A hybrid evolutionary approach to the university course timetabling problem

Combinations of evolutionary based approaches with local search have provided very good results for a variety of scheduling problems. This paper describes the development of such an algorithm for university course timetabling. This problem is concerned with the assignment of lectures to specific timeslots and rooms. For a solution to be feasible, a number of hard constraints must be satisfied. The quality of the solution is measured in terms of a penalty value which represents the degree to which various soft constraints are satisfied. This hybrid evolutionary approach is tested over established datasets and compared against state-of-the-art techniques from the literature. The results obtained confirm that the approach is able to produce solutions to the course timetabling problem which exhibit some of the lowest penalty values in the literature on these benchmark problems. It is therefore concluded that the hybrid evolutionary approach represents a particularly effective methodology for producing high quality solutions to the university course timetabling problem.

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