An integrated hybrid approach to the examination timetabling problem

Omega

Volumn 39, Issue 6, 2011, Pages 598-607

  Turabieh, Hamza ^a   Abdullah, Salwani ^a  

^a UNIVERSITI KEBANGSAAN MALAYSIA   (Malaysia)

Author keywords

Examination timetabling; Great deluge approach; Heuristics; Metaheuristics

Indexed keywords

DECAY (ORGANIC);

AUTOMATED APPROACH; EXAMINATION TIMETABLING; GREAT DELUGE ALGORITHMS; GREAT DELUGE APPROACH; HEURISTIC; HEURISTIC OPERATORS; HYBRID APPROACH; METAHEURISTIC; PERFORMANCE; TIMETABLING PROBLEM;

HEURISTIC METHODS;

EID: 79953160887     PISSN: 03050483     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.omega.2010.12.005     Document Type: Article

References (69)

1. Schaerf A. A survey of automated timetabling. Artificial Intelligence Review 1999, 13(2):87-127.
2. Lewis R. A survey of metaheuristic-based techniques for university timetabling problems. OR Spectrum 2008, 30(1):167-190.
3. Burke E.K., Petrovic S. Recent research directions in automated timetabling. European Journal of Operational Research 2002, 140(2):266-280.
4. Petrovic S., Burke E.K. University timetabling. Handbook of scheduling: algorithms, models, and performance analysis 2004, CRC Press, Boca Raton, [chapter 45]. J. Leung (Ed.).
5. Bardadym V.A. Computer-aided school and university timetabling: the new wave. Lecture notes in computer science: vol. 1153. Practice and theory of automated timetabling, I: selected papers from the 1st international conference 1996, 22-45. Springer, Berlin.
6. de Werra D. An introduction to timetabling. European Journal of Operational Research 1985, 19:151-162.
7. Burke E.K., De Causmaecker P., Vanden Berghe G., Van Landeghem H. The state of the art of nurse rostering. Journal of Scheduling 2004, 7(6):441-499.
8. Easton K., Nemhauser G., Trick M. Sports scheduling. Handbook of scheduling: algorithms, models, and performance analysis 2004, CRC Press, Boca Raton, [chapter 52]. J. Leung (Ed.).
9. Drexl A., Knust S. Sports league scheduling: graph- and resource-based models. The International Journal of Management Science (Omega) 2007, 35(5):465-471.
10. Kwan R. Bus and train driver scheduling. Handbook of scheduling: algorithms, models, and performance 2004, CRC Press, Boca Ratom, [chapter 51]. J. Leung (Ed.).
11. Caramia M., Guerriero F. A heuristic approach to long-haul freight transportation with multiple objective functions. The International Journal of Management Science (Omega) 2009, 37(3):600-614.
12. Adlakha V., Kowalski K., Lev B. A branching method for the fixed charge transportation problem. The International Journal of Management Science (Omega) 2010, 38(5):393-397.
13. Yang S.-J., Yang D.-L. Minimizing the makespan on single-machine scheduling with aging effect and variable maintenance activities. The International Journal of Management Science (Omega) 2010, 38(6):528-533.
14. Lee W.-C., Wu C.-C., Hsu P.-H. A single-machine learning effect scheduling problem with release times. The International Journal of Management Science (Omega) 2010, 38(1-2):3-11.
15. Laha D., Sarin S. A heuristic to minimize total flow time in permutation flow shop. The International Journal of Management Science (Omega) 2009, 37(3):734-739.
16. Li X., Wang Q., Wu C. Efficient composite heuristics for total flowtime minimization in permutation flow shops. The International Journal of Management Science (Omega) 2009, 37(1):155-164.
17. Ribas I., Companys R., Tort-Martorell X. An iterated greedy algorithm for the flowshop scheduling problem with blocking. The International Journal of Management Science (Omega) 2011, 39(3):293-301.
18. Qu R., Burke E.K., McCollum B., Merlot L., Lee S. A survey of search methodologies and automated system development for examination timetabling. Journal of Scheduling 2009, 12(1):55-89.
19. Qu R., Burke E.K., McCollum B. Adaptive automated construction of hybrid heuristics for exam timetabling and graph colouring problems. European Journal of Operational Research 2009, 198(2):392-404.
20. Carter MW, Laporte G. Recent developments in practical examination timetabling. In: Lecture notes in computer science: vol. 1153. Selected papers from the 1st international conference on practice and theory of automated timetabling. Berlin: Springer; 1996. p. 373-83.
21. Carter M.W. A survey of practical applications of examination timetabling algorithms. Operations Research Society of America 1986, 34(2):193-202.
22. Balakrishnan N. Examination scheduling: a computerized application. The International Journal of Management Science (Omega) 1991, 19(1):37-41.
23. Weitz, Lakshminarayanan An empirical comparison of heuristic and graph theoretic methods for creating maximally diverse groups VLSI, design and exam scheduling. Omega 1997, 25(4):473-482.
