Date
Publisher
arXiv
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.
What is the application?
Who is the user?
Why use AI?
Study design
