Quantum Annealing for Staff Scheduling in Educational Environments
This addresses a specific scheduling problem for educational administrators, but it is incremental as it applies an existing quantum method to a new domain.
The paper tackled a staff allocation problem across multiple school sites and educational levels by developing an optimization model and using quantum annealing, showing it produces balanced assignments with short runtimes in real-world data.
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.