Solving course timetabling problem using Whale Optimization Algorithm

For academic institutions, creating a conflict-free course schedule or timetable is a difficult and time-consuming task. Timetabling is a well-known NP-hard combinatorial problem. Its complexity is due to the various constraints imposed on it in order to produce an effective course timetable. This paper describes the first use of the Whale Optimization Algorithm (WOA) to solve course timetabling problems. WOA was able to produce an efficient timetable with no penalty for constraints based on experiments performed on actual datasets. Due to the longer generation time when dealing with larger datasets, WOA was integrated with various mechanisms in the current work to improve its exploration and exploitation capability in order to solve course timetabling efficiently and was dubbed EWOA. The result shows that EWOA outperformed the classical WOA in time generation of the optimal timetable by 3x. Both methods were able to optimize the use of classroom resources by using the fewest number of rooms.