A Harmony Search with Multi-pitch Adjusting Rate for the University Course Timetabling

1. Burke, E.K., Jackson, K., Kingston, J.H., Weare, R.: Automated university timetabling: The state of the art. The Computer Journal 40, 565–571 (1997)

   Article  Google Scholar 

2. Schaerf, A.: A Survey of Automated Timetabling. Artif. Intelli. Rev. 13, 87–127 (1999)

   Article  Google Scholar 

3. Wood, D.: A technique for colouring a graph applicable to large scale timetabling problems. The Computer Journal 12, 317–319 (1969)

   Article  MATH  MathSciNet  Google Scholar 

4. Asmuni, H., Burke, E.K., Garibaldi, J.: Fuzzy Multiple Heuristic Ordering for Course Timetabling. In: al-SMAe (ed.) Proceedings of the 5th United Kingdom Workshop on Computational Intelligence (UKCI 2005), London, UK, pp. 302–309 (2005)

   Google Scholar 

5. Abdullah, S., Burke, E.K., McCollum, B.: A Hybrid Evolutionary Approach to the University Course Timetabling Problem. In: Proceedings of the IEEE Congress on Evolutionary Computation, Singapore, September 2007, pp. 1764–1768 (2007)

   Google Scholar 

6. Burke, E.K., Kendall, G., Soubeiga, E.: A Tabu-Search Hyperheuristic for Timetabling and Rostering. Journal of Heuristics 9, 451–470 (2003)

   Article  Google Scholar 

7. Burke, E.K., McCollum, B., Meisels, A., Petrovic, S., Qu, R.: A graph-based hyper-heuristic for educational timetabling problems. Eur. J. Opl. Res. 176, 177–192 (2007)

   Article  MATH  MathSciNet  Google Scholar 

8. Lewis, R., Paechter, B., Rossi-Doria, O.: Metaheuristics for University Course Timetabling, Ph.D. Thesis (August 2006)

   Google Scholar 

9. Lewis, R.: A survey of metaheuristic-based techniques for University Timetabling problems. OR Spectrum 30, 167–190 (2008)

   Article  MATH  Google Scholar 

10. Blum, C., Roli, A.: Metaheuristics in combinatorial optimization: Overview and conceptual comparison. ACM Comput. Surv. 35, 268–308 (2003)

    Article  Google Scholar 

11. Lewis, R., Paechter, B.: New crossover operators for timetabling with evolutionary algorithms. In: Lofti, A. (ed.) The fifth international conference on recent advances in soft computing (RASC 2004), Nottingham, England, pp. 189–194 (2004)

    Google Scholar 

12. Socha, K., Joshua, K., Michael, S.: A MAX-MIN Ant System for the University Course Timetabling Problem. In: Dorigo, M., Di Caro, G.A., Sampels, M. (eds.) Ant Algorithms 2002. LNCS, vol. 2463, pp. 1–13. Springer, Heidelberg (2002)

    Chapter  Google Scholar 

13. Malim, M.R., Khader, A.T., Mustafa, A.: Artificial Immune Algorithms for University Timetabling. In: Burke, E.K., Rudova, H. (eds.) The 6th International Conference on Practice and Theory of Automated Timetabling, Brno, Czech Republic, pp. 234–245 (2006)

    Google Scholar 

14. Al-Betar, M.A., Khader, A.T., Gani, T.A.: A harmony search algorithm for university course timetabling. In: 7th International Conference on the Practice and Theory of Automated Timetabling (PATAT 2008), Montreal, Canada, August 18-22 (2008)

    Google Scholar 

15. Thompson, J., Dowsland, K.: Variants of simulated annealing for the examination timetabling problem. Annals of Operations Research 63, 105–128 (1996)

    Article  MATH  Google Scholar 

16. Chiarandini, M., Birattari, M., Socha, K., Rossi-Doria, O.: An effective hybrid algorithm for university course timetabling. J. of Scheduling 9, 403–432 (2006)

    Article  MATH  MathSciNet  Google Scholar 

17. Rossi-Doria, O., Blum, C., Knowles, J., Sampels, M., Socha, K., Paechter, B.: A local search for the timetabling problem. In: Proceedings of the 4th International Conference on the Practice And Theory of Automated Timetabling (PATAT 2002), August 2002, pp. 124–127 (2002)

