Multiple-retrieval case-based reasoning for course timetabling problems

Journal of the Operational Research Society

Volumn 57, Issue 2, 2006, Pages 148-162

  Burke, E K ^a   MacCarthy, B L ^b   Petrovic, S ^a   Qu, R ^a  

^a UNIVERSITY OF NOTTINGHAM   (United Kingdom)

^b NOTTINGHAM UNIVERSITY BUSINESS SCHOOL   (United Kingdom)

Author keywords

Attribute graph; Case based reasoning (CBR); Simulated annealing; Tabu search; Timetabling

Indexed keywords

DATA STRUCTURES; DECISION THEORY; INFORMATION ANALYSIS; PROBLEM SOLVING; SIMULATED ANNEALING; TREES (MATHEMATICS);

ATTRIBUTE GRAPH; CASE-BASED REASONING (CBR); TABU SEARCH; TIMETABLING;

INFORMATION RETRIEVAL;

EID: 31444449889     PISSN: 01605682     EISSN: 14769360     Source Type: Journal    
DOI: 10.1057/palgrave.jors.2601970     Document Type: Article

References (80)

1. Wren A and Rousseau J-M (1995). Bus driver scheduling - an overview. In: Daduna JR, Branco I and Paix'ao IMP (eds). Computer-Aided Transit Scheduling. Springer-Verlag, Berlin, pp 173-187.
2. Easton K, Nemhauser G and Trick M (2004). Sports scheduling. In: Leung J (ed). Handbook of Scheduling: Algorithms, Models, and Performance Analysis, Chapter 52. CRC Press, Boca Raton, FL.
3. Cheang B, Li H, Lim A and Rodrigues B (2003). Nurse rostering problems - a bibliographic survey. Eur J Opl Res 151; 447-460.
4. Burke E, De Causmaecker P, Vanden Berghe G and Van Landeghem H. (2004). The state of the art of nurse rostering. J Scheduling 7: 441-499.
5. Carter M and Laporte G (1995). Recent developments in practical examination timetabling. In: Burke E and Ross P (eds). The Practice and Theory of Automated Timetabling: Selected Papers from the Ist International Conference. Lecture Notes in Computer Science, Vol. 1153. Springer-Verlag, Berlin, pp 3-21.
6. Bardadym V (1995). Computer-aided school and university timetabling: the new wave. In: Burke E and Ross P (eds). The Practice and Theory of Automated Timetabling: Selected Papers from the 1st International Conference. Lecture Notes in Computer Science, Vol. 1153. Springer-Verlag, Berlin, pp 22-45.
7. Carter M and Laporte G (1997). Recent developments in practical course timetabling. In: Burke E and Carter M (eds). The Practice and Theory of Automated Timetabling: Selected Papers from the 2nd International Conference. Lecture Notes in Computer Science, Vol. 1408. Springer-Verlag, Berlin, pp 3-19.
8. Burke E and Ross P (1995). The Practice and Theory of Automated Timetabling: Selected Papers from the 1st International Conference. Lecture Notes in Computer Science, Vol. 1153. Springer-Verlag: Berlin.
9. Burke E and Carter MW (1997). The Practice and Theory of Automated Timetabling: Selected Papers from the 2nd International Conference. Lecture Notes in Computer Science, Vol. 1408. Springer-Verlag: Berlin.
10. Burke E and Erben W (eds) (2000). The Practice and Theory of Automated Timetabling: Selected Papers from the 3rd International Conference. Lecture Notes in Computer Science, Vol. 2079. Springer-Verlag: Berlin.
11. Burke E and de Causmaecker P (2002). The Practice and Theory of Automated Timetabling: Selected Papers from the 4th International Conference. Lecture Notes in Computer Science, Vol. 2740. Springer-Verlag: Berlin.
12. Burke E and Trick M (eds) (2004). The Proceedings of the 5th International Conference on the Practice and Theory of Automated Timetabling. Carnegie Mellon University: Pittsburgh, USA.
13. Wren A (1995). Scheduling, timetabling and rostering - a special relationship? In: Burke E and Ross P (eds). The Practice and Theory of Automated Timetabling: Selected papers from the 1st International Conference. Lecture Notes in Computer Science, Vol. 1153. Springer-Verlag, Berlin, pp 46-75.
14. Burke E and Petrovic S (2002). Recent research directions in automated timetabling. Eur J Opl Res 140: 266-280.
15. Petrovic S and Burke E (2004). University timetabling. In: Leung J (ed). Handbook of Scheduling: Algorithms, Models, and Performance Analysis, Chapter 45. CRC Press, Boca Raton, RL.
16. Schaerf A (1999). A survey of automated timetabling. Artif Intelli Rev 13: 87-127.
17. Carter M (1986). A lagrangian relaxation approach to the classroom assignment problem. INFOR 27: 230-246.
18. de Werra D (1985). Graphs, hypergraphs and timetabling. Methods Opns Res (Germany F.R.) 49: 201-213.
