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An improved multi-staged algorithmic process for the solution of the examination timetabling problem

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  • Christos Gogos
  • Panayiotis Alefragis
  • Efthymios Housos

Abstract

The efficient creation of examination timetables is a recurring and important problem for universities worldwide. Good timetables typically are characterized by balanced distances between consecutive exams for all students. In this contribution an approach for the examination timetabling problem as defined in the second International Timetabling Competition ( http://www.cs.qub.ac.uk/itc2007/ ) is presented. The solution approach is managed on the top level by GRASP (Greedy Randomized Adaptive Search Procedure) and it involves several optimization algorithms, heuristics and metaheuristics. A construction phase is executed first producing a relatively high quality feasible solution and an improvement phase follows that further ameliorates the produced timetable. Each phase consists of stages that are consumed in a circular fashion. The procedure produces feasible solutions for each dataset provided under the runtime limit imposed by the rules of the ITC07 competition. Results are presented and analyzed. Copyright Springer Science+Business Media, LLC 2012

Suggested Citation

  • Christos Gogos & Panayiotis Alefragis & Efthymios Housos, 2012. "An improved multi-staged algorithmic process for the solution of the examination timetabling problem," Annals of Operations Research, Springer, vol. 194(1), pages 203-221, April.
    • Handle: RePEc:spr:annopr:v:194:y:2012:i:1:p:203-221:10.1007/s10479-010-0712-3
    DOI: 10.1007/s10479-010-0712-3
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    References listed on IDEAS

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    1. Burke, Edmund Kieran & Petrovic, Sanja, 2002. "Recent research directions in automated timetabling," European Journal of Operational Research, Elsevier, vol. 140(2), pages 266-280, July.
    2. Graham Kendall & Naimah Mohd Hussin, 2005. "An Investigation of a Tabu-Search-Based Hyper-Heuristic for Examination Timetabling," Springer Books, in: Graham Kendall & Edmund K. Burke & Sanja Petrovic & Michel Gendreau (ed.), Multidisciplinary Scheduling: Theory and Applications, pages 309-328, Springer.
    3. R Qu & E K Burke, 2009. "Hybridizations within a graph-based hyper-heuristic framework for university timetabling problems," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 60(9), pages 1273-1285, September.
    4. Michael W. Carter & Gilbert Laporte & John W. Chinneck, 1994. "A General Examination Scheduling System," Interfaces, INFORMS, vol. 24(3), pages 109-120, June.
    5. E.K. Burke & J.P. Newall, 2004. "Solving Examination Timetabling Problems through Adaption of Heuristic Orderings," Annals of Operations Research, Springer, vol. 129(1), pages 107-134, July.
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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. Álvaro García-Sánchez & Araceli Hernández & Eduardo Caro & Gonzalo Jiménez, 2019. "Universidad Politécnica de Madrid Uses Integer Programming for Scheduling Weekly Assessment Activities," Interfaces, INFORMS, vol. 49(2), pages 104-116, March.
    4. Mohammed Al-Betar & Ahamad Khader & Iyad Doush, 2014. "Memetic techniques for examination timetabling," Annals of Operations Research, Springer, vol. 218(1), pages 23-50, July.
    5. Taha Arbaoui & Jean-Paul Boufflet & Aziz Moukrim, 2015. "Preprocessing and an improved MIP model for examination timetabling," Annals of Operations Research, Springer, vol. 229(1), pages 19-40, June.
    6. Alejandro Cataldo & Juan-Carlos Ferrer & Jaime Miranda & Pablo A. Rey & Antoine Sauré, 2017. "An integer programming approach to curriculum-based examination timetabling," Annals of Operations Research, Springer, vol. 258(2), pages 369-393, November.
    7. T. Godwin, 2022. "Obtaining quality business school examination timetable under heterogeneous elective selections through surrogacy," OPSEARCH, Springer;Operational Research Society of India, vol. 59(3), pages 1055-1093, September.
    8. Michele Battistutta & Andrea Schaerf & Tommaso Urli, 2017. "Feature-based tuning of single-stage simulated annealing for examination timetabling," Annals of Operations Research, Springer, vol. 252(2), pages 239-254, May.

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