Generating University Course Timetable Using Genetic Algorithms and Local Search

In this paper we establish a new algorithm based on genetic algorithms (GA) and sequential local search to solve course timetabling problem. Universities are challenged to arise in number of complexity, their resources and events are becoming harder to schedule. Timetabling is a kind of problem in which events (classes, exams, courses, etc) have to be arranged into a number of timeslots such that conflicts in using a given set of resources are avoided. We perform preliminary experiments on standard benchmark course timetable problems and able to produce promising results.