HYBRID GENETIC-MEMETIC ALGORITHM FOR SOLVING THE PROBLEM OF THE SCHOOL TIMETABLE – A CASE STUDY WITH REAL DATA

The problem of the school timetable is a classic challenge of combinatorial optimization with a direct impact on the pedagogical organization. This work proposes a hybrid memetic architecture for the resolution of real instances of a Federal Educational Institution. The approach integrates the global exploration of a Genetic Algorithm with intensification by Lamarckian local search, using structural repair mechanisms to ensure the viability of the solutions. The results show significant evolution: the hybrid model reached an average fitness of 613.22, against 163.03 of the classical evolutionary approach. The traceability analysis revealed a balanced coexistence between the search fronts, ensuring robustness in the face of the stochasticity of the process. Qualitatively, the solutions promoted evident advances in the blocking of disciplines and in the elimination of idle windows for professors, validating the effectiveness of the strategy as a tool to support academic management.