Joe Henry Obit
An evolutionary non-Linear great deluge approach for solving course timetabling problems
Obit, Joe Henry; Ouelhadj, Djamila; Landa-Silva, Dario; Alfred, Rayner
Authors
Djamila Ouelhadj
Professor 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
dls_ijcsi2012.pdf
(1.3 Mb)
PDF
You might also like
Local-global methods for generalised solar irradiance forecasting
(2024)
Journal Article
UAV Path Planning for Area Coverage and Energy Consumption in Oil and Gas Exploration Environment
(2023)
Presentation / Conference Contribution
Evolving Deep CNN-LSTMs for Inventory Time Series Prediction
(2019)
Presentation / Conference Contribution
Downloadable Citations
About Repository@Nottingham
Administrator e-mail: discovery-access-systems@nottingham.ac.uk
This application uses the following open-source libraries:
SheetJS Community Edition
Apache License Version 2.0 (http://www.apache.org/licenses/)
PDF.js
Apache License Version 2.0 (http://www.apache.org/licenses/)
Font Awesome
SIL OFL 1.1 (http://scripts.sil.org/OFL)
MIT License (http://opensource.org/licenses/mit-license.html)
CC BY 3.0 ( http://creativecommons.org/licenses/by/3.0/)
Powered by Worktribe © 2025
Advanced Search