Mathematical Optimization in Educational Management under Uncertainty and Crisis: Current Developments and Future Directions

Abstract

Educational systems operate under growing uncertainty and crisis conditions, where traditional deterministic management approaches lose effectiveness. This paper explores the shift toward resilience-oriented educational management based on mathematical optimization. It highlights the application of stochastic, robust, and fuzzy optimization methods to resource allocation, scheduling, and student retention. The study emphasizes the Smart Predict-then-Optimize paradigm, integrating machine learning and operations research through digital twins, data-driven and multi-criteria optimization. Key limitations related to data quality and ethical risks are also identified. Mathematical optimization is thus positioned as a strategic tool for sustaining educational systems in crisis environments