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This paper applies hybrid quantum optimization techniques to solve complex school network reorganization problems, demonstrating the practical utility of emerging quantum algorithms in constrained quadratic models. While the core application addresses educational logistics, the study's primary contribution lies in validating quantum-compatible frameworks for large-scale integer programming and resource allocation. It serves as a relevant case study for researchers exploring near-term applications of quantum computing beyond physics simulations.
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School network reorganization under educational and spatial constraints using classical and quantum optimization

arXiv2 min de cititArticolul și perspectiva sunt în engleză.

arXiv:2608.05427v1 Announce Type: cross Abstract: 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.

Abstract: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.

Computers and Society (cs.CY); Quantum Physics (quant-ph)

arXiv:2608.05427 [cs.CY]

(or arXiv:2608.05427v1 [cs.CY] for this version)

https://doi.org/10.48550/arXiv.2608.05427 Focus to learn more arXiv-issued DOI via DataCite (pending registration)

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