Design, engineering, and experimental analysis of a simulated annealing approach to the post-enrolment course timetabling problem

Computers and Operations Research

Volumn 39, Issue 7, 2012, Pages 1615-1624

  Ceschia, Sara ^a   Di Gaspero, Luca ^a   Schaerf, Andrea ^a  

^a UNIVERSITY OF UDINE   (Italy)

Author keywords

Course timetabling; Metaheuristics; Simulated annealing

Indexed keywords

EXPERIMENTAL ANALYSIS; META HEURISTICS; META-HEURISTIC APPROACH; TIMETABLING; TIMETABLING PROBLEM;

CURRICULA; SCHEDULING;

SIMULATED ANNEALING;

EID: 81555204345     PISSN: 03050548     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.cor.2011.09.014     Document Type: Article

References (48)

1. B. McCollum, A. Schaerf, B. Paechter, P. McMullan, R. Lewis, and A.J. Parkes Setting the research agenda in automated timetabling: the second international timetabling competition INFORMS Journal on Computing 22 1 2010 120 130
2. Lewis R, Paechter B, McCollum B. Post enrolment based course timetabling: a description of the problem model used for track two of the second international timetabling competition. Technical Report, Cardiff University, Wales, UK; 2007.
3. O. Rossi-Doria, M. Sampels, M. Birattari, M. Chiarandini, M. Dorigo, and L.M. Gambardella A comparison of the performance of different metaheuristic on the timetabling problem E. Burke, P. De Causmaecker, Proceedings of the 4th international conference on the practice and theory of automated timetabling (PATAT-2002), selected papers. Lecture notes in computer science vol. 2740 2003 Springer-Verlag Berlin, Heidelberg 329 351 (Pubitemid 137632826)
4. R. Lewis, and B. Paechter Application of the grouping genetic algorithm to university course timetabling G. Raidl, J. Gottlieb, Fifth international conference on evolutionary computation in combinatorial optimisation (EvoCop 2005). Lecture notes in computer science vol. 3448 2005 Springer 144 153 (Pubitemid 41273996)
5. Gotlieb CC. The construction of class-teacher timetables. In: Popplewell CM, editor. IFIP congress 62. North-Holland; 1963. p. 737.
6. D. de Werra An introduction to timetabling European Journal of Operational Research 19 1985 151 162
7. A. Schaerf A survey of automated timetabling Artificial Intelligence Review 13 2 1999 87 127
8. E.K. Burke, and S. Petrovic Recent research directions in automated timetabling European Journal of Operational Research 140 2 2002 266 280 (Pubitemid 34435033)
9. R. Lewis A survey of metaheuristic-based techniques for university timetabling problems OR Spectrum 30 1 2008 167 190
10. A. Hertz Tabu search for large scale timetabling problems European Journal of Operational Research 54 1991 39 47 (Pubitemid 21712572)
11. A. Hertz Finding a feasible course schedule using tabu search Discrete Applied Mathematics 35 3 1992 255 270
12. Murray KS, Müller T, Rudová H. Modeling and solution of a complex university course timetabling problem. In: Proceedings of the 6th international conference on the practice and theory of automated timetabling (PATAT-2006), selected papers, 2007. p. 189209.
13. Z. Lü, and J.-K. Hao Adaptive tabu search for course timetabling European Journal of Operational Research 200 1 2009 235 244
14. Lach G, Lübbecke M. Curriculum based course timetabling: optimal solutions to the Udine benchmark instances. Annals of Operations Research, 2011:118. URL 〈 http://dx.doi.org/10.1007/s10479-010-0700-7 〉.
15. E. Burke, J. Mareček, A. Parkes, and H. Rudová A supernodal formulation of vertex colouring with applications in course timetabling Annals of Operations Research 179 1 2010 105 130
16. E.K. Burke, J. Mareček, A.J. Parkes, and H. Rudová Decomposition, reformulation, and diving in university course timetabling Computers and Operations Research 37 3 2010 582 597
17. Hao J-K, Benlic U. Lower bounds for the ITC-2007 curriculum-based course timetabling problem. European Journal of Operational Research 2011:212(3), 464472. URL 〈 http://dx.doi.org/10.1016/j.ejor.2011.02.019 〉.
18. T. Müller ITC2007 solver description: a hybrid approach Annals of Operations Research 172 1 2009 429 446
19. Bellio R, Di Gaspero L, Schaerf A. Design and statistical analysis of a hybrid local search algorithm for course timetabling. Journal of Scheduling 2011:113. URL 〈 http://dx.doi.org/10.1007/s10951-011-0224-2 〉.
20. M. Chiarandini, M. Birattari, K. Socha, and O. Rossi-Doria An effective hybrid approach for the university course timetabling problem Journal of Scheduling 9 5 2006 403 432
21. P. Kostuch The university course timetabling problem with a three-phase approach E. Burke, M. Trick, Proceedings of the 5th international conference on the practice and theory of automated timetabling (PATAT-2004), selected papers. Lecture notes in computer science vol. 3616 2005 Springer-Verlag Berlin, Heidelberg 109 125
22. E. Burke, Y. Bykov, J. Newall, and S. Petrović A time-predefined approach to course timetabling Yugoslav Journal of Operations Research 13 2 2003 139 151 (Pubitemid 41289525)
