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Parallel local search algorithms for high school timetabling problems

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  • Saviniec, Landir
  • Santos, Maristela O.
  • Costa, Alysson M.

Abstract

High school timetabling consists in assigning meetings between classes and teachers, with the goal of minimizing the violation of specific soft requirements. This family of problems has been frequently considered in the literature, but few strategies employing parallelism have been proposed. In this exploratory study, we consider two different parallel frameworks and present a thorough computational study in order to understand algorithmic decisions that are closely related to performance. Our best algorithm outperforms state-of-the-art algorithms for variants of the problem considered, indicating both the efficiency and the flexibility of the method.

Suggested Citation

  • 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.
    • Handle: RePEc:eee:ejores:v:265:y:2018:i:1:p:81-98
    DOI: 10.1016/j.ejor.2017.07.029
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    References listed on IDEAS

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    1. de Werra, D., 1985. "An introduction to timetabling," European Journal of Operational Research, Elsevier, vol. 19(2), pages 151-162, February.
    2. Nelishia Pillay, 2014. "A survey of school timetabling research," Annals of Operations Research, Springer, vol. 218(1), pages 261-293, July.
    3. Gerhard Post & Samad Ahmadi & Sophia Daskalaki & Jeffrey Kingston & Jari Kyngas & Cimmo Nurmi & David Ranson, 2012. "An XML format for benchmarks in High School Timetabling," Annals of Operations Research, Springer, vol. 194(1), pages 385-397, April.
    4. 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.
    5. Gerhard Post & Luca Gaspero & Jeffrey H. Kingston & Barry McCollum & Andrea Schaerf, 2016. "The Third International Timetabling Competition," Annals of Operations Research, Springer, vol. 239(1), pages 69-75, April.
    6. George Henrique Godim Fonseca & Haroldo Gambini Santos & Túlio Ângelo Machado Toffolo & Samuel Souza Brito & Marcone Jamilson Freitas Souza, 2016. "GOAL solver: a hybrid local search based solver for high school timetabling," Annals of Operations Research, Springer, vol. 239(1), pages 77-97, April.
    7. Fred Glover, 1990. "Tabu Search: A Tutorial," Interfaces, INFORMS, vol. 20(4), pages 74-94, August.
    8. D. Abramson, 1991. "Constructing School Timetables Using Simulated Annealing: Sequential and Parallel Algorithms," Management Science, INFORMS, vol. 37(1), pages 98-113, January.
    9. George H. G. Fonseca & Haroldo G. Santos & Eduardo G. Carrano, 2016. "Late acceptance hill-climbing for high school timetabling," Journal of Scheduling, Springer, vol. 19(4), pages 453-465, August.
    10. Haroldo Santos & Eduardo Uchoa & Luiz Ochi & Nelson Maculan, 2012. "Strong bounds with cut and column generation for class-teacher timetabling," Annals of Operations Research, Springer, vol. 194(1), pages 399-412, April.
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    Cited by:

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    2. Dönmez, Kadir & Demirel, Soner & Özdemir, Mustafa, 2020. "Handling the pseudo pilot assignment problem in air traffic control training by using NASA TLX," Journal of Air Transport Management, Elsevier, vol. 89(C).
    3. Rasmus Ø. Mikkelsen & Dennis S. Holm, 2022. "A parallelized matheuristic for the International Timetabling Competition 2019," Journal of Scheduling, Springer, vol. 25(4), pages 429-452, August.

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