IDEAS home Printed from https://ideas.repec.org/a/spr/annopr/v180y2010i1p3-3110.1007-s10479-008-0490-3.html
   My bibliography  Save this article

A multiobjective framework for heavily constrained examination timetabling problems

Author

Listed:
  • Christine Mumford

Abstract

University examination timetabling is a challenging set partitioning problem that comes in many variations, and real world applications usually carry multiple constraints and require the simultaneous optimization of several (often conflicting) objectives. This paper presents a multiobjective framework capable of solving heavily constrained timetabling problems. In this prototype study, we focus on the two objectives: minimizing timetable length while simultaneously optimizing the spread of examinations for individual students. Candidate solutions are presented to a multiobjective memetic algorithm as orderings of examinations, and a greedy algorithm is used to construct violation free timetables from permutation sequences of exams. The role of the multiobjective algorithm is to iteratively improve a population of orderings, with respect to the given objectives, using various mutation and reordering heuristics. Copyright Springer Science+Business Media, LLC 2010

Suggested Citation

  • Christine Mumford, 2010. "A multiobjective framework for heavily constrained examination timetabling problems," Annals of Operations Research, Springer, vol. 180(1), pages 3-31, November.
    • Handle: RePEc:spr:annopr:v:180:y:2010:i:1:p:3-31:10.1007/s10479-008-0490-3
    DOI: 10.1007/s10479-008-0490-3
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1007/s10479-008-0490-3
    Download Restriction: Access to full text is restricted to subscribers.
    File URL: https://libkey.io/10.1007/s10479-008-0490-3?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    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. Burke, Edmund K. & McCollum, Barry & Meisels, Amnon & Petrovic, Sanja & Qu, Rong, 2007. "A graph-based hyper-heuristic for educational timetabling problems," European Journal of Operational Research, Elsevier, vol. 176(1), pages 177-192, January.
    3. 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.
    4. Michael W. Carter, 1986. "OR Practice—A Survey of Practical Applications of Examination Timetabling Algorithms," Operations Research, INFORMS, vol. 34(2), pages 193-202, April.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Syariza Abdul-Rahman & Edmund Burke & Andrzej Bargiela & Barry McCollum & Ender Özcan, 2014. "A constructive approach to examination timetabling based on adaptive decomposition and ordering," Annals of Operations Research, Springer, vol. 218(1), pages 3-21, July.
    2. Gülcin Ermis & Can Akkan, 2019. "Search algorithms for improving the pareto front in a timetabling problem with a solution network-based robustness measure," Annals of Operations Research, Springer, vol. 275(1), pages 101-121, April.
    3. Johnes, Jill, 2015. "Operational Research in education," European Journal of Operational Research, Elsevier, vol. 243(3), pages 683-696.
    4. 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.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Burke, E.K. & Eckersley, A.J. & McCollum, B. & Petrovic, S. & Qu, R., 2010. "Hybrid variable neighbourhood approaches to university exam timetabling," European Journal of Operational Research, Elsevier, vol. 206(1), pages 46-53, October.
    2. Johnes, Jill, 2015. "Operational Research in education," European Journal of Operational Research, Elsevier, vol. 243(3), pages 683-696.
    3. Edmund Burke & Graham Kendall & Mustafa Mısır & Ender Özcan, 2012. "Monte Carlo hyper-heuristics for examination timetabling," Annals of Operations Research, Springer, vol. 196(1), pages 73-90, July.
    4. Edmund K. Burke & Yuri Bykov, 2016. "An Adaptive Flex-Deluge Approach to University Exam Timetabling," INFORMS Journal on Computing, INFORMS, vol. 28(4), pages 781-794, November.
    5. 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.
    6. Thepphakorn, Thatchai & Pongcharoen, Pupong & Hicks, Chris, 2014. "An ant colony based timetabling tool," International Journal of Production Economics, Elsevier, vol. 149(C), pages 131-144.
    7. Abdul Rahman, Syariza & Bargiela, Andrzej & Burke, Edmund K. & Özcan, Ender & McCollum, Barry & McMullan, Paul, 2014. "Adaptive linear combination of heuristic orderings in constructing examination timetables," European Journal of Operational Research, Elsevier, vol. 232(2), pages 287-297.
    8. G N Beligiannis & C Moschopoulos & S D Likothanassis, 2009. "A genetic algorithm approach to school timetabling," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 60(1), pages 23-42, January.
    9. De Boeck, Liesje & Beliën, Jeroen & Creemers, Stefan, 2016. "A column generation approach for solving the examination-timetabling problemAuthor-Name: Woumans, Gert," European Journal of Operational Research, Elsevier, vol. 253(1), pages 178-194.
    10. Pillay, N. & Banzhaf, W., 2009. "A study of heuristic combinations for hyper-heuristic systems for the uncapacitated examination timetabling problem," European Journal of Operational Research, Elsevier, vol. 197(2), pages 482-491, September.
    11. Zhang, Defu & Liu, Yongkai & M'Hallah, Rym & Leung, Stephen C.H., 2010. "A simulated annealing with a new neighborhood structure based algorithm for high school timetabling problems," European Journal of Operational Research, Elsevier, vol. 203(3), pages 550-558, June.
    12. Soria-Alcaraz, Jorge A. & Ochoa, Gabriela & Swan, Jerry & Carpio, Martin & Puga, Hector & Burke, Edmund K., 2014. "Effective learning hyper-heuristics for the course timetabling problem," European Journal of Operational Research, Elsevier, vol. 238(1), pages 77-86.
    13. Qu, Rong & Burke, Edmund K. & McCollum, Barry, 2009. "Adaptive automated construction of hybrid heuristics for exam timetabling and graph colouring problems," European Journal of Operational Research, Elsevier, vol. 198(2), pages 392-404, October.
    14. Song, Kwonsik & Kim, Sooyoung & Park, Moonseo & Lee, Hyun-Soo, 2017. "Energy efficiency-based course timetabling for university buildings," Energy, Elsevier, vol. 139(C), pages 394-405.
    15. Syariza Abdul-Rahman & Edmund Burke & Andrzej Bargiela & Barry McCollum & Ender Özcan, 2014. "A constructive approach to examination timetabling based on adaptive decomposition and ordering," Annals of Operations Research, Springer, vol. 218(1), pages 3-21, July.
    16. De Causmaecker, Patrick & Demeester, Peter & Vanden Berghe, Greet, 2009. "A decomposed metaheuristic approach for a real-world university timetabling problem," European Journal of Operational Research, Elsevier, vol. 195(1), pages 307-318, May.
    17. Kahar, M.N.M. & Kendall, G., 2010. "The examination timetabling problem at Universiti Malaysia Pahang: Comparison of a constructive heuristic with an existing software solution," European Journal of Operational Research, Elsevier, vol. 207(2), pages 557-565, December.
    18. 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.
    19. Sabar, Nasser R. & Ayob, Masri & Kendall, Graham & Qu, Rong, 2012. "A honey-bee mating optimization algorithm for educational timetabling problems," European Journal of Operational Research, Elsevier, vol. 216(3), pages 533-543.
    20. Nossack, Jenny, 2022. "Therapy scheduling and therapy planning at hospitals," Omega, Elsevier, vol. 109(C).

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:spr:annopr:v:180:y:2010:i:1:p:3-31:10.1007/s10479-008-0490-3. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.