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Applying the threshold accepting metaheuristic to curriculum based course timetabling

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  • Martin Geiger

Abstract

The article presents a study of local search algorithms for timetabling problems, with the particular goal of providing a contribution to competition track 3 of the International Timetabling Competition 2007 (ITC 2007). In this track, a formulation of a curriculum based course timetabling has been published, and novel benchmark instances have been presented that allow the comparison of optimization approaches. Our heuristic local search procedure is based on the principles of Threshold Accepting, overcoming local optima by a deterministic acceptance of inferior solutions throughout the search runs. A stochastic neighborhood is proposed and implemented, randomly removing and reassigning events from the current solution. The overall concept has been incrementally obtained from a series of experiments, which we describe in each (sub)section of the paper. In conclusions, we successfully derived a potential candidate solution approach for the finals of track 3 of the ITC 2007, held in August 2008 in Montréal, Canada. Copyright Springer Science+Business Media, LLC 2012

Suggested Citation

  • Martin Geiger, 2012. "Applying the threshold accepting metaheuristic to curriculum based course timetabling," Annals of Operations Research, Springer, vol. 194(1), pages 189-202, April.
    • Handle: RePEc:spr:annopr:v:194:y:2012:i:1:p:189-202:10.1007/s10479-010-0703-4
    DOI: 10.1007/s10479-010-0703-4
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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. 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.
    3. van den Broek, John & Hurkens, Cor & Woeginger, Gerhard, 2009. "Timetabling problems at the TU Eindhoven," European Journal of Operational Research, Elsevier, vol. 196(3), pages 877-885, August.
    4. 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.
    5. 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.
    6. E K Burke & B L MacCarthy & S Petrovic & R Qu, 2006. "Multiple-retrieval case-based reasoning for course timetabling problems," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 57(2), pages 148-162, February.
    7. Lü, Zhipeng & Hao, Jin-Kao, 2010. "Adaptive Tabu Search for course timetabling," European Journal of Operational Research, Elsevier, vol. 200(1), pages 235-244, January.
    8. K A Dowsland & J M Thompson, 2005. "Ant colony optimization for the examination scheduling problem," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 56(4), pages 426-438, April.
    9. White, George M. & Xie, Bill S. & Zonjic, Stevan, 2004. "Using tabu search with longer-term memory and relaxation to create examination timetables," European Journal of Operational Research, Elsevier, vol. 153(1), pages 80-91, February.
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    Cited by:

    1. Kadri Sylejmani & Edon Gashi & Adrian Ymeri, 2023. "Simulated annealing with penalization for university course timetabling," Journal of Scheduling, Springer, vol. 26(5), pages 497-517, October.
    2. Andrea Bettinelli & Valentina Cacchiani & Roberto Roberti & Paolo Toth, 2015. "An overview of curriculum-based course timetabling," TOP: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 23(2), pages 313-349, July.
    3. Johnes, Jill, 2015. "Operational Research in education," European Journal of Operational Research, Elsevier, vol. 243(3), pages 683-696.
    4. Massimiliano Caramia & Stefano Giordani, 2020. "Curriculum-Based Course Timetabling with Student Flow, Soft Constraints, and Smoothing Objectives: an Application to a Real Case Study," SN Operations Research Forum, Springer, vol. 1(2), pages 1-21, June.
    5. Mutsunori Banbara & Katsumi Inoue & Benjamin Kaufmann & Tenda Okimoto & Torsten Schaub & Takehide Soh & Naoyuki Tamura & Philipp Wanko, 2019. "$${\varvec{teaspoon}}$$ teaspoon : solving the curriculum-based course timetabling problems with answer set programming," Annals of Operations Research, Springer, vol. 275(1), pages 3-37, April.
    6. 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.
    7. Geiger, Martin Josef, 2017. "A multi-threaded local search algorithm and computer implementation for the multi-mode, resource-constrained multi-project scheduling problem," European Journal of Operational Research, Elsevier, vol. 256(3), pages 729-741.

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