Skip to main content

Research Repository

Advanced Search

An evolutionary non-Linear great deluge approach for solving course timetabling problems

Obit, Joe Henry; Ouelhadj, Djamila; Landa-Silva, Dario; Alfred, Rayner

Authors

Joe Henry Obit

Djamila Ouelhadj

Profile Image

DARIO LANDA SILVA DARIO.LANDASILVA@NOTTINGHAM.AC.UK
Professor of Computational Optimisation

Rayner Alfred



Abstract

The aim of this paper is to extend our non-linear great deluge algorithm into an evolutionary approach by incorporating a population and a mutation operator to solve the university course timetabling problems. This approach might be seen as a variation of memetic algorithms. The popularity of evolutionary computation approaches has increased and become an important technique in solving complex combinatorial optimisation problems. The proposed approach is an extension of a non-linear great deluge algorithm in which evolutionary operators are incorporated. First, we generate a population of feasible solutions using a tailored process that incorporates heuristics for graph colouring and assignment problems. The initialisation process is capable of producing feasible solutions even for large and most constrained problem instances. Then, the population of feasible timetables is subject to a steady-state evolutionary process that combines mutation and stochastic local search. We conducted experiments to evaluate the performance of the proposed algorithm and in particular, the contribution of the evolutionary operators. The results showed the effectiveness of the hybridisation between non-linear great deluge and evolutionary operators in solving university course timetabling problems.

Citation

Obit, J. H., Ouelhadj, D., Landa-Silva, D., & Alfred, R. (2012). An evolutionary non-Linear great deluge approach for solving course timetabling problems. International Journal of Computer Science Issues, 9(4),

Journal Article Type Article
Publication Date Jul 1, 2012
Deposit Date Mar 7, 2016
Publicly Available Date Mar 7, 2016
Journal International Journal of Computer Science Issues
Print ISSN 1694-0784
Electronic ISSN 1694-0814
Publisher IJCSI Press
Peer Reviewed Peer Reviewed
Volume 9
Issue 4
Keywords Great deluge, Evolutionary algorithms, Hybrid metaheuristics, Scheduling and timetabling
Public URL https://nottingham-repository.worktribe.com/output/1007223
Publisher URL http://www.ijcsi.org/articles/An-evolutionary-nonlinear-great-deluge-approach-for-solving-course-timetabling-problems.php
Additional Information Copyright 2012 International Journal of Computer Science Issues

Files





You might also like



Downloadable Citations