Optimization of timetabling structures based on evolutionary algorithms

Timetabling is one of the most important administrative activities that take place in academic institutions. Quite often it is done by hand or with the limited help of a simple administration system and usually involves taking the previous year’s timetable and modifying it so it will work for the next year.For the timetable, the recent growth in student numbers means that the timetable will be more constrained than ever. It is no longer good enough to use the previous year’s timetable. Every year a new timetable must be produced to take account of staff, student and course changes causing a necessarily large amount of administrative work.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 optimized genetic algorithm for solving a university weekly courses timetabling problem. Preliminary experimental results indicate that the algorithm is promising

Keywords:

Evolutionary Processing , Genetic Algorithm , Optimization , Timetabling , Crossover and Mutation operators