An Investigation of a Genetic Algorithm and Sequential Local Search Approach for Curriculum-based Course Timetabling Problems

Curriculum-based course timetabling deals with the weekly assignment of a set of lectures for university courses to specific timeslots and rooms, where conflicts between courses are set according to curricula published by the university and not on the basis of enrolment data. The curriculum-based course timetabling is considered as the third track in the 2 International timetabling competition (ITC2007). The main reason for the wide interest in this formulation is because is capable of representing real world problems that often arise in higher educational institution. In this paper, we consider the same curriculum-based course timetabling problem as described in Gaspero et al. [1]. The solution of the problem is an assignment of a period (day and timeslot) and a room to all lectures of each course subject to a set of hard and soft constraints. There are four hard constraints considered as in Gaspero et al. [1]: • Lectures: All lectures of a course must be scheduled, and assigned to distinct periods. • Conflicts: All lectures of courses in the same curriculum or taught by the same teacher must be scheduled in different periods. • Availability: If the teacher of the course is not available to teach that course at a given period, then no lecture of the course can be scheduled at that period. • Room Occupation: Two lectures cannot be assigned in the same room in the same period.