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Developing compact course timetables with optimized student flows

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  • Vermuyten, Hendrik
  • Lemmens, Stef
  • Marques, Inês
  • Beliën, Jeroen

Abstract

In university buildings with many rooms spread over different floors, large student flows between two consecutive lectures might cause congestion problems. These congestions result in long queues at elevators or at stairwells, which might lead to delays in lecture starts. The course timetable clearly has an important impact on these congestions. This paper presents a two-stage integer programming approach for building a university course timetable that aims at minimizing the resulting student flows. The first stage minimizes the violation of the teacher and educational preferences by assigning lectures to timeslots and rooms. The second stage reassigns classrooms to lectures of the timetable of the first stage and minimizes the student flow. The conceptual model is applied to the dataset of the Faculty of Economics and Business of the KU Leuven Campus Brussels and is tested and validated with 21 adapted instances from the literature. In contrast to a monolithic model, the two-stage model consistently succeeds in finding good quality feasible solutions. Moreover, the generated timetables entail significantly reduced student flows compared to the flows of the manually developed course timetable.

Suggested Citation

  • Vermuyten, Hendrik & Lemmens, Stef & Marques, Inês & Beliën, Jeroen, 2016. "Developing compact course timetables with optimized student flows," European Journal of Operational Research, Elsevier, vol. 251(2), pages 651-661.
    • Handle: RePEc:eee:ejores:v:251:y:2016:i:2:p:651-661
    DOI: 10.1016/j.ejor.2015.11.028
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    References listed on IDEAS

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    Cited by:

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    2. Lemos, Alexandre & Melo, Francisco S. & Monteiro, Pedro T. & Lynce, Inês, 2019. "Room usage optimization in timetabling: A case study at Universidade de Lisboa," Operations Research Perspectives, Elsevier, vol. 6(C).
    3. Dönmez, Kadir & Demirel, Soner & Özdemir, Mustafa, 2020. "Handling the pseudo pilot assignment problem in air traffic control training by using NASA TLX," Journal of Air Transport Management, Elsevier, vol. 89(C).
    4. Almeida, João & Santos, Daniel & Figueira, José Rui & Francisco, Alexandre P., 2024. "A multi-objective mixed integer linear programming model for thesis defence scheduling," European Journal of Operational Research, Elsevier, vol. 312(1), pages 92-116.
    5. Seizinger, Markus & Brunner, Jens O., 2023. "Optimized planning of nursing curricula in dual vocational schools focusing on the German health care system," European Journal of Operational Research, Elsevier, vol. 304(3), pages 1223-1241.
    6. Lu, X. & Blanton, H. & Gifford, T. & Tucker, A. & Olderman, N., 2021. "Optimized guidance for building fires considering occupants’ route choices," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 561(C).

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