24. Carter M.W., Laporte G., Lee S. Examination timetabling: algorithmic strategies and applications. Journal of the Operational Research Society 1996, 47(3):373-383.
25. Merlot L.T.G., Boland N., Hughes B.D., Stuckey P.J. A hybrid algorithm for the examination timetabling problem. Lecture notes in computer science: vol. 2740. Practice and theory of automated timetabling, IV: selected papers from the 4th international conference 2003, 207-231. Springer, Berlin.
26. Müller T. ITC2007 solver description: a hybrid approach. Annals of Operation Research 2009, 172(1):429-446.
27. White G.M., Xie B.S., Zonjic S. Using tabu search with longer-term memory and relaxation to create examination timetables. European Journal of Operational Research 2004, 153(16):80-91.
28. Di Gaspero L., Schaerf A. Tabu search techniques for examination timetabling. Lecture notes in computer science: vol. 2079. Practice and theory of automated timetabling, III: selected papers from the 3rd international conference 2001, 104-117. Springer, Berlin.
29. Atsuta M, Nonobe K, Ibaraki T. ITC2007 Track 1: an approach using general CSP solver. (2007). http://www.cs.qub.ac.uk/itc2007.
30. Duong TA, Lam KH. Combining constraint programming and simulated annealing on university exam timetabling. In: Proceedings of the 2nd international conference in computer sciences, research, innovation & vision for the future (RIVF2004), Hanoi, Vietnam, 2-5 February 2004. p. 205-10.
31. CÔté P., Wong T., Sabouri R. Application of a hybrid multiobjective evolutionary algorithm to the uncapacitated exam proximity problem. Lecture notes in computer science: vol. 3616. Practice and theory of automated timetabling, V: selected papers from the 5th international conference 2005, 151-168. Springer, Berlin.
32. Dowsland K.A., Thompson J. Ant colony optimization for the examination scheduling problem. Journal of Operational Research Society 2005, 56:426-438.
33. Burke E.K., Bykov Y., Newall J.P., Petrovic S. A time predefined local search approach to exam timetabling problems. IIE Transactions 2004, 36(6):509-528.
34. Burke E.K., Newall J.P. Enhancing timetable solutions with local search methods. Lecture notes in computer science: vol. 2740. Practice and theory of automated timetabling, IV: selected papers from the 4th international conference 2003, 195-206. Springer, Berlin.
35. Burke E.K., Newall J.P. Enhancing timetable solutions with local search methods, practice and theory of automated timetabling iv: selected revised papers from the 4th international conference on the practice and theory of automated timetabling (PATAT 2002), Gent, Belgium, 21-23 August 2002. Lecture Notes in Computer Science 2003, vol. 2740:195-206. Springer, Berlin.
36. McCollum B, McMullan PJ, Parkes AJ, Burke EK, Abdullah S. An extended great deluge approach to the examination timetabling problem. In: MISTA09, The 4th multidisciplinary international conference on scheduling: theory and applications, Dublin, August, 2009. p. 424-34.
37. Casey S., Thompson J. GRASPing the examination scheduling problem. Lecture notes in computer science: vol. 2740. Practice and theory of automated timetabling, IV: selected papers from the 4th international conference 2003, 232-244. Springer, Berlin.
38. Gogos C, Alefragis P, Housos E. A multi-staged algorithmic process for the solution of the examination timetabling problem. In: Practice and theory of automated timetabling (PATAT 2008), Montreal, 2008, p. 19-22.
39. Burke E.K., Petrovic S., Qu R. Case-based heuristic selection for timetabling problems. Journal of Scheduling 2006, 9:115-132.
40. Yang Y., Petrovic S. A novel similarity measure for heuristic selection in examination timetabling. Lecture notes in computer science: vol. 3616. Practice and theory of automated timetabling, V: selected papers from the 5th international conference 2005, 377-396. Springer, Berlin.
41. Pillay A. Developmental approach to the examination timetabling problem 〈〉, 2007. http://www.cs.qub.ac.uk/itc2007.
42. Abdullah S., Ahmadi S., Burke E.K., Dror M. Investigating Ahuja-Orlin's large neighbourhood search approach for examination timetabling. OR Spectrum 2007, 29(2):351-372.
43. Abdullah S., Ahmadi S., Burke E.K., Dror M., McCollum B. A tabu based large neighbourhood search methodology for the capacitated examination timetabling problem. Journal of Operational Research Society 2007, 58:1494-1502.
44. Meyers C., Orlin J.B. Very large-scale neighborhood search techniques in timetabling problems. Practice and theory of automated timetabling, VI: selected papers from the 6th international conference, PATAT 2006, Lecture notes in computer science 2007, vol. 3867:24-39. Springer, Berlin.