    Google Scholar 

18. Abdullah, S., Burke, E., McCollum, B.: Using a Randomised Iterative Improvement Algorithm with Composite Neighbourhood Structures for the University Course Timetabling Problem. Metaheuristics, 153–169 (2007)

    Google Scholar 

19. Abdullah, S., Burke, E.K., McCollum, B.: An Investigation of Variable Neighbourhood Search for University Course Timetabling. In: Proceedings of the 2nd Multidisciplinary Conference on Scheduling: Theory and Applications (MISTA), New York, USA, pp. 413–427 (2005)

    Google Scholar 

20. Landa-Silva, D., Obit, J.H.: Great deluge with non-linear decay rate for solving course timetabling problems Intelligent Systems. In: Proceedings of the 4th International IEEE Conference on Intelligent Systems, pp. 8-11-18-18 (2008)

    Google Scholar 

21. McMullan, P.: An extended implementation of the great deluge algorithm for course timetabling. In: Shi, Y., van Albada, G.D., Dongarra, J., Sloot, P.M.A. (eds.) ICCS 2007. LNCS, vol. 4487, pp. 538–545. Springer, Heidelberg (2007)

    Chapter  Google Scholar 

22. Qu, R., Burke, E.K., McCullom, B., Merlot, L.T.G., Lee, S.Y.: A survey of search methodologies and automated approaches for examination timetabling. Journal of Scheduling 12, 55–89 (2009)

    Article  MATH  MathSciNet  Google Scholar 

23. Abdullah, S., Turabieh, H.: Generating university course timetable using genetic algorithms and local search. In: The Third 2008 International Conference on Convergence and Hybrid Information Technology (ICCIT), pp. 254–260 (2008)

    Google Scholar 

24. Al-Betar, M.A., Khader, A.: A hybrid harmony search for university course timetabling. In: Proceedings of the 4nd Multidisciplinary Conference on Scheduling: Theory and Applications (MISTA 2009), Dublin, Ireland, August 10-12, pp. 157–179 (2009)

    Google Scholar 

25. Landa-Silva, D., Obit, J.: Evolutionary Non-linear Great Deluge for University Course Timetabling. In: Corchado, E., et al. (eds.) HAIS 2009. LNCS (LNAI), vol. 5572, pp. 269–276. Springer, Heidelberg (2009)

    Google Scholar 

26. Carter, M.W., Laporte, G.: Recent developments in practical course timetabling. In: Burke, E.K., Carter, M. (eds.) PATAT 1997. LNCS, vol. 1408, pp. 3–19. Springer, Heidelberg (1998)

    Chapter  Google Scholar 

27. Al-Betar, M.A., Khader, A.: A Harmony Search Algorithm for University Course Timetabling. Annals of Operations Research (to appear)

    Google Scholar 

28. Geem, Z.W., Kim, J.H., Loganathan, G.V.: A new heuristic optimization algorithm: harmony search. Simulation 76, 60–68 (2001)

    Article  Google Scholar 

29. Eberhart, R., Kennedy, J.: A new optimizer using particle swarm theory. In: Proceedings of 6th International Symposium on Micro Machine and Human Science (MHS 1995), pp. 39–43 (1995)

    Google Scholar 

30. Lee, K.S., Geem, Z.W.: A new structural optimization method based on the harmony search algorithm. Computers & Structures 82, 781–798 (2004)

    Article  Google Scholar 

31. Obit, J.H., Landa-Silva, D., Ouelhadj, D., Sevaux, M.: Non-Linear Great Deluge with Learning Mechanism for Solving the Course Timetabling Problem. In: The 8th Metaheuristics International Conference (MIC 2009), Hamburg, Germany (July 2009)

    Google Scholar 

32. Turabieh, H., Abdullah, S., McCollum, B.: Electromagnetism-like Mechanism with Force Decay Rate Great Deluge for the Course Timetabling Problem. In: RSKT 2009. LNCS, vol. 5589, pp. 497–504. Springer, Heidelberg (2009)

    Google Scholar 

Download references