用模糊逻辑优化兼职学生排班，兼顾工时与人力需求
Fuzzy Logic -- Based Scheduling System for Part-Time Workforce
- 基于遗传模糊系统建模排班决策
- 在缺员情况下仍能生成可行排班方案
- 适合高校兼职人员调度场景
本文探讨了将遗传模糊系统应用于大学兼职学生团队的排班优化。在已知员工偏好工作时长和可工作时段的前提下，模型综合考虑每周最大工时、在岗人数要求及偏好工时等因素，生成可行排班方案。算法基于辛辛那提大学学生提供的可用性数据进行训练与测试。结果表明，该算法能高效生成符合运营要求的排班，并在人手不足条件下表现出强鲁棒性。
原文摘要 · Abstract (English)
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.
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