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Ant Algorithms for the Exam Timetabling Problem

  • Conference paper
Practice and Theory of Automated Timetabling VI (PATAT 2006)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 3867))

Abstract

Scheduling exams at universities can be formulated as a combinatorial optimization problem. Basically one has to schedule a certain number of exams in a given number of time periods so that a predetermined objective function is minimized. In particular, the objective function penalizes schedules where students have to write exams in consecutive periods or even in the same period. Ant colony approaches have been demonstrated to be a powerful solution approach for various combinatorial optimization problems. This paper presents two ant colony approaches for the exam timetabling problem, a Max–Min and an ANTCOL approach. Using the Toronto benchmark test cases from the literature, both algorithms arc compared to other timetabling heuristics. Finally, the Max–Min and ANTCOL algorithms are compared using the same set of test cases. In spite of some shortcomings, the ANTCOL approach turned out to be a worthwhile algorithm, among the best currently in use for examination timetabling.

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References

  1. Abdullah, S., Ahmadi, S., Burke, E.K., Dror, M.: Investigating Ahuja–Orlins large neighbourhood search for examination timetabling. OR Spectrum 29, 331–372 (2007)

    Article  Google Scholar 

  2. Asmuni, H., Burke, E.K., Garibaldi, J., McCollum, B.: Fuzzy multiple ordering criteria for examination timetabling. In: Burke, E.K., Trick, M.A. (eds.) PATAT 2004. LNCS, vol. 3616, pp. 334–353. Springer, Heidelberg (2005)

    Chapter  Google Scholar 

  3. Ayob, M., Burke, E.K., Kendall, G.: An iterative re-start variable neighbourhood search for the examination timetabling problem. In: Proceedings of the 6th International Conference on the Practice and Theory of Automated Timetabling, Brno, pp. 336–344 (August 2006)

    Google Scholar 

  4. Blum, C.: Theoretical and Practical Aspects of Ant Colony Optimization. Akademische Verlagsgesellschaft, Berlin (2004)

    Google Scholar 

  5. Burke, E.K., Bykov, Y.: Solving exam timetabling problems with the flex-deluge algorithm. In: Proceedings of the 6th International Conference on the Practice and Theory of Automated Timetabling, Brno, pp. 370–372 (August 2006)

    Google Scholar 

  6. Burke, E.K., Bykov, Y., Newall, J.P., Petrovic, S.: A time-predefined local search approach to exam timetabling problems. IIE Transactions 36, 509–528 (2004)

    Article  Google Scholar 

  7. Burke, E.K., Eckersley, A.J., McCollum, B., Petrovic, S., Qu, R.: Hybrid variable neighbourhood approaches to university exam timetabling. Technical Report NOTTCS-TR-2006-2, University of Nottingham (2006)

    Google Scholar 

  8. Burke, E.K., Elliman, D.G., Ford, P.H., Weare, R.F.: Examination timetabling in British universities: A survey. In: Burke, E.K., Ross, P. (eds.) Practice and Theory of Automated Timetabling. LNCS, vol. 1153, pp. 76–92. Springer, Heidelberg (1996)

    Google Scholar 

  9. Burke, E.K., McCollum, B., Meisels, A., Petrovic, S., Qu, R.: A graph based hyper-heuristic for exam timetabling problems. European Journal of Operational Research 176, 177–192 (2007)

    Article  MATH  MathSciNet  Google Scholar 

  10. Burke, E.K., Newall, J.P.: Enhancing timetable solutions with local search methods. In: Burke, E.K., De Causmaecker, P. (eds.) PATAT 2002. LNCS, vol. 2740, pp. 195–206. Springer, Heidelberg (2003)

    Google Scholar 

  11. Burke, E.K., Newall, J.P.: Solving examination timetabling problems through adaptation of heuristic orderings. Annals of Operational Research 129, 107–134 (2004)

    Article  MATH  MathSciNet  Google Scholar 

  12. Caramia, M., Dell’Olmo, P., Italiano, G.F.: New algorithms for examination timetabling. In: Swierstra, S.D. (ed.) PLILP 1995. LNCS, vol. 982, pp. 230–241. Springer, Heidelberg (1995)

