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A survey of school timetabling research

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  • Nelishia Pillay

Abstract

Although there has been a fair amount of research in the area of school timetabling, this domain has not developed as well as other fields of educational timetabling such as university course and examination timetabling. This can possibly be attributed to the fact that the studies in this domain have generally been conducted in isolation of each other and have addressed different school timetabling problems. Furthermore, there have been no comparative studies on the success of different methodologies on a variety of school timetabling problems. As a way forward this paper provides an overview of the research conducted in this domain, details of problem sets which are publicly available and proposes areas for further research in school timetabling. Copyright Springer Science+Business Media New York 2014

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  • Nelishia Pillay, 2014. "A survey of school timetabling research," Annals of Operations Research, Springer, vol. 218(1), pages 261-293, July.
    • Handle: RePEc:spr:annopr:v:218:y:2014:i:1:p:261-293:10.1007/s10479-013-1321-8
    DOI: 10.1007/s10479-013-1321-8
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    2. Esmaeilbeigi, Rasul & Mak-Hau, Vicky & Yearwood, John & Nguyen, Vivian, 2022. "The multiphase course timetabling problem," European Journal of Operational Research, Elsevier, vol. 300(3), pages 1098-1119.
    3. Dorneles, Árton P. & de Araújo, Olinto C.B. & Buriol, Luciana S., 2017. "A column generation approach to high school timetabling modeled as a multicommodity flow problem," European Journal of Operational Research, Elsevier, vol. 256(3), pages 685-695.
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    5. Saviniec, Landir & Santos, Maristela O. & Costa, Alysson M., 2018. "Parallel local search algorithms for high school timetabling problems," European Journal of Operational Research, Elsevier, vol. 265(1), pages 81-98.
    6. Nossack, Jenny, 2022. "Therapy scheduling and therapy planning at hospitals," Omega, Elsevier, vol. 109(C).
    7. Johnes, Jill, 2015. "Operational Research in education," European Journal of Operational Research, Elsevier, vol. 243(3), pages 683-696.
    8. Aslan, Ayse & Ursavas, Evrim & Romeijnders, Ward, 2023. "A Precedence Constrained Knapsack Problem with Uncertain Item Weights for Personalized Learning Systems," Omega, Elsevier, vol. 115(C).
    9. Oliver Czibula & Hanyu Gu & Aaron Russell & Yakov Zinder, 2017. "A multi-stage IP-based heuristic for class timetabling and trainer rostering," Annals of Operations Research, Springer, vol. 252(2), pages 305-333, May.
    10. Cristian D. Palma & Patrick Bornhardt, 2020. "Considering Section Balance in an Integer Optimization Model for the Curriculum-Based Course Timetabling Problem," Mathematics, MDPI, vol. 8(10), pages 1-12, October.
    11. Ceschia, Sara & Di Gaspero, Luca & Schaerf, Andrea, 2023. "Educational timetabling: Problems, benchmarks, and state-of-the-art results," European Journal of Operational Research, Elsevier, vol. 308(1), pages 1-18.
    12. Gülcü, Ayla & Akkan, Can, 2020. "Robust university course timetabling problem subject to single and multiple disruptions," European Journal of Operational Research, Elsevier, vol. 283(2), pages 630-646.
    13. Felipe Rosa-Rivera & Jose I. Nunez-Varela & Cesar A. Puente-Montejano & Sandra E. Nava-Muñoz, 2021. "Measuring the complexity of university timetabling instances," Journal of Scheduling, Springer, vol. 24(1), pages 103-121, February.
    14. Eiji Mizutani & Kevin Alexander Sánchez Galeano, 2023. "A note on a single-shift days-off scheduling problem with sequence-dependent labor costs," Journal of Scheduling, Springer, vol. 26(3), pages 315-329, June.
    15. R. A. Oude Vrielink & E. A. Jansen & E. W. Hans & J. Hillegersberg, 2019. "Practices in timetabling in higher education institutions: a systematic review," Annals of Operations Research, Springer, vol. 275(1), pages 145-160, April.
    16. Efstratios Rappos & Eric Thiémard & Stephan Robert & Jean-François Hêche, 2022. "A mixed-integer programming approach for solving university course timetabling problems," Journal of Scheduling, Springer, vol. 25(4), pages 391-404, August.
    17. Aslan, Ayse & Bakir, Ilke & Vis, Iris F.A., 2020. "A dynamic thompson sampling hyper-heuristic framework for learning activity planning in personalized learning," European Journal of Operational Research, Elsevier, vol. 286(2), pages 673-688.
    18. Kaixiang Zhu & Lily D. Li & Michael Li, 2021. "School Timetabling Optimisation Using Artificial Bee Colony Algorithm Based on a Virtual Searching Space Method," Mathematics, MDPI, vol. 10(1), pages 1-19, December.

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