Recent developments in practical course timetabling

1. Abramson, D., “Constructing School Timetables Using Simulated Annealing: Sequential and Parallel Algorithms”, Man. Sci. 37, No. 1, pp. 98–113., 1991.

   MathSciNet  Google Scholar 

2. Adamidis, P. and Arapakis, P., “Weekly Lecture Timetabling with Genetic Algorithms”, PATAT ’91.

   Google Scholar 

3. Aarts, E. and Lenstra, J.K., Local Search in Combinatorial Optimization, Wiley, Chichester, 1997.

   MATH  Google Scholar 

4. Aubin, J. and Ferland, J.A., “A Large Scale Timetabling Problem”, Computers & Operations Research 16, No. 1, pp. 67–77, 1989.

   Article  MATH  MathSciNet  Google Scholar 

5. Azevedo, F. and Barahona, P., “Timetabling in Constraint Logic Programming”, Proceedings of World Congress on Expert Systems’94.

   Google Scholar 

6. Bloomfield, S.D. and McSharry, M.M., “Preferential Course Scheduling”, Interfaces 9, No. 4, pp. 24–31, August 1979.

   Article  Google Scholar 

7. Carter, M.W., “A Lagrangian Relaxation Approach to the Classroom Assignment Problem”, INFOR 27, No. 2, pp. 230–246, 1989.

   MATH  Google Scholar 

8. Carter, M.W. and Tovey, C.A., “When Is the Classroom Assignment Problem Hard?”, Oper. Res. 40, Supp. No. 1, pp. S28–S39, 1992.

   MATH  Google Scholar 

9. Carter, M.W., Laporte, G. and Lee, S.Y., “Examination Timetabling: Algorithmic Strategies and Applications”, J. of Operational Research Society 47, No. 3, 373–383, March 1996.

   Article  Google Scholar 

10. Carter, M.W. and Laporte, G., “Recent Developments in Practical Examination Timetabling”, in Practice and Theory of Automated Timetabling, Springer-Verlag Lecture Notes in Computer Science 1153, Burke & Ross, eds., 1996.

    Google Scholar 

11. Chahal, N. and de Werra, D., “An Interactive System for Constructing Timetables on a PC”, EJOR 40, pp. 32–37, 1989.

    Article  MATH  Google Scholar 

12. Chan, H.W., Lau, C.K., and Sheung, J., “Practical School Timetabling: A Hybrid Approach Using Solution Synthesis and Iterative Repair”, in Practice and Theory of Automated Timetabling, Springer-Verlag Lecture Notes in Computer Science, Burke & Carter, eds., 1998.

    Google Scholar 

13. Cheng,C, Kang,L., Leung,N. and White, G.M., “Investigations of a Constraint Logic Programming Approach to University Timetabling”, in Practice and Theory of Automated Timetabling, Springer-Verlag Lecture Notes in Computer Science 1153, Burke & Ross, eds., 1996.

    Google Scholar 

14. Colorni A., Dorigo M. and Maniezzo V., “Genetic Algorithms — A New Approach to the Timetable Problem”, Lecture Notes in Computer Science — NATO ASI Series, Vol. F 82, Combinatorial Optimization, (Akgul et al eds), Springer-Verlag, pp 235–239. 1990. (1992?)

    Google Scholar 

15. Cooper, T.B. and Kingston, J.H., “The Solution of Real Instances of the Timetabling Problem”, The Computer Journal, vol 36, no 7, pp 645–653, 1993.

    Article  Google Scholar 

16. Corne, D., and Ross, P., “Peckish Initialization Strategies for Evolutionary Timetabling”, in Practice and Theory of Automated Timetabling, Springer-Verlag Lecture Notes in Computer Science 1153, Burke & Ross, eds., 1996.

    Google Scholar 

17. Costa, D., “A Tabu Search Algorithm for Computing an Operational Timetable”, European J. of Operational Res. 76, pp. 98–110, 1994.

    Article  MATH  Google Scholar 

18. Davis, L. and Ritter, L., “Schedule Optimization with Probabilistic Search”, Proceedings of the 3rd IEEE Conference on Artificial Intelligence Applications, Orlando, Florida, USA, pp. 231–236, IEEE, 1987.

    Google Scholar 

19. de Gans, O.B., “A Computer Timetabling System for Secondary Schools in The Netherlands”, EJOR 7, 175–182, 1981.

    Article  Google Scholar 

20. de Werra, D., “Construction of School Timetables by Flow Methods”, INFOR 9, No.1, 1971, 12–22.

