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

  • S.I. : PATAT 2014
  • Published:
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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.

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Notes

  1. http://www.cs.qub.ac.uk/itc2007/.

  2. http://satt.diegm.uniud.it/ctt/ (accessed: 2015-07-01).

  3. http://satt.diegm.uniud.it/.

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Acknowledgments

The financial support by the Austrian Federal Ministry of Science, Research and Economy and the National Foundation for Research, Technology and Development is gratefully acknowledged. The computational results presented have been achieved in part using the Vienna Scientific Cluster (VSC). We acknowledge the constructive input by the anonymous reviewers.

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Authors and Affiliations

  1. Christian Doppler Laboratory for Efficient Intermodal Transport Operations, Department of Business Administration, University of Vienna, Oskar-Morgenstern-Platz 1, 1090, Vienna, Austria

    Alexander Kiefer

  2. Department of Business Administration, University of Vienna, Oskar-Morgenstern-Platz 1, 1090, Vienna, Austria

    Richard F. Hartl & Alexander Schnell

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  1. Alexander Kiefer
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  2. Richard F. Hartl
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  3. Alexander Schnell
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Correspondence to Alexander Kiefer.

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Kiefer, A., Hartl, R.F. & Schnell, A. Adaptive large neighborhood search for the curriculum-based course timetabling problem. Ann Oper Res 252, 255–282 (2017). https://doi.org/10.1007/s10479-016-2151-2

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  • DOI: https://doi.org/10.1007/s10479-016-2151-2

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