19. Burke E, Kingston J and de Werra D (2004). Applications to timetabling. In: Gross J and Yellen J (eds). Handbook of Graph Theory. Chapman & Hall/ CRC Press, London, Boca Raton, FL, pp 445-474.
20. Schaerf A (1996). Tabu search techniques for large high-school timetabling problems. In: Franz A and Kitano H (eds). Proceedings of the Thirteenth National Conference on Artificial Intelligence. AAAI Press: Menlo Park, CA, pp 363-368.
21. Costa D (1994). A tabu search algorithm for computing an operational timetable. Eur J Opl Res 76: 98-110.
22. Abramson D (1991). Constructing school timetables using simulated annealing; sequential and parallel algorithms. Mngt Sci 37: 98-113.
23. Elmohamed MAS, Coddington P and Fox G (1997). A comparison of annealing techniques for academic course scheduling. In: Burke E and Carter M (eds). The Practice and Theory of Automated Timetabling: Selected Papers from the 2nd International Conference. Lecture Notes in Computer Science, Vol. 1408. Springer-Verlag, Berlin, pp 92-112.
24. Burke E, Bykov Y, Newall J and Petrovic S (2003). A time-predefined approach to course timetabling. Yugoslav J Opns Res 13: 139-151.
25. Erben W and Keppler J (1995). A genetic algorithm solving a weekly course-timetabling problem. In: Burke E and Ross P (eds). The Practice and Theory of Automated Timetabling: Selected papers from the 1st International Conference. Lecture Notes in Computer Science, Vol. 1153. Springer-Verlag, Berlin, pp 198-211.
26. Paechter B, Cumming A and Luchian H (1995). The use of local search suggestions lists for improving the solutions of timetable problems with evolutionary algorithms. In: Fogarty T (ed). AISB Workshop on Evolutionary Computing. Lecture Notes in Computer Science, Vol. 993. Springer-Verlag, Berlin, pp 86-93.
27. Carrasco M and Pato M (2000). A multiobjective genetic algorithm for the class/teacher timetabling problem. In: Burke E and Erben W (eds). The Practice and Theory of Automated Timetabling: Selected papers from the 3rd International Conference. Lecture Notes in Computer Science, Vol. 2079. Springer-Verlag, Berlin, pp 3-17.
28. Burke E, Newall J and Weare R (1996). A memetic algorithm for university timetabling. In: Burke E and Ross P (eds). The Practice and Theory of Automated Timetabling: Selected Paper a from the 1st International Conference. Lecture Notes in Computer Science, Vol. 1153. Springer-Verlag, Berlin, pp 241-250.
29. Burke E, Newall J and Weare R (1998). Initialisation strategies and diversity in evolutionary timetabling. Evol Comput J (special issue on scheduling) 6: 81-103.
30. Lajos G (1996). Complete university modular timetabling using constraint logic programming. In: Burke E and Ross P (eds). The Practice and Theory of Automated Timetabling: Selected Papers from the 1st International Conference. Lecture Notes in Computer Science, Vol. 1153. Springer-Verlag, Berlin, pp 146-161.
31. Deris SB, Omatu S, Ohta H and Samat PABD (1997). University timetabling by constraint-based reasoning: A case study. J Opl Res Soc 48: 1178-1190.
32. Nonobe K and Ibaraki T (1998). A tabu search approach to the constraint satisfaction problem as a general problem solver. Eur J Opl Res 106: 599-623.
33. ten Eikelder HMM and Willemen RJ (2000). Some complexity aspects of secondary school timetabling problems. In: Burke E and Erben W (eds). The Practice and Theory of Automated Timetabling: Selected Papers from the 3rd International Conference. Lecture Notes in Computer Science, Vol. 2079. Springer-Verlag, Berlin, pp 18-27.
34. de Werra D, Asratian AS and Durand S (2002). Complexity of some special types of timetabling problems. J Scheduling 5: 171-184.
35. Burke E, MacCarthy B, Petrovic S and Qu R (2000). Structured cases in case-based reasoning - re-using and adapting cases for timetabling problems. Knowledge-based System 13: 159-165.
36. Burke E, MacCarthy B, Petrovic S and Qu R (2001). Case-based reasoning in course timetabling: an attribute graph approach. In: Aha DW and Watson I (eds). Case-Based Reasoning Research and Development. Proceedings of 4th International Conference on Case-Based Reasoning (ICCBR-2001). Lecture Notes in Artificial Intelligence, Vol. 2080. Springer-Verlag, Berlin, pp 90-104.
37. Kolodner J (1993). Case Based Reasoning. Morgan Kaufmann: Los Altos, CA.
38. Leake D (ed). (1996). Case-Based Reasoning: Experiences, Lessons, & Future Directions. The AAAI Press, MIT Press: Cambridge, MA, USA.
