Home > Archive > 2021 > Volume 11 Number 1 (Jan. 2021) >
IJMLC 2021 Vol.11(1): 40-47 ISSN: 2010-3700
DOI: 10.18178/ijmlc.2021.11.1.1012

A Survey of Computational Intelligence in Educational Timetabling

Kaixiang Zhu, Lily D Li, and Michael Li

Abstract—Timetabling problems have been widely studied, of which Educational Timetabling Problem (ETP) is the biggest section. Generally, ETP can be divided into three modules, namely, course timetabling, school timetabling, and examination timetabling. For solving ETP, many techniques have been developed including conventional algorithms and computational intelligence approaches. Several surveys have been conducted focusing on those methods. Some surveys target on particular categories; some tend to cover all types of approaches. However, there are lack of reviews specifically focusing on computational intelligence in ETP. Therefore, this paper aims at providing a reference of selecting a method for the applications of ETP by reviewing popular computational intelligent algorithms, such as meta-heuristics, hyper-heuristics, hybrid methods, fuzzy logic, and multi-agent systems. The application would be categorised and described into the three types of ETP respectively.

Index Terms—Computational intelligence, educational timetabling, heuristics, fuzzy logic.

The authors are with the School of Engineering and Technology, CQUniversity, Rockhampton, Q4702 Australia (e-mail: k.zhu@ cqu.edu.au, l.li@cqu.edu.edu, m.li@cqu.edu.edu).

[PDF]

Cite: Kaixiang Zhu, Lily D Li, and Michael Li, "A Survey of Computational Intelligence in Educational Timetabling," International Journal of Machine Learning and Computing vol. 11, no. 1, pp. 40-47, 2021.

Copyright © 2021 by the authors. This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).

General Information

  • ISSN: 2010-3700 (Online)
  • Abbreviated Title: Int. J. Mach. Learn. Comput.
  • Frequency: Bimonthly
  • DOI: 10.18178/IJMLC
  • Editor-in-Chief: Dr. Lin Huang
  • Executive Editor:  Ms. Cherry L. Chen
  • Abstracing/Indexing: Inspec (IET), Google Scholar, Crossref, ProQuest, Electronic Journals Library.
  • E-mail: ijmlc@ejournal.net


Article Metrics