The university course timetabling problem involves assigning a given number of events into a limited number of timeslots and rooms under a given set of constraints; the objective is to satisfy the hard constraints (essential requirements) and minimize the violation of soft constraints (desirable requirements). In this study we employed a Dual-sequence Simulated Annealing (DSA) algorithm as an improvement algorithm. The Round Robin (RR) algorithm is used to control the selection of neighbourhood structures within DSA. The performance of our approach is tested over eleven benchmark datasets. Experimental results show that our approach is able to generate competitive results when compared with other state-of-the-art techniques.