Abstract

There has been a large amount of research into the development of automated systems for creating school timetables. Methodologies such as constraint programming, simulated annealing, and Tabu search have been applied to many school timetabling problems. The research presented in this paper forms part of work-in-progress aimed at evaluating genetic algorithms as a means of solving the school timetabling problem. In previous work a genetic algorithm was successful applied to solving the school timetabling problem with hard constraints. The paper presents our first attempt at extending this system to cater for school timetabling problems with both hard and soft constraints.

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