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

2026-08-05

AI Summary

This study addresses the multifaceted challenges posed by demographic shifts, geographic accessibility, and institutional constraints by proposing an efficient approach to reconfigure public school networks for optimal allocation of public resources. We formulate an integer linear programming model that integrates geographic, administrative, and educational criteria, and—novel in this domain—recast the problem as a constrained quadratic model amenable to quantum computation. To facilitate evaluation across classical and hybrid quantum optimization solvers, we develop a scalable generator of synthetic test instances. Experiments on both synthetic data and real-world case studies from the Calabria region of Italy demonstrate that our method consistently yields structurally sound, equitable, and sustainable school consolidation plans under diverse policy scenarios, thereby confirming its robustness and potential as a decision-support tool for educational 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.

Problem

• school network reorganization
• educational planning
• spatial constraints
• resource allocation
• strategic planning

Innovation

• Integer Linear Programming
• Quantum Optimization
• School Network Reorganization
• Constrained Quadratic Model
• Spatial-Educational Planning