2002
DOI: 10.1002/jos.97
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Complexity of some special types of timetabling problems

Abstract: SUMMARYStarting from the simple class-teacher model of timetabling (where timetables correspond to edge colorings of a bipartite multigraph), we consider an extension deÿned as follows: we assume that the set of classes is partitioned into groups. In addition to the teachers giving lectures to individual classes, we have a collection of teachers who give all their lectures to groups of classes. We show that when there is one such teacher giving lectures to three groups of classes, the problem is NP-complete. W… Show more

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Cited by 30 publications
(17 citation statements)
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“…De Werra et al (2002) presented a simple model and some possible extensions for classteacher timetabling problems. The computational complexity of these problems was also studied, showing some variants of the problem as NP-complete.…”
Section: The Examination Timetabling Problem: Modellingmentioning
confidence: 99%
“…De Werra et al (2002) presented a simple model and some possible extensions for classteacher timetabling problems. The computational complexity of these problems was also studied, showing some variants of the problem as NP-complete.…”
Section: The Examination Timetabling Problem: Modellingmentioning
confidence: 99%
“…[30][31][32] Complexity issues in course timetabling have also been studied in some depth. 33,34 A wide variety of research papers on different types of timetabling are also available. [8][9][10][11][12] In this paper, we investigate CBR for course timetabling.…”
Section: Timetabling Problemsmentioning
confidence: 99%
“…In this case, we cannot even find any feasible solution in two hours of computation time. Some- (24). With this strategy, P rob1 is solved to optimality in time very close to the limit of 2 hours.…”
Section: Namechrḡs Nodesmentioning
confidence: 99%
“…The class-teacher model is formulated as an edge-coloring problem on a bipartite multigraph [23]. It is polynomially solvable, but the addition of some real-life constraints makes the problem NP-complete [24].…”
Section: Introductionmentioning
confidence: 99%