Applications of Particle Swarm Optimization to a Practical University Timetabling Problem

In this paper, Particle Swarm Optimization algorithm and its combination with hill-climbing and Tabu Search algorithm are applied to a real-world university course timetabling problem. Experimental results taken from the tests on 14 practical data instances are shown, leading to the drawing of some conclusions.