A harmony search algorithm for university course timetabling

7th International Conference on the Practice and Theory of Automated Timetabling, PATAT 2008

Volumn , Issue , 2008, Pages

  Al Betar, Mohammed Azmi ^a   Khader, Ahamad Tajudin ^a   Gani, Taufiq Abdul ^a  

^a SCHOOL OF PHYSICS   (Malaysia)

Author keywords

Exploitation; Exploration; Harmony search algorithm; Metaheuristic algorithms; University course timetabling problem

Indexed keywords

BEHAVIORAL RESEARCH; COMPUTATIONAL COMPLEXITY; LEARNING ALGORITHMS; NATURAL RESOURCES EXPLORATION; OPTIMIZATION;

EXPLOITATION; EXPLOITATION AND EXPLORATIONS; HARMONY SEARCH ALGORITHMS; META HEURISTIC ALGORITHM; PARALLEL OPTIMIZATION; POPULATION-BASED ALGORITHM; UNIVERSITY COURSE TIMETABLING; UNIVERSITY COURSE TIMETABLING-PROBLEMS;

SCHEDULING;

EID: 84926400354     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper

References (41)

1. Abdullah S, Burke EK, McCollum B (2005a) Using a randomised iterative improvement algorithm with composite neighbourhood structures for course timetabling. In Proceedings of MIC 05: The 6th Meta-Heuristic International Conference, Vienna, Austria, 22-26 Aug 2005.
2. Abdullah S, Burke EK, Mccollum B (2005b) An investigation of variable neighbourhood search for university course timetabling. Proceedings of MISTA 2005: The 2nd Multidisciplinary Conference on Scheduling: Theory and Applications. NY, USA.
3. Abdullah S, Burke EK, Mccollum B (2007) A hybrid evolutionary approach to the university course timetabling problem. In Proceedings of the IEEE Congress on Evolutionary Computation. Singapore, September 2007.
4. Abramson D (1991) Constructing school timetables using simulated annealing: sequential and parallel algorithms. Management Science 37(1):98–113.
5. Arani T, Lofti JA (1989) A three phased approach to final exam scheduling. IIE Transactions 21(4):86-96.
6. Asmuni H, Burke EK, GARIBALDI J (2005) Fuzzy multiple heuristic ordering for course timetabling. IN AL,S. M. A. E. (Ed.) Proceedings of the 5th United Kingdom Workshop on Computational Intelligence. London, UK, (UKCI05).
7. Brelaz D (1979) New methods to color vertices of a graph. Communications of the ACM 22(4):251–256.
8. Burke EK, Elliman DG, Weare RF (1995) A hybrid genetic algorithm for highly constrained timetabling problems. 6th International Conference on Genetic Algorithms (ICGA’95, Pittsburgh, USA, 15th-19th July 1995). Morgan Kaufmann, San Francisco, CA, USA.
9. Burke EK, Bykov Y, Newall JP et al (2003) A time-predefined approach to course timetabling. Yugoslav Journal of Operations Research 13: 139-151.
10. Burke EK, Elliman DG, Weare RF (1994) A genetic algorithm for university timetabling. In proceedings of the AISB workshop on Evolutionary Computing. University of Leeds, UK.
11. Burke EK, Kingston J, Jackson K et al (1997) Automated university timetabling: the state of the art, The Computer Journal 40 (9): 565-571.
12. Burke EK, Kendall G, Soubeiga E (2003) A tabu-search hyperheuristic for timetabling and rostering. Journal of Heuristics 9(6): 451-470.
13. Burke EK, Mccollum B, Meisels A et al (2007) A Graph-Based Hyper-Heuristic for Educational Timetabling Problems. European Journal of Operational Research 176(1): 177-192.
14. Carter MW, Laporte G, Lee SY (1996) Examination timetabling: algorithmic strategies and applications. Journal of the Operational Research Society 74(3):373-383.
15. Carter MW, Laporte G (1997) Recent developments in practical course timetabling. In: E. Burke, M. Carter (Eds.), the Practice and Theory of Automated Timetabling: Selected Papers from the Second International Conference, Springer Lecture Notes in Computer Science 1408: 3-19.
16. Chiarandini M, Birattari M, Socha K et al (2006) An effective hybrid algorithm for university course timetabling. Journal of Scheduling 9(5):403-432.
17. Colorni A, Dorigo M, Maniezzo V (1990) Genetic algorithms and highly constrained problems: the timetable case. Proceedings of the First International Workshop on Parallel Problem Solving from Nature. Dortmund, Germany, Springer-Verlag,55-59.
18. Duong T, Lam K (2004) Combining constraint programming and simulated annealing on university exam timetabling. In: Proceedings of RIVF 2004 Conference Hanoi,Vietnam.
