Abstract
DEVELOPMENT OF A PARTICLE SWARM OPTIMIZATION BASED CULTURAL ALGORITHM FOR SOLVING UNIVERSITY TIMETABLING PROBLEM
Alade O. M.*, Oyeleye C. A., Adedeji O. T., Omidiora E. O. and Oabiyisi S. O.
ABSTRACT
Timetabling problems are search problems in which courses must be arranged around a set of timeslots so that some constraints are satisfied. However, slow convergence speed and high computational complexity are one of drawbacks limiting the efficiency of the existing timetabling algorithms. In this paper, Particle Swarm Optimization based Cultural Algorithm (PSOCA) was developed for solving university lecture timetabling problems. Particle Swarm Optimization (PSO) algorithm was used in the population space of cultural algorithm in order to improve the convergence speed of the algorithm. Experimental results confirmed that PSOCA was able to improve the performance of PSO to solve timetabling problem with promising result.
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