University course timetable planning using hybrid particle swarm optimization
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 ch...
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| Format: | Book Section |
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American Chemical Society
2009
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| Summary: | 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. |
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