Solving University Course Timetabling Problem Using Memetic Algorithms and Rule-based Approaches

Abstract

In this paper, we present the optimization of a university course timetabling (UCT) using memetic algorithms and rule-based approaches. The method will optimize the course timetables adjustment which includes: lecturers, classrooms, time slots, and courses in one week of activity for one semester. Some hard and soft constraints are also applied to test the performance of the algorithm. The results of the experimental tests prove that memetic algorithms combined with some ruled-based approaches can be used optimally for UCT. As for the occurrence of multiple violations of soft constraints, it can be handled by manually correcting the course timetables that have been generated. From some experiments conducted also known that the system has been able to produce satisfactory course timetables, which is to adjust the distribution of timetables needs between lecturers, classrooms, time slots, and courses.