A genetic algorithm for a university weekly courses timetabling problem

The timetabling problem is concerned with the allocation, subject to constraints, of given resources to objects in space and time in such a way as to satisfy as nearly as possible a set of desirable objectives. This problem is known to be NP-complete and as such only combinatorial optimization methods can guarantee an optimal timetable. In this paper we propose a sector-based genetic algorithm for solving a university weekly courses timetabling problem. Preliminary experimental results indicate that the algorithm is promising.