Exploring Selection Hyper-heuristics on University of Khartoum Course Timetabling Problem

Abstract

This paper defines a model for University of Khartoum course timetabling problem and explores selection optimization methods. A combination of three selection methods (Random Permutation, Simple Random and Greedy) and three move acceptance methods (Great Deluge, Simulated Annealing and Only Improving Moves) is measured to generate an optimal solution. Greedy-Simulated Annealing combination is found to show the best performance according to the metrics of minimum, maximum and average evaluation function within a short running time.