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Optimal Student Sectioning at Niederrhein University of Applied Sciences

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Operations Research Proceedings 2019

Part of the book series: Operations Research Proceedings ((ORP))

Abstract

Degree programs with a largely fixed timetable require centralized planning of student groups (sections). Typically, group sizes for exercises and practicals are small, and different groups are taught at the same time. To avoid late or weekend sessions, exercises and practicals of the same or of different subjects can be scheduled concurrently, and the duration of lessons can vary. By means of an integer linear program, an optimal group division is carried out. To this end, groups have to be assigned to time slots and students have to be divided into groups such that they do not have conflicting appointments. The optimization goal is to create homogeneous group sizes.

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Notes

  1. 1.

    See https://www.ibm.com/customer-engagement/commerce.

References

  1. Bettinelli, A., Cacchiani, V., Roberti, R., Toth, P.: An overview of curriculum-based course timetabling. TOP 23(2), 313–349 (2015)

    Article  Google Scholar 

  2. Laporte, G., Desroches, S.: The problem of assigning students to course sections in a large engineering school. Comput. Oper. Res. 13(4), 387–394 (1986)

    Article  Google Scholar 

  3. Müller, T., Murray, K.: Comprehensive approach to student sectioning. Ann. Oper. Res. 181(1), 249–269 (2010)

    Article  Google Scholar 

  4. Schaerf, A.: A survey of automated timetabling. Artif. Intell. Rev. 13(2), 87–127 (1999)

    Article  Google Scholar 

  5. Schimmelpfeng, K., Helber, S.: Application of a real-world university-course timetabling model solved by integer programming. OR Spectr. 29(4), 783–803 (2007)

    Article  Google Scholar 

  6. Schindl, D.: Student sectioning for minimizing potential conflicts on multi-section courses. In: Proceedings of the 11th International Conference of the Practice and Theory of Automated Timetabling (PATAT 2016), Udine, pp. 327–337 (2016)

    Google Scholar 

  7. Sherali, H.D., Driscoll, P.J.: Course scheduling and timetabling at USMA. Mil. Oper. Res. 4(2), 25–43 (1999)

    Article  Google Scholar 

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Correspondence to Steffen Goebbels or Timo Pfeiffer .

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Goebbels, S., Pfeiffer, T. (2020). Optimal Student Sectioning at Niederrhein University of Applied Sciences. In: Neufeld, J.S., Buscher, U., Lasch, R., Möst, D., Schönberger, J. (eds) Operations Research Proceedings 2019. Operations Research Proceedings. Springer, Cham. https://doi.org/10.1007/978-3-030-48439-2_20

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