Solving a Scholar Timetabling Problem Using a Genetic Algorithm - Study Case: Instituto Tecnologico De Zitacuaro

Abstract

The Scholar Timetabling Problem consists of fixing a sequence of meetings between lecturers, classrooms and schedule to a set of groups and courses in a given period of time, satisfying a set of different constraints, where each course, lecturer, classroom, and time have special features, this problem is known to be NP-hard. Given the impossibility to solve this problem optimally, traditional and metaheuristic methods have been proposed to provide near-optimal solutions. This paper shows the implementation of a Genetic Algorithm (GA) using a real coding to solve the Scholar Timetabling Problem. A naive representation for chromosomes in a population-based heuristic search leads to high probabilities of violation of the problem constraints. To convert solutions that violate constraints (unfeasible solutions) into ones that do not (feasible solutions), we propose a repair mechanism. Based on the proposed mechanism, we present a possible solution to the Scholar Timetabling Problem applied to a real school (Instituto Tecnologico de Zitacuaro). Here we present experimental results based on different types of GA configurations to solve this problem and present the best GA configuration to solve the study case.