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Research output: Contribution to Journal/Magazine › Journal article › peer-review
Research output: Contribution to Journal/Magazine › Journal article › peer-review
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TY - JOUR
T1 - Integer programming for minimal perturbation problems in university course timetabling
AU - Phillips, Antony E.
AU - Walker, Cameron G.
AU - Ehrgott, Matthias
AU - Ryan, David M.
N1 - The final publication is available at Springer via http://dx.doi.org/10.1007/s10479-015-2094-z
PY - 2017/5
Y1 - 2017/5
N2 - In this paper we present a general integer programming-based approach for theminimal perturbation problem in university course timetabling. This problem arises when an existing timetable contains hard constraint violations, or infeasibilities, which need to be resolved. The objective is to resolve these infeasibilities while minimising the disruption or perturbation to the remainder of the timetable. This situation commonly occurs in practical timetabling, for example when there are unexpected changes to course enrolments or availablerooms. Our method attempts to resolve each infeasibility in the smallest neighbourhood possible, by utilising the exactness of integer programming. Operating within a neighbourhood of minimal size keeps the computations fast, and does not permit large movements of course events, which cause widespread disruption to timetable structure. We demonstrate the application of this method using examples based on real data from the University ofAuckland.
AB - In this paper we present a general integer programming-based approach for theminimal perturbation problem in university course timetabling. This problem arises when an existing timetable contains hard constraint violations, or infeasibilities, which need to be resolved. The objective is to resolve these infeasibilities while minimising the disruption or perturbation to the remainder of the timetable. This situation commonly occurs in practical timetabling, for example when there are unexpected changes to course enrolments or availablerooms. Our method attempts to resolve each infeasibility in the smallest neighbourhood possible, by utilising the exactness of integer programming. Operating within a neighbourhood of minimal size keeps the computations fast, and does not permit large movements of course events, which cause widespread disruption to timetable structure. We demonstrate the application of this method using examples based on real data from the University ofAuckland.
KW - Minimal perturbation problems
KW - University course timetabling
KW - Integer Programming
KW - Decision Support Systems
U2 - 10.1007/s10479-015-2094-z
DO - 10.1007/s10479-015-2094-z
M3 - Journal article
VL - 252
SP - 283
EP - 304
JO - Annals of Operations Research
JF - Annals of Operations Research
SN - 0254-5330
IS - 2
ER -