Abstract

This paper tackles university course timetabling problems (UCTP) to find a (near) optimal solution (timetable) while satisfying hard constraints (essential requirements) and minimizing as much as possible the violations of the soft constrains (desirable requirements). In this study, we apply three algorithms, that is, Great Deluge, Simulated Annealing and Hill Climbing where the Round Robin algorithm is used as control strategy in choosing the algorithm to be employed at the current stage. The performance of the approach is tested with over two sets of benchmark datasets, that is, enrolment-based course timetabling and curriculum-based course timetabling (UD1) in comparison with a set of state-of-the-art methods from the literature. The experimental results show that the proposed approach is able to produce competitive results for the test UCTPs.

Key words: University course timetabling problem, round robin, great deluge, simulated annealing, hill climbing algorithm.