Personal Course Timetabling for University Students based on Genetic Algorithm

Abstract

This paper presents the optimization problem of generating a Personal University Course Timetabling (PUCT) for students from a Published Course Catalog (PCC) and an evolutionary approach to solve it. A PPC is a result of a manual or automatic process of a university course timetabling system to assign classes to times and spaces, considering constraints and preferences. However, independently of how the PPC was created, each university student faces particular constraints to select its timetable's courses. Due to the complexity of generating the timetable manually, several students were currently not considered a better option. In this paper, we present a method based on a genetic algorithm that considers the constraints and preferences presented by students at the Autonomous University of the State of Mexico for generating a PUCT. According to experimentation with a ground truth dataset, the proposed method not only shows better quantitative results than manual generation of the timetable but also shows good qualitative results based on the evaluation of the students.