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A honey-bee mating optimization algorithm for educational timetabling problems

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  • Sabar, Nasser R.
  • Ayob, Masri
  • Kendall, Graham
  • Qu, Rong

Abstract

In this work, we propose a variant of the honey-bee mating optimization algorithm for solving educational timetabling problems. The honey-bee algorithm is a nature inspired algorithm which simulates the process of real honey-bees mating. The performance of the proposed algorithm is tested over two benchmark problems; exam (Carter’s un-capacitated datasets) and course (Socha datasets) timetabling problems. We chose these two datasets as they have been widely studied in the literature and we would also like to evaluate our algorithm across two different, yet related, domains. Results demonstrate that the performance of the honey-bee mating optimization algorithm is comparable with the results of other approaches in the scientific literature. Indeed, the proposed approach obtains best results compared with other approaches on some instances, indicating that the honey-bee mating optimization algorithm is a promising approach in solving educational timetabling problems.

Suggested Citation

  • Sabar, Nasser R. & Ayob, Masri & Kendall, Graham & Qu, Rong, 2012. "A honey-bee mating optimization algorithm for educational timetabling problems," European Journal of Operational Research, Elsevier, vol. 216(3), pages 533-543.
    • Handle: RePEc:eee:ejores:v:216:y:2012:i:3:p:533-543
    DOI: 10.1016/j.ejor.2011.08.006
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    References listed on IDEAS

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    1. Burke, Edmund Kieran & Petrovic, Sanja, 2002. "Recent research directions in automated timetabling," European Journal of Operational Research, Elsevier, vol. 140(2), pages 266-280, July.
    2. Burke, E.K. & Eckersley, A.J. & McCollum, B. & Petrovic, S. & Qu, R., 2010. "Hybrid variable neighbourhood approaches to university exam timetabling," European Journal of Operational Research, Elsevier, vol. 206(1), pages 46-53, October.
    3. Barry McCollum & Andrea Schaerf & Ben Paechter & Paul McMullan & Rhyd Lewis & Andrew J. Parkes & Luca Di Gaspero & Rong Qu & Edmund K. Burke, 2010. "Setting the Research Agenda in Automated Timetabling: The Second International Timetabling Competition," INFORMS Journal on Computing, INFORMS, vol. 22(1), pages 120-130, February.
    4. Burke, Edmund K. & McCollum, Barry & Meisels, Amnon & Petrovic, Sanja & Qu, Rong, 2007. "A graph-based hyper-heuristic for educational timetabling problems," European Journal of Operational Research, Elsevier, vol. 176(1), pages 177-192, January.
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    Cited by:

    1. Sabar, Nasser R. & Kendall, Graham, 2015. "An iterated local search with multiple perturbation operators and time varying perturbation strength for the aircraft landing problem," Omega, Elsevier, vol. 56(C), pages 88-98.
    2. Lan Nguyen-Ngoc & Quyet Nguyen-Huu & Guido De Roeck & Thanh Bui-Tien & Magd Abdel-Wahab, 2024. "Deep Neural Network and Evolved Optimization Algorithm for Damage Assessment in a Truss Bridge," Mathematics, MDPI, vol. 12(15), pages 1-25, July.
    3. Janmenjoy Nayak & Bighnaraj Naik, 2018. "A Novel Honey-Bees Mating Optimization Approach with Higher order Neural Network for Classification," Journal of Classification, Springer;The Classification Society, vol. 35(3), pages 511-548, October.
    4. Song, Kwonsik & Kim, Sooyoung & Park, Moonseo & Lee, Hyun-Soo, 2017. "Energy efficiency-based course timetabling for university buildings," Energy, Elsevier, vol. 139(C), pages 394-405.
    5. Goh, Say Leng & Kendall, Graham & Sabar, Nasser R., 2017. "Improved local search approaches to solve the post enrolment course timetabling problem," European Journal of Operational Research, Elsevier, vol. 261(1), pages 17-29.
    6. Say Leng Goh & Graham Kendall & Nasser R. Sabar & Salwani Abdullah, 2020. "An effective hybrid local search approach for the post enrolment course timetabling problem," OPSEARCH, Springer;Operational Research Society of India, vol. 57(4), pages 1131-1163, December.
    7. De Boeck, Liesje & Beliën, Jeroen & Creemers, Stefan, 2016. "A column generation approach for solving the examination-timetabling problemAuthor-Name: Woumans, Gert," European Journal of Operational Research, Elsevier, vol. 253(1), pages 178-194.
    8. Alejandro Cataldo & Juan-Carlos Ferrer & Jaime Miranda & Pablo A. Rey & Antoine Sauré, 2017. "An integer programming approach to curriculum-based examination timetabling," Annals of Operations Research, Springer, vol. 258(2), pages 369-393, November.
    9. Khaled Alomari & Osama Almarashdi & Ala Marashdh & Belal Zaqaibeh, 2020. "A New Optimization on Harmony Search Algorithm for Exam Timetabling System," Journal of Information & Knowledge Management (JIKM), World Scientific Publishing Co. Pte. Ltd., vol. 19(01), pages 1-13, March.

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