: | Despite the adverse impacts of occupational fatigue such as accidents and injuries in the manufacturing industry, it has not been systematically examined in the literature on production scheduling. In this paper, we integrate the classic bio-mathematical fatigue prediction model from the brain science literature into the simple single machine scheduling problem with sequence-dependent setup times. Then, we formulate the problem as a mixed-integer linear programming model and propose an adaptive large neighborhood search heuristic. The effectiveness of the heuristic is numerically validated through real cases. Finally, we argue that considering bio-mathematical fatigue prediction can lead to safer production schedules, notably reducing the fatigue working hours in our real case. [ABSTRACT FROM AUTHOR] |
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| Database: | Engineering Source |
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| Abstract: | Despite the adverse impacts of occupational fatigue such as accidents and injuries in the manufacturing industry, it has not been systematically examined in the literature on production scheduling. In this paper, we integrate the classic bio-mathematical fatigue prediction model from the brain science literature into the simple single machine scheduling problem with sequence-dependent setup times. Then, we formulate the problem as a mixed-integer linear programming model and propose an adaptive large neighborhood search heuristic. The effectiveness of the heuristic is numerically validated through real cases. Finally, we argue that considering bio-mathematical fatigue prediction can lead to safer production schedules, notably reducing the fatigue working hours in our real case. [ABSTRACT FROM AUTHOR] |
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| ISSN: | 00207543 |
| DOI: | 10.1080/00207543.2025.2459290 |