    Google Scholar 

  13. Carter, M.W., Laporte, G.: Recent developments in practical examination timetabling. In: Burke, E.K., Ross, P. (eds.) Practice and Theory of Automated Timetabling. LNCS, vol. 1153, pp. 3–21. Springer, Heidelberg (1996)

    Google Scholar 

  14. Carter, M.W., Laporte, G., Lee, S.Y.: Examination timetabling algorithmic strategies and applications. Journal of the Operational Research Society 47, 373–383 (1996)

    Article  Google Scholar 

  15. Casey, S., Thompson, J.: Grasping the examination scheduling problem. In: Burke, E.K., De Causmaecker, P. (eds.) PATAT 2002. LNCS, vol. 2740, pp. 233–244. Springer, Heidelberg (2003)

    Google Scholar 

  16. Colorni, A., Dorigo, M., Maniezzo, V.: Distributed optimization by ant colonies. In: Proceedings of the 1st European Conference on Artificial Life, pp. 134–142. Elsevier, Amsterdam (1992)

    Google Scholar 

  17. Costa, D., Hertz, A.: Ants can color graphs. Journal of the Operational Research Society 48, 295–305 (1997)

    Article  MATH  Google Scholar 

  18. Cote, P., Wong, T., Sabouri, R.: Application of a hybrid multi-objective evolutionary algorithm to the uncapacitated exam proximity problem. In: Burke, E.K., Trick, M.A. (eds.) PATAT 2004. LNCS, vol. 3616, pp. 151–168. Springer, Heidelberg (2005)

    Google Scholar 

  19. Di Gaspero, L.: Recolour, shake and kick: A recipe for the examination timetabling problem. In: Burke, E.K., De Causmaecker, P. (eds.) PATAT 2002. LNCS, vol. 2740, Springer, Heidelberg (2003)

    Google Scholar 

  20. Di Gaspero, L., Schaerf, A.: Tabu search techniques for examination timetabling. In: Burke, E., Erben, W. (eds.) PATAT 2000. LNCS, vol. 2079, pp. 104–117. Springer, Heidelberg (2001)

    Chapter  Google Scholar 

  21. Dorigo, M., Di Caro, G., Gambarella, L.M.: Ant algorithms for discrete optimization. Artificial Life 5, 137–172 (1999)

    Article  Google Scholar 

  22. Dowsland, K., Thompson, J.: Ant colony optimisation for the examination scheduling problem. Journal of the Operational Research Society 56, 426–439 (2005)

    Article  MATH  Google Scholar 

  23. Garey, M.R., Johnson, D.S.: Computers and Intractability: A Guide to the Theory of NP-Completeness. Freeman, New York (1979)

    MATH  Google Scholar 

  24. Kendall, G., Hussin, N.M.: A tabu search hyper-heuristic approach to the examination timetabling problem at the Mara University of Technology. In: Burke, E.K., Trick, M.A. (eds.) PATAT 2004. LNCS, vol. 3616, pp. 199–218. Springer, Heidelberg (2005)

    Chapter  Google Scholar 

  25. Manfrin, M., Birattari, M., Stuetzle, T., Dorigo, M.: Parallel ant colony optimization for the traveling salesman problem. In: Dorigo, M., Gambardella, L.M., Birattari, M., Martinoli, A., Poli, R., Stützle, T. (eds.) ANTS 2006. LNCS, vol. 4150, pp. 224–234. Springer, Heidelberg (2006)

    Chapter  Google Scholar 

  26. Merkle, M., Middendorf, M.: An ant algorithm with a new pheromone evaluation rule for total tardiness problems. In: Oates, M.J., Lanzi, P.L., Li, Y., Cagnoni, S., Corne, D.W., Fogarty, T.C., Poli, R., Smith, G.D. (eds.) EvoIASP 2000, EvoWorkshops 2000, EvoFlight 2000, EvoSCONDI 2000, EvoSTIM 2000, EvoTEL 2000, and EvoROB/EvoRobot 2000. LNCS, vol. 1803, pp. 287–296. Springer, Heidelberg (2000)

