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This paper introduces an optimization framework for school network reorganization that integrates geographical, administrative, and educational criteria through a novel Integer Linear Programming formulation. By applying this framework to both synthetic benchmarks and a real-world case study in Calabria, Italy, the authors demonstrate its effectiveness in identifying optimal school aggregation plans while maintaining the educational system's structural integrity. Additionally, the model's reformulation as a constrained quadratic model and its implementation in a hybrid quantum optimization environment showcase its adaptability to emerging quantum technologies, emphasizing its potential as a decision-support tool for sustainable school planning.
Achieving optimal school network reorganization while balancing educational and spatial constraints could revolutionize resource allocation in public education systems.
School network reorganization is a strategic planning problem that requires balancing demographic trends, territorial accessibility, educational requirements, and institutional constraints while ensuring an efficient allocation of public resources. This paper proposes an optimization framework for school dimensioning decisions based on a novel Integer Linear Programming formulation integrating geographical, administrative, and educational criteria. A synthetic benchmark generator is introduced to evaluate the scalability and computational performance of the model on artificial instances, while a real-world case study involving the complete public school network of the Calabria region (Italy) is conducted using actual institutional, territorial, and demographic data. The proposed approach effectively identifies optimal aggregation plans under different policy scenarios while preserving the structural characteristics of the educational system. Furthermore, the model is reformulated as a constrained quadratic model and implemented within a hybrid quantum optimization environment, demonstrating its compatibility with emerging quantum technologies. The results highlight the robustness of the proposed methodology and its potential as a decision-support tool for sustainable and equitable school network planning.