A novel approach of genetic algorithm for solving university timetabling problems: A case study of Thai universities

University timetabling problems have been interested by many researchers for more than a decade. However, there is no appropriated solution or computation model available to solve these problems successfully. This is because of many different version of timetabling problems. In this paper, a noval approach of Genetic Algorithm (GA) for solving educational timetabling problem is proposed, including the constraints statements, the definition of a hierarchical structure for the fitness function, and the generalized genetic operators, which can be applied to matrices representing timetables. The paper focuses on lecturing timetables only, but not the examinational timetabling, and a Thai university is employed for a case study. The crossover rate and mutation rate were varied to conduct effective results and they shows that the given appropriate crossover rate of 50% and mutation rate of 50% is the best ratio to solve university timetabling problems which significantly can be able to control the maximum one period separation between subjects and decrease loading of computer resources for GA process.