Skip to main content
SpringerLink
Log in
Book cover

International Conference on the Practice and Theory of Automated Timetabling

PATAT 1997: Practice and Theory of Automated Timetabling II pp 3–19Cite as

Recent developments in practical course timetabling

  • Conference paper
  • First Online:

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 1408))

Abstract

Course timetabling is a multi-dimensional NP-Complete problem that has generated hundreds of papers and thousands of students have attempted to solve it for their own school. In this paper, we describe the major components of the course timetabling problem. We discuss some of the primary types of algorithms that have been applied to these problems. We provide a series of tables listing papers in refereed journals that have either implemented a solution or tested their algorithm on real data. We made no attempt to provide a qualitative comparison. We restricted our presentation to a description of the types of technique used and the size of problem solved We have not included commercial software vendors

This is a preview of subscription content, log in via an institution.

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  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

Author information

Authors and Affiliations

  1. Department of Mechanical and Industrial Engineering, University of Toronto, 5 King’s College Road, M5S 3G8, Toronto, Ontario

    Michael W. Carter

  2. GERAD école des Hautes études Commerciales de Montréal, 3000 chemin de la CÔte-Sainte-Catherine, H3T 1V6, Montréal, Canada

    Gilbert Laporte

Authors
  1. Michael W. Carter
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Gilbert Laporte
    View author publications

    You can also search for this author in PubMed Google Scholar

Editor information

Edmund Burke Michael Carter

Rights and permissions

Reprints and permissions

Copyright information

© 1998 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Carter, M.W., Laporte, G. (1998). Recent developments in practical course timetabling. In: Burke, E., Carter, M. (eds) Practice and Theory of Automated Timetabling II. PATAT 1997. Lecture Notes in Computer Science, vol 1408. Springer, Berlin, Heidelberg. https://doi.org/10.1007/BFb0055878

Download citation

  • DOI: https://doi.org/10.1007/BFb0055878

  • Published:

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-64979-3

  • Online ISBN: 978-3-540-49803-2

  • eBook Packages: Springer Book Archive

Publish with us

Policies and ethics

Search

Navigation