Metaheuristic Mathematical Optimization in Crisis Management of Educational Systems

Abstract

The article explores metaheuristic mathematical optimization as an effective tool for crisis management of educational systems under conditions of uncertainty and limited resources. It is argued that traditional linear management approaches are insufficient for addressing complex challenges caused by economic, demographic, and institutional instability. The study highlights the potential of metaheuristic algorithms, including evolutionary, collective intelligence, and stochastic methods, to solve multi-criteria and nonlinear management problems in education. The results demonstrate that metaheuristic optimization supports adaptive decision-making, efficient resource allocation, structural transformation, and risk assessment, enhancing the adaptability, resilience, and sustainability of educational systems in crisis conditions.