| Summary: | 碩士 === 國立臺北教育大學 === 資訊科學系碩士班 === 98 === Scheduling and course planning in any kind of school and university require tremendous efforts to fulfill many constraints without conflicts. In course timetabling, the scheduler determines the day and time to offer each section of each course. The objective is normally to find a course timetable that minimizes the number of (potential) student conflicts while respecting teacher, room and equipment restrictions.
The problem of developing schedules for course timetabling has been modeled as a particle swarm group optimization problem. To avoid cluster searching procedure falls into a local optimum and improves optimum local area search ability, Particle Swarm Optimization with Random Particles and Fine-Tuning Mechanism, PSO-RPFT, was proposed in the thesis with dynamic user constraining rules. The simulation of PSO-RPFT has shown high level satisfactory results in a large range of solutions with finite search particles.
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