A novel genetic algorithm technique for solving university course timetabling problems

Abstract

In this paper, as a machine learning or system modeling, a novel genetic algorithm (GA) approach for solving university course timetabling problem is presented. The designed timetabling is free of any hard constraint violations and satisfies most of the soft constraints as much as realistically possible. When compared with other methods, the followings were the advantages: 1) the number of soft constraint violations is less, 2) the use of external rooms is eliminated, and 3) the number of instructors' overload is less.