Optimizing Academic Timetables Using Integer Linear Programming: A Case Study

An Integer Linear Programming (ILP) model was proposed to optimize academic timetables, with a focus on the School of Management at Western Galilee Academic College.The model was designed to address the dual challenges of course scheduling and faculty availability while incorporating a minor structural adjustment to enhance computational efficiency and accelerate convergence, particularly for large-scale problems.By employing this model, optimal scheduling solutions were generated within minutes, even in scenarios involving over 200 classes and 100 lecturers.The approach effectively minimizes planning time, identifies unavoidable scheduling conflicts, and highlights unschedulable classes due to constraint violations.Furthermore, the model provides actionable insights into staffing requirements, ensuring a comprehensive resource allocation strategy.Results from the application of the model during the 2023 winter semester demonstrated its capability to efficiently schedule 236 classes across multiple programs and instructional modalities.The method achieved adherence to predefined constraints, optimized the utilization of institutional resources, and enhanced overall scheduling efficiency.This case study underscores the potential of the proposed ILP framework to streamline academic timetabling processes, particularly in environments with diverse programmatic needs and complex resource interdependencies.The findings indicate that the model can be readily adapted to other academic institutions seeking to improve the effectiveness and precision of their scheduling systems.