Designing an Automated Timetable for University Courses Using Genetic Algorithms

Abstract

Designing timetables, for example course timetables in an institute, is one of the most complicated and time-consuming challenges for personnel. Automating it, not only can help the personnel to manage their work better, but also can be considered as a desired sample to assess the ways of planning and to tackle the constraint satisfaction in artificial intelligence. In this paper, genetic algorithms are primarily studied and then it is applied for optimization of an imaginary faculty course timetable. The new designed algorithm is based on keeping the better chromosomes of the population and employing genetic operators on the others in order to improve the overall quality of genes. Some other amendments are also carried out to develop a more capable genetic algorithm for TT applications, compared to the standard one. According to the tests, the new GA algorithm will be more successful in generating high fidelity TTs which do not break any hard constraint. The proposed ideas, in this approach are applicable in other similar situations.