Abstract
In university timetabling problems, course subjects must be assigned to a certain timeslots and rooms that satisfy preferred constraints. Timetabling problem is NP-completeness problem, which is a difficult problem with a lot of constraints to be solved and a huge search space needed to be explored if the problem size increases. As particle swarm optimization (PSO) has many successful applications in continuous optimization problems, the main contribution of this paper is to utilize PSO to solve the discrete problem of university course timetable (UCT). Experimental results confirm that PSO able to solve the timetabling problem with promising result.
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