    MATH  Google Scholar 

21. Dinkel, J.J., Mote, J. and Venkataramanan, M.A., “An Efficient Decision Support System for Academic Course Scheduling”, Operations Research 37, No. 6, pp. 853–864, 1989.

    Google Scholar 

22. Dyer, J.S. and Mulvey, J.M., “Computerized Scheduling and Planning”, New Directions for Institutional Research 13, pp. 67–86, 1977.

    Google Scholar 

23. Elmohamed, S., Coddington, P., and Fox, G., “A Comparison of Annealing Techniques for Academic Course Scheduling”, in Practice and Theory of Automated Timetabling, Springer-Verlag Lecture Notes in Computer Science, Burke & Carter, eds., 1998.

    Google Scholar 

24. Erben,W. and Keppler, J., “A Genetic Algorithm Solving a Weekly Course Timetabling Problem”, in Practice and Theory of Automated Timetabling, Springer-Verlag Lecture Notes in Computer Science 1153, Burke & Ross, eds., 1996.

    Google Scholar 

25. Fahrion, R. and Dollansky, G., “Construction of University Faculty Timetables Using Logic Programming”, Discrete Applied Mathematics 35, No. 3, pp. 221–236, 1992.

    Article  MATH  Google Scholar 

26. Glassey, C.R. and Mizrach, M., “A Decision Support System for Assigning Classes to Rooms”, Interfaces 16, No. 5, pp. 92–100, 1986.

    Google Scholar 

27. Gosselin, K. and Truchon, M., “Allocation of Classrooms by Linear Programming”, J. Operational Research Soc. 37, No. 6, 561–569, 1986.

    Article  Google Scholar 

28. Graves, R.L., Schrage, L. and Sankaran, J., “An Auction Method for Course Registration”, Interfaces 23, No. 5, pp 81–92, September–October 1993.

    Google Scholar 

29. Gueret,G., Jussien,N., Boizumault,P. and Prins, C., “Building University Timetables Using Constraint Logic Programming”, in Practice and Theory of Automated Timetabling, Springer-Verlag Lecture Notes in Computer Science 1153, Burke & Ross, eds., 1996.

    Google Scholar 

30. Henz,M. and Wurtz,J., “Using Oz for College Timetabling”, in Practice and Theory of Automated Timetabling, Springer-Verlag Lecture Notes in Computer Science 1153, Burke & Ross, eds., 1996.

    Google Scholar 

31. Hertz, A., “Tabu Search for Large Scale Timetabling Problems”, EJOR 54, pp. 39–47, 1991.

    Article  MATH  Google Scholar 

32. Jaffar, J. and Maher, M.J., “Constraint Logic Programming: A Survey”, Journal of Logic Programming 19/20, pp. 503–581, 1994.

    Article  MathSciNet  Google Scholar 

33. Kang, L. and White, G.M., “A Logic Approach to the Resolution of Constraints in Timetabling”, European Journal of Operational Research 61, pp. 306–317, 1992.

    Article  MATH  Google Scholar 

34. Kang, L., Von Schoenberg, G.H. and White, G.M., 1Complete University Timetabling Using Logicl, Computers and Education, 17 No. 2, pp. 145–153, 1991.

    Article  Google Scholar 

35. Lajos, G., “Complete University Modular Timetabling Using Constraint Logic Programming”, in Practice and Theory of Automated Timetabling, Springer-Verlag Lecture Notes in Computer Science 1153, Burke & Ross, eds., 1996.

    Google Scholar 

36. Laporte, G. and Desroches, S., “The Problem of Assigning Students to Course Sections in a Large Engineering School”, Comp. & Ops. Res. 13, No. 4, pp. 387–394, 1986.

    Article  Google Scholar 

37. McClure, R.H. and Wells, C.E., “A Mathematical Programming Model for Faculty Course Assignments”, Decision Sciences 15, No. 3, pp. 409–420, 1984.

    Google Scholar 

38. Miyaji, I., Ohno, K. and Mine, H., Solution Method for Partitioning Students into Groupsl, European Journal of Operational Research, 33, No. 1, pp. 82–90. 616, 1981.

    Google Scholar 

39. Nepal, T., Melville, S.W., and Ally, M.I., “A Brute Force and Heuristics Approach to Tertiary Timetabling”, in Practice and Theory of Automated Timetabling, Springer-Verlag Lecture Notes in Computer Science, Burke & Carter, eds., 1998.

