Automated Lecture Timetable Generation Using Genetic Algorithm

Abstract

Making the perfect school schedule has been a major concern for both administrators and lecturers. Often, this is done manually, and  many errors are discovered at the stages where a class is supposed to begin. A Genetic Algorithm approach is proposed in this study to  aid the timetable scheduling process. The main reason for this is that there are numerous factors and decisions to be taken, such as  audience, subjects, lecturers, student group, and time slot the need to take into account the difficulty of the classes they will take as well  as their exam schedules and availability. This approach compares the quality of different schedules to decide which one is the best based  on fitness costs. Then, we may decide on better schedules utilizing crossover, mutation, and elitism choices. The use of a genetic  algorithm assists in the automatic generation of a timetable based on information. Human error and effort in the planning process are  reduced by the genetic algorithm.