39. Aamodt A and Plaza E (1994). Case-based reasoning: foundational issues, methodological variations and system approaches. AI Commun 7: 39-59.
40. Mantaras RL and Plaza E (1997). Case-based reasoning: an overview. AI Commun 10: 21-29.
41. Burke E, Elliman D, Ford P and Weare R (1996). Examination timetabling in British universities - a survey. In: Burke E and Ross P (eds). The Practice and Theory of Automated Time-tabling: Selected Papers from the 1st International Conference. Lecture Notes in Computer Science, Vol. 1153. Springer-Verlag, Berlin, pp 76-92.
42. Burke E, De Causmaecker P and Vanden Berghe G. (1998). A hybrid tabu search algorithm for the nurse rostering problem. In: McKay B, Yao X, Newton CS, Kim JH and Furuhashi T (eds). Proceedings of the Second Asia-Pacific Conference on Simulated Evolution and Learning. Springer-Verlag, Berlin, pp 187-194.
43. Watson JP, Rana S, Whitley LD and Howe AE (1999). The impact of approximate evaluation on the performance of search algorithms for warehouse scheduling. J Scheduling 2: 79-98.
44. Aickelin U and Dowsland K (2000). Exploiting problem structure in a genetic algorithm approach to a nurse rostering problem. J Scheduling 3: 139-154.
45. Di Gaspero and Schaerf A (2000). Tabu search techniques for examination timetabling. In: Burke E and Erben W (eds). The Practice and Theory of Automated Timetabling: Selected Papers from the 3rd International Conference. Lecture Notes in Computer Science, Vol. 2079. Springer-Verlag, Berlin, pp 104-117.
46. Marir F and Watson I (1994). Case-based reasoning: a categorised bibliography. Knowledge Eng Rev 9: 355-381.
47. Burke E, Hart E, Kendall G, Newall J, Ross P and Schulenburg S (2003). Hyper-heuristics: an emerging direction in modern search technology. In: Glover F and Kochenberger G (eds). Handbook of Meta-Heuristics. Kluwer, Boston, pp 457-474.
48. Koton P (1989). SMARTplan: a case-based resource allocation and scheduling system. In: Hammond K (ed). Proceedings of the Workshop on Case-based Reasoning (DARPA). Morgan Kaufmann, San Francisco, CA, pp 285-289.
49. Hennessy D and Hinkle D (1992). Applying case-based reasoning to autoclave loading. IEEE Expert 7: 21-26.
50. Bezirgan A (1993). A case-based approach to scheduling constraints. In: Dorn J and Froeschl KA (eds). Scheduling of Production Processes. Ellis Horwood Limited, Chichester, UK, pp 48-60.
51. Miyashita K and Sycara K (1995). CABINS: a framework of knowledge acquisition and iterative revision for schedule improvement and reactive repair. Artif Intelli 76: 377-426.
52. Dorn J (1995). Case-based reactive scheduling. In: R Kerr, E Szelke (eds.) Artificial Intelligence in Reactive Scheduling. London, Chapman & Hall, pp 32-50.
53. Cunningham P and Smyth B (1997). Case-based reasoning in scheduling: reusing solution components. Int J Prod Res 35: 2947-2961.
54. Beddoe G and Petrovic S (2005). Determining feature weight using a genetic algorithm in a case-based reasoning approach to personnel rostering. Eur J Opl Res (forthcoming).
55. Scott S and Simpson R (1998). Case-bases incorporating scheduling constraint dimensions: experiences in nurse rostering. In: Smyth B and Cunningham P (eds). Advances in Case-Based Reasoning EWCBK98, Lecture Notes in Artificial Intelligence 1488. Springer-Verlag, Berlin, pp 392-401.
56. Szelke E and Markus G (1997). A learning reactive scheduler using CBR/L. Comput Ind 33: 31-46.
57. Schmidt G (1998). Case-based reasoning for production scheduling. Int J Prod Econom 56-57: 537-546.
58. MacCarthy B and Jou P (1995). A case-based expert system for scheduling problems with sequence dependent set up times. In: Adey RA and Rzevski G (eds). Applications of Artificial Intelligence. Engineering X. Computational Machines Publications, Southampton, pp 89-96.
59. MacCarthy B and Jou P (1996). Case-based reasoning in scheduling. In: Khan MK and Wright CS (eds), Proceedings of the Symposium on Advanced Manufacturing Processes, Systems and Techniques (AMPST96). MEP Publications Ltd, Bradford, UK, pp 211-218.
60. Carter M (1983). A decomposition algorithm for practical timetabling problems. Working paper 83-06, Industrial Engineering, University of Toronto.
