Abstract
This work addresses the timetabling problem faced by the Department of Statistical Sciences at the University of Cape Town each year for the honours course or fourth-year class. The approach taken by the department to design the timetable has been a manual one, which is time consuming. An automated approach is proposed in this work, based on mathematical programming models, with the aim to alleviate the burden caused by the manual approach to create such timetable. The proposed mixed integer programming model consists of three phases: The first phase involves the allocation of lecturers to modules based on preferences and expertise, the second phase consists of assigning modules to time slots, and the third phase involves the allocation of available venues for classes on the timetable. The model was applied to real data, collected from the department. The resulting timetabling solutions were compared to the 2022 timetable and validated by the course convenors.
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