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.

Why it matters

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.

Key insights

• A novel Integer Linear Programming (ILP) formulation is proposed for school dimensioning decisions.
• The ILP integrates geographical, administrative, and educational criteria for comprehensive school network planning.
• A synthetic benchmark generator was developed to test the model's scalability and computational performance.
• A real-world case study was conducted on the complete public school network of the Calabria region, Italy, using actual institutional and territorial data.

Source

arXiv — Computers and Society — https://arxiv.org/abs/2608.05427