61. Robert V and Hertz A (1995). How to decompose constrained course scheduling problems into easier assignment type subproblems. In: Burke E and Ross P (eds). The Practice and Theory of Automated Timetabling: Selected Papers from the 1st International Conference. Lecture Notes in Computer Science, Vol. 1153. Springer-Verlag, Berlin, pp 364-373.
62. Weare RF (1995). Automated examination timetabling. PhD dissertation, Department of Computer Science, University of Nottingham.
63. Burke E and Newall J (1999). A multistage evolutionary algorithm for the timetable problem. IEEE Trans Evol Comput 3: 63-74.
64. Marir F and Watson I (1995). Representation and indexing building refurbishment cases for multiple retrieval of adaptable pieces of cases. In: Veloso M and Aamodt A (eds). Case-Based Reasoning Research & Development: Proceedings of the 1st International Conference on Case-Based Reasoning (ICCBR-95). Springer-Verlag, Heidelberg, pp 55-66.
65. Smyth B, Keane M and Cunningham P (2001). Hierarchical case-based reasoning. IEEE Trans Knowledge Data Eng 13: 793-812.
66. Borner K, Coulon CH, Pippig E and Tammer EC (1996). Structural similarity and adaptation. In: Smith I and Faltings B (eds). Advances in Case-based Reasoning: Proceedings of the 4th European Workshop (EWCBR'98). Springer-Verlag, Heidelberg, pp 58-75.
67. Andersen WA, Evett MP, Kettler B and Hendler J (1994). Massively parallel support for case-based planning. IEEE Expert 7: 8-14.
68. Macedo L and Cardoso A (1998). Nested graph-structured representations for cases. In: Smyth B and Cunningham P (eds). Advances in Case-Based Reasoning: Proceedings of the 4th European Workshop on Case-Based Reasoning. Lecture Notes on Artificial Intelligence, Vol. 1488. Springer-Verlag, Heidelberg, pp 1-11.
69. Sanders KE, Kettler BP and Hendler JA (1997). The case for graph-structured representations. In: Leake D and Plaza E (eds). Case-Based Reasoning Research and Development: Proceedings of the 2nd International Conference on Case-Based Reasoning (ICCBR-97). Springer-Verlag, Berlin, pp 245-254.
70. Ricci F and Senter L (1998). Structured cases, trees and efficient retrieval. Advances in case-based reasoning. In: Smyth B and Cunningham P (eds). Proceedings of the 4th European Workshop on Case-Based Reasoning, Lecture Notes on Artificial Intelligence, Vol. 1488. Springer-Verlag, Heidelberg, pp 88-99.
71. Gebhardt F (1995). Methods and systems for case retrieval exploiting the case structure. FABEL-Report 39, GMD, Sankt Augustin.
72. Gebhardt F (1997). Survey on structure-based case retrieval. Knowledge Engi Rev 12: 41-58.
73. Burke E, Newall J and Weare R (1998). A simple heuristically guided search for the timetable problem. In: Alpaydin E (ed). Proceedings of the International ICSC Symposium on Engineering of Intelligent Systems. ICSC Academic Press, Canada, pp 574-579.
74. Corne DW and Ross PM (1996). Peckish initialisation strategies for evolutionary timetabling. In: Burke E and Ross P (eds). The Practice and Theory of Automated Timetabling: Selected Papers from the 1st International Conference. Lecture Notes in Computer Science, Vol. 1153. Springer-Verlag, Berlin, pp 227-240.
75. Rossi-Doria O, Blum C, Knowles J, Sampels M, Socha K and Paechter B (2002). A local search for the timetabling problem. In: Burke E and De Causmaecker P (eds). Proceedings of the 4th International Conference on the Practice and Theory of Automated Timetabling, PATAT 2002 Ka Ho St.-Lieven, Gent, Belgium, pp 124-127.
76. Socha K, Knowles J and Sampels M (2002). A max-min ant system for the university course timetabling problem. In: Proceedings of the 3rd International Workshop on Ant Algorithms, ANTS 2002. Lecture Notes in Computer Science, Vol. 2463. Springer, Berlin, pp 1-13.
77. Burke E, Kendall G and Soubeiga E (2003). A tabu search hyperheuristic for timetabling and rostering. J Heuristics 9: 451-470.
78. Kostuch P (2004). The university course timetabling problem with a 3-phase approach. In: Burke E and Trick M (eds). The Proceedings of the 5th International Conference on the Practice and Theory of Automated Timetabling. Carnegie Mellon University, Pittsburgh, USA, pp 251-266.
79. Williams ML, Wilson RC and Hancock ER (1999). Deterministic search for relational graph matching. Pattern Recognition 32: 1255-1271.
80. Cross ADJ, Myers R and Hancock ER (2000). Convergence of a hill-climbing genetic algorithm for graph matching. Pattern-Recognition 33: 1863-1880.