    Chapter  Google Scholar 

  27. Merlot, L.T.G., Boland, N., Hughes, P.J., Stuckey, B.D.: A hybrid algorithm for the examination timetabling problem. In: Burke, E.K., De Causmaecker, P. (eds.) PATAT 2002. LNCS, vol. 2740, pp. 207–231. Springer, Heidelberg (2003)

    Google Scholar 

  28. Naji Azimi, Z.: Comparison of metaheuristic algorithms for examination timetabling problem. Applied Mathematics and Computation 16, 337–354 (2004)

    Article  MATH  MathSciNet  Google Scholar 

  29. Naji Azimi, Z.: Hybrid heuristics for examination timetabling problem. Applied Mathematics and Computation 163, 705–733 (2005)

    Article  MATH  MathSciNet  Google Scholar 

  30. Paquete, L., Stuetzle, T.: Empirical analysis of tabu search for the lexicographic optimization of the examination timetabling problem. In: Burke, E.K., De Causmaecker, P. (eds.) PATAT 2002. LNCS, vol. 2740, pp. 413–420. Springer, Heidelberg (2003)

    Google Scholar 

  31. Socha, K., Knowles, J., Samples, M.: A max–min ant system for the university course timetabling problem. In: Dorigo, M., Di Caro, G.A., Sampels, M. (eds.) Ant Algorithms. LNCS, vol. 2463, pp. 1–13. Springer, Heidelberg (2002)

    Chapter  Google Scholar 

  32. Socha, K., Sampels, M., Manfrin, M.: Ant algorithms for the university course timetabling problem with regard to state-of-the-art. In: Raidl, G.R., Cagnoni, S., Cardalda, J.J.R., Corne, D.W., Gottlieb, J., Guillot, A., Hart, E., Johnson, C.G., Marchiori, E., Meyer, J.-A., Middendorf, M. (eds.) EvoCOP 2003. LNCS, vol. 2611, pp. 334–345. Springer, Heidelberg (2003)

    Google Scholar 

  33. Stuetzle, T., Hoos, H.H.: Max–min ant systems. Future Generation Computer Systems 16, 889–914 (2000)

    Article  Google Scholar 

  34. http://www.cs.nott.ac.uk/~rxq/data.htm

  35. http://www.or.ms.unimelb.edu.au/timetabling

  36. http://www.fh-aschaffenburg.de/index.php?idlogdown

  37. Qu, R., Burke, E.K., McCollum, B., Merlot, L.T.G., Lee, S.Y.: A survey of search methodologies and automated approaches for examination timetabling. Computer Science Technical Report No. NOTTCS-TR-2006-4, University of Nottingham (2006)

    Google Scholar 

  38. Vesel, A., Zerovni, J.: How well can ants color graphs? Journal of Computing and Information Technology (CIT) 8, 131–136 (2000)

    Article  Google Scholar 

  39. White, G.M., Xie, B.S.: Examination timetabling and tabu search with longer-term memory. In: Burke, E., Erben, W. (eds.) PATAT 2000. LNCS, vol. 2079, pp. 85–103. Springer, Heidelberg (2001)

    Chapter  Google Scholar 

  40. White, G.M., Xie, B.S., Zonjic, S.: Using tabu search with long-term memeory and relaxation to create examination timetables. European Journal of Operational Research 153, 80–91 (2004)

    Article  MATH  MathSciNet  Google Scholar 

  41. Yang, Y., Petrovic, S.: A novel similarity measure for heuristic selection in examination timetabling. In: Burke, E.K., Trick, M.A. (eds.) PATAT 2004. LNCS, vol. 3616, pp. 377–396. Springer, Heidelberg (2005)

    Chapter  Google Scholar 

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Authors and Affiliations

  1. Aschaffenburg University of Applied Science, Logistics Laboratory (LlAb), Aschaffenburg, Germany

    Michael Eley

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  1. Michael Eley
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Edmund K. Burke Hana Rudová

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Eley, M. (2007). Ant Algorithms for the Exam Timetabling Problem. In: Burke, E.K., Rudová, H. (eds) Practice and Theory of Automated Timetabling VI. PATAT 2006. Lecture Notes in Computer Science, vol 3867. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-77345-0_23

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  • DOI: https://doi.org/10.1007/978-3-540-77345-0_23

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-77344-3

  • Online ISBN: 978-3-540-77345-0

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