School network reorganization under educational and spatial constraints using classical and quantum optimization

The paper introduces an optimization framework designed for school network reorganization, addressing challenges such as demographic shifts, accessibility, educational standards, and resource allocation. It utilizes a novel Integer Linear Programming formulation that integrates geographical, administrative, and educational criteria. The model's performance was evaluated using a synthetic benchmark generator and a real-world case study of the public school network in the Calabria region, Italy.

This research provides a systematic and quantifiable approach to strategic planning for public service infrastructure like school networks. Optimizing resource allocation and balancing multiple complex constraints can lead to more efficient and equitable service provision, which is critical for long-term institutional stability and societal development.

A novel Integer Linear Programming (ILP) formulation is proposed for school dimensioning decisions.

Forward consideration, not a verified fact.