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Efficient iterated local search based metaheuristic approach for solving sports timetabling problems of International Timetabling Competition 2021

Author

Listed:
  • I. Gusti Agung Premananda

    (Institut Teknologi Sepuluh Nopember (ITS))

  • Aris Tjahyanto

    (Institut Teknologi Sepuluh Nopember (ITS))

  • Ahmad Mukhlason

    (Institut Teknologi Sepuluh Nopember (ITS))

Abstract

Sports timetabling is a complex and challenging problem. The latest open benchmark dataset for the sport timetabling problem is from the International Timetabling Competition (ITC) 2021. Due to its complexity, only a few approaches have successfully generated feasible solutions for the problems in this dataset, as reported in scientific literature. To the best of our knowledge, there is only one study in the literature that has successfully generated feasible solutions for all 45 problems in the dataset. In this paper, we propose our novel efficient algorithm based on the Iterated Local Search algorithm to solve the ITC 2021 benchmark dataset. Unlike prior successful approaches that combined metaheuristics with an exact approach, our proposed approach is solely metaheuristic. Our contribution includes the design of strategies for both perturbation and local search phases, coupled with the integration of shuffling strategies. The experimental results show that our proposed algorithm is remarkably successful in generating feasible solutions for all 45 problems present in the ITC 2021 dataset.

Suggested Citation

  • I. Gusti Agung Premananda & Aris Tjahyanto & Ahmad Mukhlason, 2024. "Efficient iterated local search based metaheuristic approach for solving sports timetabling problems of International Timetabling Competition 2021," Annals of Operations Research, Springer, vol. 343(1), pages 411-427, December.
    • Handle: RePEc:spr:annopr:v:343:y:2024:i:1:d:10.1007_s10479-024-06285-x
    DOI: 10.1007/s10479-024-06285-x
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    References listed on IDEAS

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    1. Martin Mariusz Lester, 2022. "Pseudo-Boolean optimisation for RobinX sports timetabling," Journal of Scheduling, Springer, vol. 25(3), pages 287-299, June.
    2. 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.
    3. Van Bulck, David & Goossens, Dries, 2023. "The international timetabling competition on sports timetabling (ITC2021)," European Journal of Operational Research, Elsevier, vol. 308(3), pages 1249-1267.
    4. 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.
    5. Van Bulck, David & Goossens, Dries & Schönberger, Jörn & Guajardo, Mario, 2020. "RobinX: A three-field classification and unified data format for round-robin sports timetabling," European Journal of Operational Research, Elsevier, vol. 280(2), pages 568-580.
    6. Roberto Maria Rosati & Matteo Petris & Luca Di Gaspero & Andrea Schaerf, 2022. "Multi-neighborhood simulated annealing for the sports timetabling competition ITC2021," Journal of Scheduling, Springer, vol. 25(3), pages 301-319, June.
    7. Xiajie Yi & Dries Goossens, 2023. "Strategies for dealing with uncertainty in time-relaxed sports timetabling," Annals of Operations Research, Springer, vol. 320(1), pages 473-492, January.
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