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Minimal Perturbation in University Timetabling with Maximum Satisfiability

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Integration of Constraint Programming, Artificial Intelligence, and Operations Research (CPAIOR 2020)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 12296))

Abstract

Every new academic year, scheduling new timetables due to disruptions is a major problem for universities. However, computing a new timetable from scratch may be unnecessarily expensive. Furthermore, this process may produce a significantly different timetable which in many cases is undesirable for all parties involved. For this reason, we aim to find a new feasible timetable while minimizing the number of perturbations relative to the original disrupted timetable.

The contribution of this paper is a maximum satisfiability (MaxSAT) encoding to solve large and complex university timetabling problem instances which can be subject to disruptions. To validate the MaxSAT encoding, we evaluate university timetabling real-world instances from the International Timetabling Competition (ITC) 2019. We consider the originally found solutions as a starting point, to evaluate the capacity of the proposed MaxSAT encoding to find a new solution with minimal perturbation. Overall, our model is able to efficiently solve the disrupted instances.

The authors would like to thank the reviewers for their helpful comments and suggestions that contributed to an improved manuscript. This work was supported by national funds through Fundação para a Ciência e a Tecnologia (FCT) with reference SFRH/BD/143212/2019 (PhD grant), DSAIPA/AI/0033/2019 (project LAIfeBlood) and UIDB/50021/2020 (INESC-ID multi-annual funding).

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Notes

  1. 1.

    https://www.itc2019.org/validator.

  2. 2.

    TT-Open-WBO-Inc won the Weighted Incomplete category at MaxSAT Evaluation 2019. The results are available at https://maxsat-evaluations.github.io/2019.

  3. 3.

    We use the RAPIDXML parser which is available at rapidxml.sourceforge.net/.

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Authors and Affiliations

  1. Instituto Superior Técnico, Universidade de Lisboa, INESC-ID, Rua Alves Redol 9, 1000-029, Lisbon, Portugal

    Alexandre Lemos, Pedro T. Monteiro & Inês Lynce

Authors
  1. Alexandre Lemos
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  2. Pedro T. Monteiro
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  3. Inês Lynce
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Corresponding author

Correspondence to Alexandre Lemos .

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Editors and Affiliations

  1. LAAS - CNRS, Toulouse, France

    Emmanuel Hebrard

  2. TU Wien, Vienna, Wien, Austria

    Nysret Musliu

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Lemos, A., Monteiro, P.T., Lynce, I. (2020). Minimal Perturbation in University Timetabling with Maximum Satisfiability. In: Hebrard, E., Musliu, N. (eds) Integration of Constraint Programming, Artificial Intelligence, and Operations Research. CPAIOR 2020. Lecture Notes in Computer Science(), vol 12296. Springer, Cham. https://doi.org/10.1007/978-3-030-58942-4_21

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  • DOI: https://doi.org/10.1007/978-3-030-58942-4_21

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