    Google Scholar 

40. Ng, W.-Y., “TESS: An Interactive Support System for School Timetabling”, Information Technology in Educational Management for the Schools of the Future, Fung et al (ed.), Chapman and Hall, pp. 131–137, 1997.

    Google Scholar 

41. Osman, I.H. and Laporte, G., “Metaheuristics: A Bibliography. G. Laporte and I.H. Osman (eds), Metaheuristics in Combinatorial Optimization”, Annals of Operations Research 63, pp. 513–623, Baltzer, Amsterdam, 1996.

    Google Scholar 

42. Ostermann, R. and de Werra, D., “Some Experiments with a Timetabling System”, OR Spektrum 3, pp. 199–204, 1982.

    Article  Google Scholar 

43. Paechter, B., Cumming, A. and Luchian, H., “The Use of Local Search Suggestion Lists for Improving the Solution of Timetable Problems with Evolutionary Algorithms”, In Proceedings of the AISB Workshop on Evolutionary Computing, Sheffield, England, April 3–7, 1995.

    Google Scholar 

44. Papoulias, D.B., “The Assignment-to-days problem in a School Time-table, a Heuristic Approach”, EJOR 4, pp. 31–41, 1980.

    Article  Google Scholar 

45. Poutain, D., “Constraint Logic Programming”, Byte 20, pp. 159–160, 1995.

    Google Scholar 

46. Ram,V. and Scogings, C., “Automated Time Table Generation Using Multiple Context Reasoning with Truth Maintenance”, in Practice and Theory of Automated Timetabling, Springer-Verlag Lecture Notes in Computer Science 1153, Burke & Ross, eds., 1996.

    Google Scholar 

47. Rankin, R.C., “Automatic Timetabling in Practice”, in Practice and Theory of Automated Timetabling, Springer-Verlag Lecture Notes in Computer Science 1153, Burke & Ross, eds., 1996.

    Google Scholar 

48. Reeves, C.R., 1Modern Heuristic Techniques for Combinatorial Problems 1, Blackwell, Oxford, 1993.

    Google Scholar 

49. Rich, D.C., “A Smart Genetic Algorithm for University Timetabling”, in Practice and Theory of Automated Timetabling, Springer-Verlag Lecture Notes in Computer Science 1153, Burke & Ross, eds., 1996.

    Google Scholar 

50. Ross, P., Corne, D. and Fang, H.-L., “Successful Lecture Timetabling with Evolutionary Algorithms”, Dept of A.I. Working Paper, University of Edinburg, 1994.

    Google Scholar 

51. Sabin, G.C.W. and Winter, G.K., “The Impact of Automated Timetabling on Universities — A Case Study”, J. Operational Research Soc. 37, No.7, pp. 689–693, 1986.

    Article  Google Scholar 

52. Sampson, S.E., Freeland, J.R. and Weiss, E.N., “Class Scheduling to Maximize Participant Satisfaction”, Interfaces 25, No. 3, pp. 30–41, May–June 1995.

    Google Scholar 

53. Schaerf, A., “Tabu Search Techniques for Large High-School Timetabling Problems”, Comp. Science/Dept. of Interactive Systems, CS-R9611, Centrum voor Wiskunde en Informatica, SMC, Netherlands Organization for Scientific Researchm 1996.

    Google Scholar 

54. Schniederjans, M.J. and Kim, G.C., “A Goal Programming Model to Optimize Departmental Preference in Course Assignments”, Comput. Opns. Res. 14, No. 2, pp. 87–96, 1987.

    Article  Google Scholar 

55. Selim, S.M., “An Algorithm for Constructing a Unversity Faculty Timetable”, Comput. Educ. 6, No. 4, pp. 323–334., 1982.

    Article  Google Scholar 

56. White, G.M., and Zhang, J., “Generating Complete University Timetables by Combining Tabu Search with Constraint Logic”, in Practice and Theory of Automated Timetabling, Springer-Verlag Lecture Notes in Computer Science, Burke & Carter, eds., 1998.

    Google Scholar 

57. Wright, M., “School Timetabling using Heuristic Search”, Journal of the Operational Research Society, Vol. 47, pp. 347–357, 1996.

    Article  Google Scholar 

58. Yoshikawa, M., Kaneko, K., Yamanouchi, T. and Watanabe, N., “A Constraint-Based High School Scheduling System”, IEEE Expert, Vol. 11, No. 1, IEEE Coputer Society, Los Alamitos, CA., pp. 63–72, February 1996.

    Google Scholar 

Download references