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

Alexander Kiefer (), Richard F. Hartl and Alexander Schnell
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Alexander Kiefer: University of Vienna
Richard F. Hartl: University of Vienna
Alexander Schnell: University of Vienna

Annals of Operations Research, 2017, vol. 252, issue 2, No 4, 255-282

Abstract: 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.

Keywords: University courses; Timetabling; Metaheuristics; Adaptive large neighborhood search (search for similar items in EconPapers)
Date: 2017
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Citations: View citations in EconPapers (6)

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DOI: 10.1007/s10479-016-2151-2

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