He, Yulan; Hui, Siu Cheung and Lai, Edmund Ming-Kit
(2005).
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| DOI (Digital Object Identifier) Link: | http://dx.doi.org/doi:10.1007/11496199_8 |
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| Google Scholar: | Look up in Google Scholar |
Abstract
University timetabling problem is a very common and seemingly simple, but yet very difficult problem to solve in practice. While solution definitely exists (evidenced by the fact that we do hold classes), an automated optimal schedule is very difficult to derive at present. There were successful attempts to address this problem using heuristics search methods. However, until now, university timetabling is still largely done by hand, because a typical university setting requires numerous customized complicated constraints that are difficult to model or automate. In addition, there is a problem of certain constraints being inviolable, while others are merely desirable. This paper intends to address the university timetabling problem that is highly constrained using Artificial Immune System. Empirical study on course timetabling for the School of Computer Engineering (SCE), Nanyang Technological University (NTU), Singapore as well as the benchmark dataset provided by the Metaheuristic Network shows that our proposed approach gives better results than those obtained using the Genetic Algorithm (GA).
| Item Type: | Conference Item |
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| Copyright Holders: | 2005 Springer-Verlag |
| ISSN: | 0302-9743 |
| Extra Information: | Published in:
Algorithmic Applications in Management: First International Conference, AAIM 2005, Xian, China, June 22-25, 2005, Proceedings / N. Megiddo, Y. Xu, and B. Zhu (Eds.) (LNCS 3521, pp. 55-65, ISBN 978-3-540-262244) |
| Academic Unit/Department: | Knowledge Media Institute |
| Interdisciplinary Research Centre: | Centre for Research in Computing (CRC) |
| Item ID: | 28564 |
| Depositing User: | Kay Dave |
| Date Deposited: | 18 May 2011 15:21 |
| Last Modified: | 26 Oct 2012 04:47 |
| URI: | http://oro.open.ac.uk/id/eprint/28564 |
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