A heuristic optimization approach for a real-world university timetabling problem

In this study, the solution to the problem of automating the course timetabling used at the universities through the student affairs automation tool has been established by applying one of the heuristic optimization approaches, namely, the genetic algorithm method. The scheduling problem involves the optimal placing of tasks in time slots in accordance with designated constraints. Solving this problem through analytical methods at universities is becoming impossible due to the magnitude of the solution space and the wide range of constraints. Therefore, the genetic algorithm method, which is known to yield very good results for such problems, is used as a new approach, along with the investigation of parameters with the best results.