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GOAL solver: a hybrid local search based solver for high school timetabling

Author

Listed:
  • George Henrique Godim Fonseca

    (Federal University of Ouro Preto)

  • Haroldo Gambini Santos

    (Federal University of Ouro Preto)

  • Túlio Ângelo Machado Toffolo

    (Federal University of Ouro Preto)

  • Samuel Souza Brito

    (Federal University of Ouro Preto)

  • Marcone Jamilson Freitas Souza

    (Federal University of Ouro Preto)

Abstract

This work presents a local search approach to the High School Timetabling Problem. The addressed timetabling model is the one stated in the Third International Timetabling Competition (ITC 2011), which considered many instances from educational institutions around the world and attracted seventeen competitors. Our team, named GOAL (Group of Optimization and Algorithms), developed a solver built upon the Kingston High School Timetabling Engine. Several neighborhood structures were developed and used in a hybrid metaheuristic based on Simulated Annealing and Iterated Local Search. The developed algorithm was the winner of the competition and produced the best known solutions for almost all instances.

Suggested Citation

  • 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.
    • Handle: RePEc:spr:annopr:v:239:y:2016:i:1:d:10.1007_s10479-014-1685-4
    DOI: 10.1007/s10479-014-1685-4
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    References listed on IDEAS

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    1. David S. Johnson & Cecilia R. Aragon & Lyle A. McGeoch & Catherine Schevon, 1991. "Optimization by Simulated Annealing: An Experimental Evaluation; Part II, Graph Coloring and Number Partitioning," Operations Research, INFORMS, vol. 39(3), pages 378-406, June.
    2. Lü, Zhipeng & Hao, Jin-Kao, 2010. "Adaptive Tabu Search for course timetabling," European Journal of Operational Research, Elsevier, vol. 200(1), pages 235-244, January.
    3. Gerhard Post & Jeffrey Kingston & Samad Ahmadi & Sophia Daskalaki & Christos Gogos & Jari Kyngas & Cimmo Nurmi & Nysret Musliu & Nelishia Pillay & Haroldo Santos & Andrea Schaerf, 2014. "XHSTT: an XML archive for high school timetabling problems in different countries," Annals of Operations Research, Springer, vol. 218(1), pages 295-301, July.
    4. Tomáš Müller, 2009. "ITC2007 solver description: a hybrid approach," Annals of Operations Research, Springer, vol. 172(1), pages 429-446, November.
    5. 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:

    1. 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.
    2. André Renato Villela Silva & Luiz Satoru Ochi & Bruno José da Silva Barros & Rian Gabriel S. Pinheiro, 2020. "Efficient approaches for the Flooding Problem on graphs," Annals of Operations Research, Springer, vol. 286(1), pages 33-54, March.
    3. Rodriguez-Tello, Eduardo & Lardeux, Frédéric & Duarte, Abraham & Narvaez-Teran, Valentina, 2019. "Alternative evaluation functions for the cyclic bandwidth sum problem," European Journal of Operational Research, Elsevier, vol. 273(3), pages 904-919.
    4. 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.
    5. Drake, John H. & Kheiri, Ahmed & Özcan, Ender & Burke, Edmund K., 2020. "Recent advances in selection hyper-heuristics," European Journal of Operational Research, Elsevier, vol. 285(2), pages 405-428.

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