Quantum Annealing for Staff Scheduling in Educational Environments

Ciacco, Alessia, Guerriero, Francesca, Osaba, Eneko

arXiv.org Artificial Intelligence 

Abstract--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. T o 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. In recent years, the Italian school system has experienced a significant increase in the complexity of its organizational processes. Today, schools operate in a highly regulated environment, characterized by increasingly stringent legal constraints, often deriving from both national laws and regional directives, as well as by a constant focus on cost efficiency and the quality of services provided.

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