23. L. Di Gaspero, and A. Schaerf Neighborhood portfolio approach for local search applied to timetabling problems Journal of Mathematical Modeling and Algorithms 5 1 2006 65 89 (Pubitemid 43473950)
24. Chiarandini M, Fawcett C, Hoos H. A modular multiphase heuristic solver for post enrolment course timetabling. In: Burke E, Gendreau M, editors. Proceedings of the 7th international conference on the practice and theory of automated timetabling (PATAT-2008), 2008. p. 16.
25. F. Hutter, H. Hoos, K. Leyton-Brown, and T. Stützle ParamILS: an automatic algorithm configuration framework Journal of Artificial Intelligence Research 36 2009 267 306
26. Broek van den JJJ, Hurkens CAJ. An IP-based heuristic for the post enrolment course timetabling problem of the ITC2007. Annals of Operations Research 2010:116. URL 〈 http://dx.doi.org/10.1007/s10479-010-0708-z 〉.
27. Lewis R, A time-dependent metaheuristic algorithm for post enrolment-based course timetabling. Annals of Operations Research 2010:117. URL 〈 http://dx.doi.org/10.1007/s10479-010-0696-z 〉.
28. Cambazard H, Hebrard E, OSullivan B, Papadopoulos A. Local search and constraint programming for the post enrolment-based course timetabling problem. Annals of Operations Research 2010:125. URL 〈 http://dx.doi.org/10.1007/ s10479-010-0737-7 〉.
29. R. Lewis, and B. Paechter Finding feasible timetables using group-based operators IEEE Transactions on Evolutionary Computation 11 3 2007 397 413 (Pubitemid 46895415)
30. Tuga M, Berretta R, Mendes A. A hybrid simulated annealing with Kempe chain neighborhood for the university timetabling problem. In: 6th IEEE/ACIS international conference on computer and information science (ICIS 2007), 2007. p. 4005.
31. Y. Liu, D. Zhang, and F. Chin A clique-based algorithm for constructing feasible timetables Optimization Methods and Software 26 2 2011 281 294
32. S. Kirkpatrick, C.D. Gelatt Jr, and M.P. Vecchi Optimization by simulated annealing Science 220 1983 671 680
33. R.W. Eglese Simulated annealing: a tool for operational research European Journal of Operational Research 46 1990 271 281 (Pubitemid 20720808)
34. E. Aarts, and J.K. Lenstra Local search in combinatorial optimization 1997 John Wiley & Sons Chichester
35. H.H. Hoos, and T. Stützle Stochastic local search - foundations and applications 2005 Morgan Kaufmann Publishers San Francisco, CA, USA
36. Johnson DS. A theoreticians guide to the experimental analysis of algorithms. In: Goldwasser MH, Johnson DS, McGeoch CC, editors. Data structures, near neighbor searches, and methodology: fifth and sixth DIMACS implementation challenges. American Mathematical Society; 2002. p. 21550. URL 〈 http://www.research.att.com/∼dsj/papers.html 〉.
37. L. Di Gaspero, and A. Schaerf EasyLocal: an object-oriented framework for flexible design of local search algorithms Software - Practice and Experience 33 8 2003 733 765
38. T.M. Cioppa, and T.W. Lucas Efficient nearly orthogonal and space-filling latin hypercubes Technometrics 49 1 2007 45 55 (Pubitemid 46373233)
39. Sanchez SM. NOLH designs spreadsheet. 〈 http://diana.cs.nps.navy. mil/SeedLab/ 〉, visited on May 13, 2011. Last updated on April 7, 2006. URL 〈 http://diana.cs.nps.navy.mil/SeedLab/ 〉; 2005.
40. Birattari M, The RACE package. April 2005. URL 〈 http://cran.r-project.org/web/packages/race/ 〉.
41. Mayer A, Nothegger C, Chwatal A, Raidl G. Solving the post enrolment course timetabling problem by ant colony optimization. In: Burke E, Gendreau M, editors. Proceedings of the 7th international conference on the practice and theory of automated timetabling (PATAT-2008), 2008. p. 113.
42. K. Socha, J. Knowles, and M. Sampels A MAX-MIN ant system for the university timetabling problem Proceedings of the 3rd international workshop on ant algorithms (ANTS 2002). Lecture notes in computer science vol. 2463 2002 Springer-Verlag Berlin, Germany 1 13
43. S. Abdullah, E.K. Burke, and B. McCollum A hybrid evolutionary approach to the university course timetabling problem E. Burke, M.E Trick, IEEE congress on evolutionary computation vol. 3616 2007 Springer-Verlag 1764 1768
44. McMullan P. An extended implementation of the great deluge algorithm for course timetabling. In: Computational scienceICCS 2007, 2007. p. 53845.
45. Landa-Silva D, Obit JH. Great deluge with non-linear decay rate for solving course timetabling problems. In: 2008 4th international IEEE conference intelligent systems, September 2008. p. 818.
46. Turabieh H, Abdullah S, McCollum B. Electromagnetism-like mechanism with force decay rate great deluge for the course timetabling problem. Lecture notes in artificial intelligence, vol. 5589, 2009. p. 497.
47. P. Kostuch, and K. Socha Hardness prediction for the university course timetabling problem J. Gottlieb, G.R. Raidl, Evolutionary computation in combinatorial optimization. Lecture notes in computer science vol. 3004 2004 Springer Berlin, Heidelberg 135 144
48. Smith-Miles KA, Lopes L. Generalising algorithm performance in instance space: a timetabling case study. In: Proceedings of learning and intelligent optimization (LION 2011), 2011. p. 115.