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Adaptive large neighborhood search for the curriculum-based course timetabling problem

Author

Listed:
  • Alexander Kiefer

    (University of Vienna)

  • Richard F. Hartl

    (University of Vienna)

  • Alexander Schnell

    (University of Vienna)

Abstract

In curriculum-based course timetabling, lectures have to be assigned to periods and rooms, while avoiding overlaps between courses of the same curriculum. Taking into account the inherent complexity of the problem, a metaheuristic solution approach is proposed, more precisely an adaptive large neighborhood search, which is based on repetitively destroying and subsequently repairing relatively large parts of the solution. Several problem-specific operators are introduced. The proposed algorithm proves to be very effective for the curriculum-based course timetabling problem. In particular, it outperforms the best algorithms of the international timetabling competition in 2007 and finds five new best known solutions for benchmark instances of the competition.

Suggested Citation

  • Alexander Kiefer & Richard F. Hartl & Alexander Schnell, 2017. "Adaptive large neighborhood search for the curriculum-based course timetabling problem," Annals of Operations Research, Springer, vol. 252(2), pages 255-282, May.
    • Handle: RePEc:spr:annopr:v:252:y:2017:i:2:d:10.1007_s10479-016-2151-2
    DOI: 10.1007/s10479-016-2151-2
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    References listed on IDEAS

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    Cited by:

    1. Turkeš, Renata & Sörensen, Kenneth & Hvattum, Lars Magnus, 2021. "Meta-analysis of metaheuristics: Quantifying the effect of adaptiveness in adaptive large neighborhood search," European Journal of Operational Research, Elsevier, vol. 292(2), pages 423-442.
    2. 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.
    3. TURKEŠ, Renata & SÖRENSEN, Kenneth & HVATTUM, Lars Magnus & BARRENA, Eva & CHENTLI, Hayet & COELHO, Leandro & DAYARIAN, Iman & GRIMAULT, Axel & GULLHAVE, Anders & IRIS, Çagatay & KESKIN, Merve & KIEFE, 2019. "Meta-analysis of metaheuristics: Quantifying the effect of adaptiveness in adaptive large neighborhood search," Working Papers 2019002, University of Antwerp, Faculty of Business and Economics.
    4. Emil Karlsson & Elina Rönnberg & Andreas Stenberg & Hannes Uppman, 2021. "A matheuristic approach to large-scale avionic scheduling," Annals of Operations Research, Springer, vol. 302(2), pages 425-459, July.
    5. 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.
    6. 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.

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