Combining the analytical hierarchy process and the genetic algorithm to solve the timetable problem
This addresses timetabling challenges for educational institutions by integrating teacher preferences, though it is incremental as it combines existing methods.
The paper tackled the school timetabling problem by incorporating teacher preferences and importance scores, using the analytic hierarchy process (AHP) to assign scores and a genetic algorithm (GA) to generate conflict-free schedules, resulting in solutions that satisfy most teacher preferences.
The main problems of school course timetabling are time, curriculum, and classrooms. In addition there are other problems that vary from one institution to another. This paper is intended to solve the problem of satisfying the teachers preferred schedule in a way that regards the importance of the teacher to the supervising institute, i.e. his score according to some criteria. Genetic algorithm (GA) has been presented as an elegant method in solving timetable problem (TTP) in order to produce solutions with no conflict. In this paper, we consider the analytic hierarchy process (AHP) to efficiently obtain a score for each teacher, and consequently produce a GA-based TTP solution that satisfies most of the teachers preferences.