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.
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