用量子退火优化学校教师分配，实现公平高效排班。
Quantum Annealing for Staff Scheduling in Educational Environments
- 基于量子退火算法构建教师调度优化模型。
- 在真实数据上快速生成均衡的跨校区人员分配方案。
- 适合教育管理与量子优化交叉研究者参考。
我们研究了一个在多个校区和教育层级间协调协作人员的新颖人员分配问题。该问题源于意大利卡拉布里亚地区一所公立学校的实际案例，需在幼儿园、小学和中学之间分配教师，同时满足出勤、能力及公平性约束。为解决此问题，我们建立了一个优化模型，并探索了基于量子退火的求解方法。在真实世界数据上的计算实验表明，量子退火能在短时间内生成平衡的分配方案。这些结果验证了量子优化方法在教育调度中的实际可行性，也拓展至更广泛的复杂资源分配任务中。
原文摘要 · Abstract (English)
We address a novel staff allocation problem that arises in the organization of collaborators among multiple school sites and educational levels. The problem emerges from a real case study in a public school in Calabria, Italy, where staff members must be distributed across kindergartens, primary, and secondary schools under constraints of availability, competencies, and fairness. To tackle this problem, we develop an optimization model and investigate a solution approach based on quantum annealing. Our computational experiments on real-world data show that quantum annealing is capable of producing balanced assignments in short runtimes. These results provide evidence of the practical applicability of quantum optimization methods in educational scheduling and, more broadly, in complex resource allocation tasks.
Thank you to arXiv for use of its open access interoperability. PaperDance 不是 arXiv 官方产品；中文卡片由大模型生成，请以原文为准。