45. Burke E.K., Eckersley A.J., McCollum B., Petrovic S., Qu R. Hybrid variable neighbourhood approaches to university exam timetabling. European Journal of Operation Research 2010, 206(1):46-53.
46. Caramia M., Dellolmo P., Italiano G.F. Novel local search-based approaches to university examination timetabling. INFORMS Journal on Computing 2009, 20(1):86-99.
47. Bilgin B., Ozcan E., Korkmaz E.E. An experimental study on hyperheuristics and exam timetabling. Practice and theory of automated timetabling: selected papers from the 6th international conference. Lecture notes in computer science 2007, vol. 3867:394-412. Springer, Berlin.
48. 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 2007, 176:177-192.
49. Qu R., Burke E.K. Hybridisations within a graph based hyper-heuristic framework for university timetabling problems. Journal of the Operational Research Society 2009, 60:1273-1285.
50. McCollum B. A perspective on bridging the gap between theory and practice in university timetabling. Lecture notes in computer science: vol. 3867. Practice and theory of automated timetabling, VI: selected papers from the 6th international conference 2007, 3-23. Springer, Berlin.
51. McCollum B., Schaerf A., Paechter B., McMullan P., Lewis R., Parkes A.J., et al. Setting the research agenda in automated timetabling: the second international timetabling competition. INFORMS Journal on Computing 2010, 22:120-130.
52. Burke E.K., Elliman D.G., Ford P.H., Weare R.F. Examination timetabling in British universities: a survey. Lecture notes in computer science: vol. 1153. Practice and theory of automated timetabling, I: selected papers from the 1st international conference 1996, 76-90. Springer, Berlin.
53. Dueck G. New optimization heuristics: the great deluge and the record-to-record travel. Journal of Computational Physics 1993, 104:86-92.
54. Burke E.K., Bykov Y., Newall J.P., Petrovic S. A Time-predefined approach to course timetabling. Yugoslav Journal of Operational Research (YUJOR) 2003, 13(2):139-151.
55. Birbil S.I., Fang S.-C. An electromagnetism-like mechanism for global optimization. Journal of Global Optimization 2003, 25:263-282.
56. Burke EK, Kendall G. In: Burke EK, Kendall G, editors. Search methodologies: introductory tutorials in optimization and decision support techniques. Springer; 2005. p. 5-18 [chapter 1].
57. Kennedy J, Eberhart RC. Particle swarm optimization. In Proceedings of the IEEE international conerence on neural networks, Piscataway, NJ, 1995. p. 1942-48.
58. Tavakkoli-Moghaddam R., Khalili M., Naderi B. Electromagnetism-like mechanism and simulated annealing algorithms for flowshop scheduling problems minimizing the total weighted tardiness and makespan. Knowledge-Based Systems 2009, 23(2):77-85.
59. Yurtkuran A., Emel E. A new hybrid electromagnetism-like Algorithm for capacitated vehicle routing problems. Expert Systems with Applications 2010, 37(4):3427-3433.
60. Jhang Jhen-Yan, Lee Kun-Chou Array pattern optimization using electromagnetism-like algorithm. AEU-International Journal of Electronics and Communications 2009, 491-496.
61. Tsou C-S, Kao C-H. An electromagnetism-like meta-heuristic for multi-objective optimization. In: Proceedings of the 2006 IEEE congress on evolutionary computation, 2006, p. 1172-8.
62. Gol Alikhani M., Javadian N., Tavakkoli-Moghaddam R. A novel hybrid approach combining electromagnetism-like method with Solis and Wets local search for continuous optimization problems. Journal of Global Optimization 2009, 44(2):227-234.
63. Birbil SI. Stochastic global optimization techniques. PhD thesis, North Carolina State University, 2002.
64. De Smet G. ITC 2007-Examination Track: 1, 〈〉, 2007. http://www.cs.qub.ac.uk/itc2007.
65. Gogos C., Alefragis P., Housos E. An improved multi-staged algorithmic process for the solution of the examination timetabling problem. Annals of Operations Research 2010, 10.1007/s10479-010-0712-3.
66. Gogos C, Goulas G, Alefragis P, Housos E. Pursuit of better results for the examination timetabling problem using grid resources. In: Proceedings of the CI-Sched '09, IEEE symposium on computational intelligence in scheduling, 2009, p. 48-53.
67. Thompson J.M., Dowsland K.A. Variants of simulated annealing for the examination timetabling problem. Ann Oper Res 1996, 63(1):105-128.
68. Thompson J.M., Dowsland K.A. A robust simulated annealing based examination timetabling system. Comput Oper Res 1998, 25(7-8):637-648.
69. Sabar NR, Ayob M, Kendall G. Solving examination timetabling problems using honey-bee mating optimization (ETP-HBMO). In: Proceedings of the 4th Multidisciplinary International Scheduling Conference: Theory andApplications (MISTA 2009), 10-12 Aug 2009, Dublin, Ireland, pp. 399-408.