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 isdone manually, and many errors are discovered at the stages where a class is supposed to begin. A GeneticAlgorithm approach is proposed in this study to aid the timetable scheduling process. The main reason for this is thatthere are numerous factors and decisions to be taken, such as audience, subjects, lecturers, student group, and timeslot the need to take into account the difficulty of the classes they will take as well as their exam schedules andavailability. This approach compares the quality of different schedules to decide which one is the best based onfitness costs. Then, we may decide on better schedules utilizing crossover, mutation, and elitism choices. The use ofa genetic algorithm assists in the automatic generation of a timetable based on information. Human error and effortin the planning process are reduced by the genetic algorithm.