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Licence: CC BY: Creative Commons Attribution 4.0 International License
Research output: Contribution to Journal/Magazine › Special issue › peer-review
Research output: Contribution to Journal/Magazine › Special issue › peer-review
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TY - JOUR
T1 - Modelling and solving the university course timetabling problem with hybrid teaching considerations
AU - Davison, Matthew
AU - Kheiri, Ahmed
AU - Zografos, K. G.
PY - 2025/4/30
Y1 - 2025/4/30
N2 - The university course timetabling problem is a challenging problem to solve. As universities have evolved, the features of this problem have changed. One emerging feature is hybrid teaching where classes can be taught online, in-person or a combination of both in-person and online. This work presents a multi-objective binary programming model that includes common university timetabling features, identified from the literature, as well as hybrid teaching features. A lexicographic solution method is outlined and computational experiments using benchmark data are used to demonstrate the key aspects of the model and explore trade-offs among the objectives considered. The results of these experiments demonstrate that the model can be used to find demand-driven schedules for universities that include hybrid teaching. They also show how the model could be used to inform practitioners who are involved in strategic decision-making at universities.
AB - The university course timetabling problem is a challenging problem to solve. As universities have evolved, the features of this problem have changed. One emerging feature is hybrid teaching where classes can be taught online, in-person or a combination of both in-person and online. This work presents a multi-objective binary programming model that includes common university timetabling features, identified from the literature, as well as hybrid teaching features. A lexicographic solution method is outlined and computational experiments using benchmark data are used to demonstrate the key aspects of the model and explore trade-offs among the objectives considered. The results of these experiments demonstrate that the model can be used to find demand-driven schedules for universities that include hybrid teaching. They also show how the model could be used to inform practitioners who are involved in strategic decision-making at universities.
U2 - 10.1007/s10951-024-00817-w
DO - 10.1007/s10951-024-00817-w
M3 - Special issue
VL - 28
SP - 195
EP - 215
JO - Journal of Scheduling
JF - Journal of Scheduling
SN - 1094-6136
IS - 2
ER -