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Adaptive Tabu Search for course timetabling

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  • Lü, Zhipeng
  • Hao, Jin-Kao

Abstract

This paper presents an Adaptive Tabu Search algorithm (denoted by ATS) for solving a problem of curriculum-based course timetabling. The proposed algorithm follows a general framework composed of three phases: initialization, intensification and diversification. The initialization phase constructs a feasible initial timetable using a fast greedy heuristic. Then an adaptively combined intensification and diversification phase is used to reduce the number of soft constraint violations while maintaining the satisfaction of hard constraints. The proposed ATS algorithm integrates several distinguished features such as an original double Kempe chains neighborhood structure, a penalty-guided perturbation operator and an adaptive search mechanism. Computational results show the high effectiveness of the proposed ATS algorithm, compared with five reference algorithms as well as the current best known results. This paper also shows an analysis to explain which are the essential ingredients of the ATS algorithm.

Suggested Citation

  • 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.
    • Handle: RePEc:eee:ejores:v:200:y:2010:i:1:p:235-244
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    References listed on IDEAS

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    6. 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.
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    Cited by:

    1. Lewis, R. & Thompson, J., 2015. "Analysing the effects of solution space connectivity with an effective metaheuristic for the course timetabling problem," European Journal of Operational Research, Elsevier, vol. 240(3), pages 637-648.
    2. Roberto Asín Achá & Robert Nieuwenhuis, 2014. "Curriculum-based course timetabling with SAT and MaxSAT," Annals of Operations Research, Springer, vol. 218(1), pages 71-91, July.
    3. Rezaei, Mahmood & Shamsaei, Fahimeh & Mohammadian, Iman & Van Vyve, Mathieu, 2012. "A heuristic method to schedule training programs for Small and Medium Enterprises," European Journal of Operational Research, Elsevier, vol. 217(3), pages 600-608.
    4. 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.
    5. Zeng, Zhizhong & Yu, Xinguo & He, Kun & Huang, Wenqi & Fu, Zhanghua, 2016. "Iterated Tabu Search and Variable Neighborhood Descent for packing unequal circles into a circular container," European Journal of Operational Research, Elsevier, vol. 250(2), pages 615-627.
    6. Zhouxing Su & Zhipeng Lü & Zhuo Wang & Yanmin Qi & Una Benlic, 2020. "A Matheuristic Algorithm for the Inventory Routing Problem," Transportation Science, INFORMS, vol. 54(2), pages 330-354, March.
    7. Moritz Mühlenthaler & Rolf Wanka, 2016. "Fairness in academic course timetabling," Annals of Operations Research, Springer, vol. 239(1), pages 171-188, April.
    8. 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.
    9. Lü, Zhipeng & Hao, Jin-Kao, 2012. "Adaptive neighborhood search for nurse rostering," European Journal of Operational Research, Elsevier, vol. 218(3), pages 865-876.
    10. Hao, Jin-Kao & Benlic, Una, 2011. "Lower bounds for the ITC-2007 curriculum-based course timetabling problem," European Journal of Operational Research, Elsevier, vol. 212(3), pages 464-472, August.
    11. 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.
    12. Taoqing Zhou & Zhipeng Lü & Yang Wang & Junwen Ding & Bo Peng, 2016. "Multi-start iterated tabu search for the minimum weight vertex cover problem," Journal of Combinatorial Optimization, Springer, vol. 32(2), pages 368-384, August.
    13. Alexander Kiefer & Richard F. Hartl & Alexander Schnell, 2017. "Adaptive large neighborhood search for the curriculum-based course timetabling problem," Annals of Operations Research, Springer, vol. 252(2), pages 255-282, May.
    14. Soria-Alcaraz, Jorge A. & Ochoa, Gabriela & Sotelo-Figeroa, Marco A. & Burke, Edmund K., 2017. "A methodology for determining an effective subset of heuristics in selection hyper-heuristics," European Journal of Operational Research, Elsevier, vol. 260(3), pages 972-983.
    15. Fu, Zhanghua & Huang, Wenqi & Lü, Zhipeng, 2013. "Iterated tabu search for the circular open dimension problem," European Journal of Operational Research, Elsevier, vol. 225(2), pages 236-243.
    16. 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.
    17. Bhuvnesh Sharma & M. Ramkumar & Nachiappan Subramanian & Bharat Malhotra, 2019. "Dynamic temporary blood facility location-allocation during and post-disaster periods," Annals of Operations Research, Springer, vol. 283(1), pages 705-736, December.
    18. George Henrique Godim Fonseca & Haroldo Gambini Santos & Túlio Ângelo Machado Toffolo & Samuel Souza Brito & Marcone Jamilson Freitas Souza, 2016. "GOAL solver: a hybrid local search based solver for high school timetabling," Annals of Operations Research, Springer, vol. 239(1), pages 77-97, April.
    19. Fabian Dunke & Stefan Nickel, 2023. "A matheuristic for customized multi-level multi-criteria university timetabling," Annals of Operations Research, Springer, vol. 328(2), pages 1313-1348, September.
    20. 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.
    21. 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.

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