A New Genetic Approach for Course Timetabling Problem

Abstract

Educational timetabling problems, such as university exam timetabling, university course timetabling and school timetabling, are combinatorial optimization problems that require the allocation of a set of resources to meet some objectives, based a specified set of constraints [1]. The university course timetabling is often finalized in stages, the data changes making it impossible to return to a certain previous version. As each version is announced to the community, it is desirable to have a robust initial schedule, i.e. one that can be repaired with a limited number of changes, being a version that, through modifications, will lead to a new solution whose quality is better [2]. In this article we used genetic algorithms that, based on heuristics, generate an initial population of good quality schedules. Within the described algorithm we calculate a fitness function that takes into account the windows between teaching activities, but also takes into account the efficient use of space, but also a maximum number of lectures per day. To test the algorithm we used a set of real data from the Faculty of Economics and Public Administration, belonging to "Ştefan cel Mare" University from Suceava, Romania.

Keywords

• timetabling
• genetic algorithm
• chromosomes
• generations
• greedy
• neh
• job shop scheduling