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Introducing UniCorT: an iterative university course timetabling tool with MaxSAT

Author

Listed:
  • Alexandre Lemos

    (Universidade de Lisboa, INESC-ID)

  • Pedro T. Monteiro

    (Universidade de Lisboa, INESC-ID)

  • Inês Lynce

    (Universidade de Lisboa, INESC-ID)

Abstract

This paper describes the UniCorT tool designed to solve university course timetabling problems specifically tailored for the 2019 International Timetabling Competition (ITC 2019). The proposed approach includes pre-processing, the use of a maximum satisfiability (MaxSAT) solver and a local search procedure. UniCorT is assessed with the benchmark instances from the ITC 2019. The impact of a handful of techniques in the quality of the solution and the execution time is evaluated. We take into account different pre-processing techniques and conjunctive normal form (CNF) encodings, as well as the combination with a local search procedure. The success of our tool is attested by having been ranked among the five finalists of the ITC 2019 competition.

Suggested Citation

  • Alexandre Lemos & Pedro T. Monteiro & Inês Lynce, 2022. "Introducing UniCorT: an iterative university course timetabling tool with MaxSAT," Journal of Scheduling, Springer, vol. 25(4), pages 371-390, August.
    • Handle: RePEc:spr:jsched:v:25:y:2022:i:4:d:10.1007_s10951-021-00695-6
    DOI: 10.1007/s10951-021-00695-6
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    References listed on IDEAS

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    1. Antony E. Phillips & Cameron G. Walker & Matthias Ehrgott & David M. Ryan, 2017. "Integer programming for minimal perturbation problems in university course timetabling," Annals of Operations Research, Springer, vol. 252(2), pages 283-304, May.
    2. Mutsunori Banbara & Katsumi Inoue & Benjamin Kaufmann & Tenda Okimoto & Torsten Schaub & Takehide Soh & Naoyuki Tamura & Philipp Wanko, 2019. "$${\varvec{teaspoon}}$$ teaspoon : solving the curriculum-based course timetabling problems with answer set programming," Annals of Operations Research, Springer, vol. 275(1), pages 3-37, April.
    3. Roberto Asín Achá & Robert Nieuwenhuis, 2014. "Curriculum-based course timetabling with SAT and MaxSAT," Annals of Operations Research, Springer, vol. 218(1), pages 71-91, July.
    4. David Schindl, 2019. "Optimal student sectioning on mandatory courses with various sections numbers," Annals of Operations Research, Springer, vol. 275(1), pages 209-221, April.
    5. Lemos, Alexandre & Melo, Francisco S. & Monteiro, Pedro T. & Lynce, Inês, 2019. "Room usage optimization in timetabling: A case study at Universidade de Lisboa," Operations Research Perspectives, Elsevier, vol. 6(C).
    6. 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.
    7. Britta Herres & Heinz Schmitz, 2021. "Decomposition of university course timetabling," Annals of Operations Research, Springer, vol. 302(2), pages 405-423, July.
    8. Lindahl, Michael & Stidsen, Thomas & Sørensen, Matias, 2019. "Quality recovering of university timetables," European Journal of Operational Research, Elsevier, vol. 276(2), pages 422-435.
    9. 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.
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    Cited by:

    1. Fabian Dunke & Stefan Nickel, 2023. "A matheuristic for customized multi-level multi-criteria university timetabling," Annals of Operations Research, Springer, vol. 328(2), pages 1313-1348, September.

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