A harmony search with multi-pitch adjusting rate for the university course Timetabling

Studies in Computational Intelligence

Volumn 270, Issue , 2010, Pages 147-161

  Al Betar, Mohammed Azmi ^a   Khader, Ahamad Tajudin ^a   Liao, Iman Yi ^a  

^a SCHOOL OF PHYSICS   (Malaysia)

Author keywords

[No Author keywords available]

Indexed keywords

EID: 75749086795     PISSN: 1860949X     EISSN: None     Source Type: Book Series    
DOI: 10.1007/978-3-642-04317-8_13     Document Type: Article

References (32)

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)
2. Schaerf, A.: A Survey of Automated Timetabling. Artif. Intelli. Rev. 13, 87-127 (1999)
3. Wood, D.: A technique for colouring a graph applicable to large scale timetabling problems. The Computer Journal 12, 317-319 (1969)
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)
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)
6. Burke, E.K., Kendall, G., Soubeiga, E.: A Tabu-Search Hyperheuristic for Timetabling and Rostering. Journal of Heuristics 9, 451-470 (2003)
7. Burke, E.K., McCollum, B., Meisels, A., Petrovic, S., Qu, R.: A graph-based hyperheuristic for educational timetabling problems. Eur. J. Opl. Res. 176, 177-192 (2007)
8. Lewis, R., Paechter, B., Rossi-Doria, O.: Metaheuristics for University Course Timetabling, Ph.D. Thesis (August 2006)
9. Lewis, R.: A survey of metaheuristic-based techniques for University Timetabling problems. OR Spectrum 30, 167-190 (2008)
10. Blum, C., Roli, A.: Metaheuristics in combinatorial optimization: Overview and conceptual comparison. ACM Comput. Surv. 35, 268-308 (2003)
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)
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)
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)
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)
15. Thompson, J., Dowsland, K.: Variants of simulated annealing for the examination timetabling problem. Annals of Operations Research 63, 105-128 (1996)
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)
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)
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)
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)
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)
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)
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)
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)
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)
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)
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)
27. Al-Betar, M.A., Khader, A.: A Harmony Search Algorithm for University Course Timetabling. Annals of Operations Research (to appear)
28. Geem, Z.W., Kim, J.H., Loganathan, G.V.: A new heuristic optimization algorithm: harmony search. Simulation 76, 60-68 (2001)
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)
30. Lee, K.S., Geem, Z.W.: A new structural optimization method based on the harmony search algorithm. Computers & Structures 82, 781-798 (2004)
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)
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)