An improved multi-staged algorithmic process for the solution of the examination timetabling problem

Annals of Operations Research

Volumn 194, Issue 1, 2012, Pages 203-221

  Gogos, Christos ^a,b   Alefragis, Panayiotis ^a,c   Housos, Efthymios ^a  

^a UNIVERSITY OF PATRAS   (Greece)

^b Epirus Institute of Technology Arta   (Greece)

^c TECHNOLOGICAL EDUCATIONAL INSTITUTE OF PATRAS   (Greece)

Author keywords

GRASP; Integer programming; Kempe chains; Metaheuristics; Simulated annealing

Indexed keywords

EID: 84857446757     PISSN: 02545330     EISSN: 15729338     Source Type: Journal    
DOI: 10.1007/s10479-010-0712-3     Document Type: Article

References (44)

1. Asmuni, H., Burke, E., Garibaldi, J., & McCollum, B. (2009). An investigation of fuzzy multiple heuristic orderings in the construction of university examination timetables. Computers and Operations Research, 36(4), 981-1001.
2. Balakrishnan, N., Lucena, A., & Wong, R. T. (1992). Scheduling examinations to reduce second order conflicts. Computers and Operations Research, 19, 353-361.
3. Brelaz, D. (1979). New methods to color the vertices of a graph. Communication of the ACM, 22(4), 251-256.
4. Broder, S. (1964). Final examination scheduling. Communications of the ACM, 7(8), 494-498.
5. Burke, E. K., & Newall, J. P. (2004). Solving examination timetabling problems through adaptation of heuristic orderings. Annals of Operations Research, 129, 107-134.
6. Burke, E. K., & Petrovic, S. (2002). Recent research directions in automated timetabling. European Journal of Operational Research, 140, 266-280.
7. Burke, E. K., Newall, J. P., & Weare, R. F. (1996). A memetic algorithm for university exam timetabling. In Lecture notes in computer science: Vol. 1153. Practice and theory of automated timetabling (pp. 241-250). Berlin: Springer. doi: 10. 1007/3-540-61794-9_63.
8. Burke, E. K., Kingston, J. H., & de Werra, D. (2004). Applications to timetabling. In J. Gross & J. Yellen (Eds.), The handbook of graph theory (pp. 445-474). London, Boca Raton: Chapman Hall/CRC Press.
9. Burke, E. K., Kendal, G., McCollum, B., & McMullan, P. (2007). Constructive versus improvement heuristics: an investigation of examination timetabling. In 3rd Multidisciplinary international scheduling conference: theory and applications, 28-31 August 2007, Paris.
10. Carter, M. W., Laporte, G., & Chinneck, J. W. (1994). A general examination scheduling system. Interfaces, 24, 109-120.
11. Carter, M. W., Laporte, G., & Lee, S. Y. (1996). Examination timetabling: algorithmic strategies and applications. Journal of Operational Research Society, 47, 373-383.
12. Casey, S., & Thompson, J. (2003). GRASPing the examination scheduling problem. In Lecture notes in computer science: Vol. 2740. Practice and theory of automated timetabling (pp. 232-244). Berlin, Heidelberg: Springer.
13. David, P. (1998). A constraint-based approach for examination timetabling using local repair techniques. In E. K. Burke & M. W. Carter (Eds.), Lecture notes in computer science: Vol. 1408. Practice and theory of automated timetabling: selected papers from the 2nd international conference (pp. 169-186). Berlin, Heidelberg: Springer.
14. Di Caspero, L. (2002). Recolour, Shake and Kick: a recipe for the examination timetabling problem. In E. K. Burke & P. De Causmaecker (Eds.), Proceedings of the 4th international conference on practice and theory of automated timetabling, KaHo St.-Lieven, Gent, Belgium (pp. 404-407). Berlin: Springer.
15. Dowsland, K. A. (1993). Simulated annealing. Modern heuristic techniques for combinatorial problems by C. Reeves. New York: Wiley. ISBN 0-470-22079-1.
16. Eley, M. (2006). Ant algorithms for the exam timetabling problem. In Practice and theory of automated timetabling (pp. 167-180). Berlin: Springer. ISBN 80-210-3726-1.
17. Ersoy, E., Ozcan, E., & Sima Uyar, A. (2007). Memetic algorithms and hyperhill-climbers. In Proceedings of the 3nd multidisciplinary international conference on scheduling: theory and applications, MISTA07 (pp. 159-166).
18. Feo, T. A., & Resende, M. G. C. (1995). Greedy randomized adaptive search procedures. Journal of Global Optimization, 6, 109-133.
19. Gamma, E., Helm, R., Johnson, R., & Vlissides, J. (1994). Design patterns: elements of reusable object-oriented software. Addison-Wesley Professional Computing Series. Reading: Addison-Wesley. ISBN-13: 978-0201633610.
20. Glover, F., & Laguna, M. (1997). Tabu search. Dordrecht: Kluwer Academic. ISBN 0-7923-9965-X.
21. Gogos, C., Alefragis, P., & Housos, E. (2008). A multi staged algorithmic process for the solution of the examination timetabling problem. In Proceedings of the 7th international conference on practice and theory of automated timetabling. University of Montreal, Canada.
