Integrating ABC with genetic grouping for university course timetabling problem

Scheduling courses in university is an important matter in all academic institutes across the world. Scheduling courses, students, and class rooms without any crash is the main aim of university course time tabling problem. This problem is categorized as a NP-hard problem. The proposed algorithm is firstly based on a genetic grouping approach to generate feasible solutions. In the second step, an effective neighborhood structure which is embedded in an artificial bee colony is used to overcome the problem´s conflicts. Experimental results showed that proposed algorithm can obtain comparative results with the best known results of previous articles. The proposed algorithm has been performed on a standard and well known dataset named Socha. The results revealed the efficiency of proposed method. The suggested approach could find the best results on large scale instances of Socha dataset. Results on medium size of the dataset has been improved approaches in four cases out of five instances of dataset.