AUTOMATED DISTRIBUTION OF TEACHING TASKS WITH MAXIMUM CONSTRAINT SATISFACTION: MATHEMATICAL MODELING OF A REAL CASE STUDY AT UNIVERSITY

University timetable generation is a complex NP-hard problem requiring robust decision-support tools for effective planning and management. While significant research exists in this domain, most efforts focus on automating time and space allocation, often overlooking the critical aspect of teaching task assignment. This study aims to bridge that gap by proposing a new mathematical model for the automatic distribution of teaching tasks, prioritizing the satisfaction of faculty preferences and the equitable balancing of workloads. Applied to a real case study in a university department, the results demonstrate that the automated system significantly outperforms manual methods. It provides a practical and scalable solution to enhance operational efficiency while saving substantial time and effort. By addressing a vital yet underexplored aspect of academic planning, this work contributes to the optimization of university management systems and highlights the benefits of integrating advanced methodologies in institutional processes.