22. Gogos, C., Goulas, G., Alefragis, P., & Housos, E. (2009). Pursuit of better results for the examination timetabling problem using grid resources. In Computational intelligence in scheduling, 2009, CI-Sched09 (pp. 48-53). doi: 10. 1109/SCIS. 2009. 4927014.
23. Henderson, D., Jacobson, S., & Johnson, A. (2003). The theory and practice of simulated annealing. In F. Glover & G. Kochenberger (Eds.), Handbook of metaheuristics, Chap. 10. Dordrecht: Kluwer Academic. ISBN 978-1-4020-7263-5.
24. Ibaraki, T. (2008). Problem solving by general purpose solvers. In The 7th international symposium on operations research and its applications (ISORA'08), Lijiang, China, ORSC & APORC (pp. 10-17).
25. Joslin, D., & Clements, D. (1999). Squeaky wheel optimization. Journal of Artificial Intelligence Research, 10, 353-373.
26. Kendall, G., & Hussin, N. M. (2005). An investigation of a tabu search based hyper-heuristic for examination timetabling. In G. Kendall, E. K. Burke, & S. Petrovic (Eds.), Selected papers from multidisciplinary scheduling: theory and applications (pp. 309-328).
27. Kingston, J., & Yin-Sun Lynn, B. (2001). A software architecture for timetable construction. In Lecture notes in computer science: Vol. 2079. PATAT 2000 (pp. 342-350). Berlin: Springer.
28. McCollum, B. (2007). A perspective on bridging the gap between theory and practice in university timetabling. In Lecture notes in computer science: Vol. 3867. PATAT 2006 (pp. 3-23). Berlin: Springer. ISBN 978-3-540-77344-3.
29. McCollum, B., & McMullan, M. (2007). The second international timetabling competition: examination timetabling track (Technical report: QUB/IEEE/Tech/ITC2007/Exam/v4. 0/17). School of Electronics, Electrical Engineering and Computer Science, Queen's University, Belfast, UK, August 2007.
30. McCollum, B., McMullan, P., Burke, E., Parkes, A., & Qu, R. (2009a). A new model for automated examination timetabling. Submitted to post PATAT Annals of OR.
31. McCollum, B., McMullan, P., Parkes, A., Burke, E., & Abdullah, S. (2009b). An extended great deluge approach to the examination timetabling problem. In Proceedings of MISTA09. The 4th multidisciplinary international conference on scheduling: theory and applications, Dublin, August 2009 (pp. 424-434).
32. McCollum, B., Schaerf, A., Paechter, B., McMullan, P., Lewis, R., Parkes, A., Di Gaspero, L., Qu, R., & Burke, E. (2009c). Setting the research agenda in automated timetabling: the second international timetabling competition. INFORMS Journal of Computing. doi: 10. 1287/ijoc. 1090. 0320.
33. McMullan, P. (2007). An extended implementation of the great deluge algorithm for course timetabling. In Lecture notes in computer science: Vol. 4487 (pp. 538-545). Berlin: Springer.
34. Merlot, L. T. G., Boland, N. Hughes B. D., & Stuckey, P. J. (2003). A hybrid algorithm for the examination timetabling problem. In E. K. Burke & P. De Causmaecker (Eds.), Lecture notes in computer science: Vol. 2740. Practice and theory of automated timetabling: selected papers from the 4th international conference (pp. 207-231). Berlin: Springer.
35. Muller, T. (2008). ITC 2007: Solver description. In Proceedings of the 7th international conference on practice and theory of automated timetabling. University of Montreal, Canada.
36. Petrovic, S., & Burke, E. K. (2004). Chap. 45. University timetabling. In J. Leung (Ed.), Handbook of scheduling: algorithms, models, and performance analysis. Boca Raton: CRC Press.
37. Pillay, N., & Banzhaf, W. (2008). A study of heuristic combinations for hyper-heuristic systems for the uncapacitated examination timetabling problem. European Journal of Operational Research. doi: 10. 1016/j. ejor. 2008. 07. 023.
38. Qu, R., & Burke, E. K. (2009). Hybridizations within a graph based hyper-heuristic framework for university timetabling problems. Journal of Operational Research Society. doi: 10. 1057/jors. 2008. 102.
39. Qu, R., Burke, E., McCollum, B., Merlot, L., & Lee, S. (2009). A survey of search methodologies and automated system development for examination timetabling. Journal of scheduling, 12(1), 55-89. doi: 10. 1007/s10951-008-0077-5.
40. Resende, M. G. C., & Ribeiro, C. C. (2003). Greedy randomized adaptive search procedures, Chap. 8. In F. Glover & G. Kochenberger (Eds.), Handbook of metaheuristics. Dordrecht: Kluwer. ISBN: 978-1-4020-7263-5.
41. Schaerf, A. (1999). A survey of automated timetabling. Artificial Intelligence Review, 13, 87-127.
42. Thompson, J. M., & Dowsland, K. A. (1996). Variants of simulated annealing for the examination timetabling problem. Annals of Operations Research, 63(1), 105-128.
43. Welsh, D. J. A., & Powell, M. B. (1967). An upper bound for the chromatic number of a graph and its application to timetabling problems. The Computer Journal, 10, 85-86.
44. White, G. M., & Chan, P. W. (1979). Towards the construction of optimal examination schedules. INFOR, 17, 219-229.