Validating the Adaptability of a Developed General University Course Timetabling Model through Practical Implementation

Researchers have extensively studied the university course timetabling problem (UCTP) over the past decades, aiming to develop efficient, practical, and scalable scheduling that cater to the needs of academic institutions. This paper presents the implementation of a general Mixed-Integer Programming (MIP) model to solve UCTP using a dataset from an East Coast Malaysian public university. Building upon previous research that proposed a model with 24 constraints, this study aims to validate the original model to ensure its applicability and flexibility. Through the validation process, this study demonstrates how the model can be customized by selecting 13 relevant constraints based on East Coast Malaysian public university’s specific scheduling requirements, institutional policies, and academic preferences. This approach ensures that the model remains both realistic and adaptable to various scheduling contexts. Two different case studies with the same dataset are explored: case study 1 focuses on generating a timetable based on the university’s real timetabling requirements, while case study 2 integrates additional preferences and requests from lecturers and top university management to accommodate specific needs. The model is solved using AIMMS with the CPLEX 12.9 solver, ensuring feasible and optimal solutions. With minor modifications, this general model is adaptable and applicable to other universities' while addressing various institutional requirements and preferences.