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The Study of Genetic Algorithm Approach to Solving University Course Timetabling Problem

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Computational Science and Technology (ICCST 2017)

Part of the book series: Lecture Notes in Electrical Engineering ((LNEE,volume 488))

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Abstract

This research presents the metaheuristic strategy to solve educational timetabling problem. The metaheuristic described in this research highlight the role of Genetic Algorithm (GA) when the algorithm improves the quality of solution by performing genetic operators. Two datasets of university course timetabling are used whereby the datasets are obtained from Universiti Malaysia Sabah Labuan International Campus (UMSLIC). The research experiment is conducted by comparing the quality of solutions produced by Genetic Algorithm with other metaheuristics which have been done in the past researches. The experimental results suggest that Genetic Algorithm manages to produces good solutions in this domain although other algorithms are able to improve the quality of the solutions.

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Author information

Authors and Affiliations

  1. Universiti Malaysia Sabah, Labuan International Campus, W. P. Labuan, Malaysia

    Kuan Yik Junn & Joe Henry Obit

  2. Knowledge Technology Research Unit (KTRU), Faculty of Computing and Informatics, Universiti Malaysia Sabah (UMS), Jalan UMS, 88400, Kota Kinabalu, Sabah, Malaysia

    Rayner Alfred

Authors
  1. Kuan Yik Junn
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  2. Joe Henry Obit
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  3. Rayner Alfred
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Corresponding authors

Correspondence to Joe Henry Obit or Rayner Alfred .

Editor information

Editors and Affiliations

  1. Knowledge Technology Research Unit, Faculty of Computing and Informatics, Universiti Malaysia Sabah, Kota Kinabalu, Malaysia

    Rayner Alfred

  2. School of Information Science, Japan Advanced Institute of Science and Technology, Nomi, Ishikawa, Japan

    Hiroyuki Iida

  3. Faculty of Computing and Informatics, Universiti Malaysia Sabah, Kota Kinabalu, Malaysia

    Ag. Asri Ag. Ibrahim

  4. School of Information Science, Security and Networks Area, Japan Advanced Institute of Science and Technology, Nomi, Ishikawa, Japan

    Yuto Lim

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Junn, K.Y., Obit, J.H., Alfred, R. (2018). The Study of Genetic Algorithm Approach to Solving University Course Timetabling Problem. In: Alfred, R., Iida, H., Ag. Ibrahim, A., Lim, Y. (eds) Computational Science and Technology. ICCST 2017. Lecture Notes in Electrical Engineering, vol 488. Springer, Singapore. https://doi.org/10.1007/978-981-10-8276-4_43

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  • DOI: https://doi.org/10.1007/978-981-10-8276-4_43

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-10-8275-7

  • Online ISBN: 978-981-10-8276-4

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