19. Erben W (2001) A grouping genetic algorithm for graph colouring and exam timetabling. Practice and Theory of Automated Timetabling III: Third International Conference, PATAT 2000 Konstanz, Germany, August 16-18, 2000, Selected Papers.
20. Fang H (1994) Genetic algorithms in timetabling and scheduling. Ph.D. thesis, Department of Artificial Intelligence. University of Edinburgh, Edinburgh, UK.
21. Garey MR, Johnson DS (1979) Computers and intractability: a guide to the theory of NP-completeness. Freeman and Company.New York.
22. Geem ZW (2005) School bus routing using harmony search. In Rothlauf, F. (Ed.) Late breaking paper at Genetic and Evolutionary Computation Conference (GECCO'2005). Washington, D.C., USA.
23. Geem ZW (2006a) Improved harmony search from ensemble of music players. Lecture Notes in Artificial Intelligence 4251:86–93.
24. Geem ZW (2006b) Optimal cost design of water distribution networks using harmony search. Engineering Optimization 38(3):259-280.
25. Geem ZW (2007a) Harmony search algorithm for solving sudoku. Lecture Notes in Artificial Intelligence 4692:371–378.
26. Geem ZW (2007b) Optimal scheduling of multiple dam system using harmony search algorithm. Lecture Notes in Computer Science 4507:316–323.
27. Geem ZW, Kim J, Loganathan G (2001) A new heuristic optimization algorithm: harmony search. Simulation 76(2):60-68.
28. Kostuch P (2005) The university course timetabling problem with a three-phase approach. In Edmund Burke and Michael Trick, editors, Proc. of the 5th Int. Conf. on the Practice and Theory of Automated Timetabling (PATAT-2004 Berlin-Heidelberg), selected papers, Springer Lecture Notes in Computer Science 3616:109–125.
29. Lee KS, Geem ZW (2004) A new structural optimization method based on the harmony search algorithm. Computers and Structures 82(9):781-798.
30. Lewis R (2008) A survey of metaheuristic-based techniques for University Timetabling problems. OR Spectrum 30: 167-190.
31. Lewis R (2006) Metaheuristics for university course timetabling. PhD thesis, School of Computing, Napier University, Edinburgh, October.
32. Lewis R, Paechter B, Mccollum B (2007) Post enrolment based course timetabling: a description of the problem model used for track two of the second international timetabling competition. Cardiff University, Cardiff Business School, Accounting and Finance Section.
33. Lewis R, Paechter B (2005) Application of the grouping genetic algorithm to university course timetabling. in Evolutionary Computation in Combinatorial Optimisation (EVOCop) V. G. Raidl and J. Gottlieb Eds.Berlin, Germany: Springer-Verlag, 2005. LectureNotes in Computer Science 3448: 144-153.
34. Lewis R, Paechter B (2004) New crossover operators for timetabling with evolutionary algorithms. In:Lofti A (ed) The fifth international conference on recent advances in soft computing RASC2004. Nottingham, England.
35. Marco C, Mauro B, Krzysztof S et al (2006) An effective hybrid algorithm for university course timetabling. Journal of Scheduling. 9(5): 403-432.Doi: 10.1007/s10951-006-8495-8.
36. Malim MR, Khader AT, Mustafa A (2006) Artificial immune algorithms for university timetabling. Proceedings of the 6th International Conference on the Practice & Theory of Automated Timetabling (PATAT 2006). 30 Ogos – 1 September 2006, Czech Republic.
37. Ross P, Hart E, Corne D (1998) Some observations about GA-based exam timetabling. In: E.K. Burke and M. Carter (eds.), LNCS 1408, Practice and Theory of Automated Timetabling II: Second International Conference, PATAT 1997, Toronto, Canada, selected papers. Springer-Verlag,115–129.
38. Socha K, Knowles J and Samples M (2002) A max-min ant system for the university course timetabling problem. Proceedings of the 3rd International Workshop on Ant Algorithms (ANTS 2002), Springer Lecture Notes in Computer Science 2463:1-13.
39. Thanh ND (2007) Solving timetabling problem using genetic and heuristic algorithms. Software Engineering, Artificial Intelligence, Networking, and Parallel/Distributed Computing, 2007. SNPD 2007. Eighth ACIS International Conference.
40. Thompson GL, Dowsland KA(1996) Variants of Simulated Annealing for the Examination Timetabling Problem. Annals of Operations Research 63(1):105-128.
41. Tuga M, Berretta R, Mendes A (2007) A Hybrid simulated annealing with kempe chain neighborhood for the university timetabling problem. Computer and Information Science, 2007. ICIS 2007. 6th IEEE/ACIS International Conference.