Fuzzy Logic -- Based Scheduling System for Part-Time Workforce
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arXiv
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| Hauptverfasser: | , |
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| Format: | Preprint |
| Veröffentlicht: |
2025
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| _version_ | 1866908337177624576 |
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| author | Nguyen, Tri Cohen, Kelly |
| author_facet | Nguyen, Tri Cohen, Kelly |
| contents | This paper explores the application of genetic fuzzy systems to efficiently generate schedules for a team of part-time student workers at a university. Given the preferred number of working hours and availability of employees, our model generates feasible solutions considering various factors, such as maximum weekly hours, required number of workers on duty, and the preferred number of working hours. The algorithm is trained and tested with availability data collected from students at the University of Cincinnati. The results demonstrate the algorithm's efficiency in producing schedules that meet operational criteria and its robustness in understaffed conditions. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2504_17805 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Fuzzy Logic -- Based Scheduling System for Part-Time Workforce Nguyen, Tri Cohen, Kelly Neural and Evolutionary Computing Artificial Intelligence This paper explores the application of genetic fuzzy systems to efficiently generate schedules for a team of part-time student workers at a university. Given the preferred number of working hours and availability of employees, our model generates feasible solutions considering various factors, such as maximum weekly hours, required number of workers on duty, and the preferred number of working hours. The algorithm is trained and tested with availability data collected from students at the University of Cincinnati. The results demonstrate the algorithm's efficiency in producing schedules that meet operational criteria and its robustness in understaffed conditions. |
| title | Fuzzy Logic -- Based Scheduling System for Part-Time Workforce |
| topic | Neural and Evolutionary Computing Artificial Intelligence |
| url | https://arxiv.org/abs/2504.17805 |