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    Please use this identifier to cite or link to this item: http://ir.lib.ksu.edu.tw/handle/987654321/5700

    Title: A Novel Particle Swarm Optimization for Course Scheduling with Multiple Constraints
    Authors: Der-Fang Shiau
    Shih-Tang Lo (羅仕堂)
    Pi-Chung Hsu
    Keywords: Course scheduling
    Particle swarm optimization
    Local search
    Optimal satisfaction
    Date: 2009-09-25
    Issue Date: 2009-11-20 00:08:54 (UTC+8)
    Abstract: A novel meta-heuristic algorithm that is based on the principles of particle swarm optimization (PSO) is proposed for course scheduling problem. In the original PSO algorithm, particles search solutions in a continuous solution space. Since the solution space of the course scheduling problem is discrete, this study incorporates a local search method into the proposed PSO in order to explore a better solution improvement. The simulation results demonstrate that the proposed PSO in this study can significantly reduce the amount of computation required for course scheduling, and yields an optimal satisfaction of course scheduling for instructors and class scheduling arrangements.
    Relation: Der-Fang Shiau, Shih-Tang Lo, Pi-Chung Hsu, A Novel Particle Swarm Optimization for Course Scheduling with Multiple Constraints, The 2nd International Conference on Advanced Computer Science and Engineering (ICACTE 2009), Pages. 1723-1732, September 25 -27,2009
    Appears in Collections:[Graduate School and Department of Information Management] Proceedings

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