University examination timetabling using a hybrid black hole algorithm

Abstract

University timetabling construction is a complicated task that universities worldwide encounter. This study developed a hybrid approach to produce a timetable solution for the university examination timetabling problem. Black Hole Algorithm (BHA), a population-based approach that mimics the black hole phenomenon, has recently been introduced in the literature and successfully applied in addressing various optimization problems. Although its effectiveness has been proven, there still exists inefficiency regarding the exploitation ability where BHA is poor in fine-tuning search region in reaching for good quality of the solution. Hence, a hybrid framework for university examination timetabling problem that is based on BHA and Hill Climbing local search is proposed (hybrid BHA). This hybridization aims to improve the exploitation ability of BHA in fine-tuning the promising search regions and convergence speed of the search process. A real-world university examination benchmark dataset has been used to evaluate the performance of hybrid BHA. The computational results demonstrate that hybrid BHA can generate competitive results and record the best results for three instances compared to the reference approaches and current best-known recorded in the literature. Besides, findings from the Friedman tests show that the hybrid BHA ranked second and third in comparison with hybrid and meta-heuristic approaches (a total of 27 approaches) reported in the literature, respectively.