Artificial Orca Algorithm for Solving University Course Timetabling Issue

Timetabling problem for university courses (UCTP) is one of most traditional challenges that have been emphasized for a long time by many researches. This issue belong to NP-Hard problems, which are hard to solved with classical algorithms due to their complexity. Swarm intelligence become a trend to solve NP-hard problems, and also solve real life issues. This paper proposes a new based Artificial Orca Algorithm (AOA) solver for university courses timetabling problem. In order to evaluate our proposal, A series of are carried out on Ghardaia University Timetabling data, the performance of the proposed approach are evaluated and compared with other algorithms developed to solve the same problem. The results show a clear superiority of our proposal against the other in terms of execution time and result quality.