University course timetable planning using hybrid particle swarm optimization

• Main Authors: Ho, Irene Sheau Fen, Deris, Safaai, Mohd. Hashim, Siti Zaiton
• Format: Book Section
• Published: American Chemical Society 2009
• Subjects: QA75 Electronic computers. Computer science
• Online Access: http://eprints.utm.my/id/eprint/13169/; http://dx.doi.org/10.1145/1543834.1543868

University Course Timetabling (UCT) is a complex problem and cannot be dealt with using only a few general principles. The complicated relationships between time periods, subjects and classrooms make it difficult to obtain feasible solution. Thus,finding feasible solution for UCT is a continually challenging problem. This paper presents a hybrid particle swarm optimization algorithm to solve University Course Timetabling Problem(UCTP). The proposed approach (hybrid particle swarm optimization with constraint-based reasoning) uses particle swarm optimization to find the position of room and timeslot using suitable objective function and the constraints-based reasoning has been used to search for the best preference value based on the student capacity for each lesson in a reasonable computing time. The proposed algorithm has been validated with other hybrid algorithms (hybrid particle swarm optimization with local search and hybrid genetic algorithm with constraint-based reasoning) using a real world data from Faculty of Science at Ibb University - Yemen and results show that the proposed algorithm can provide more promising solution.