Abstract
This paper takes three important steps towards constraint-based school timetabling: (i) It proposes a constraint model that covers many important requirements of school timetables by means of global constraints. (ii) It proposes a corresponding problem solver that learns from its earlier faults and restarts to escape non-promising parts of the search space. (iii) By reporting a large-scale computational study, it delivers a proof of concept.
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References
Abdennadher, S., & Marte, M. (2000). University course timetabling using constraint handling rules. Journal of Applied Artificial Intelligence, 14(4), 311–326.
Aggoun, A., & Beldiceanu, N. (1993). Extending CHIP in order to solve complex scheduling and placement problems. Mathematical and Computer Modelling, 17(7), 57–73.
Apt, K. R. (2003). Principles of constraint programming. Cambridge: Cambridge University Press.
Beldiceanu, N. (2001). Pruning for the minimum constraint family and for the number of distinct values constraint family. In Walsh (2001), pp. 211–224.
Beldiceanu, N., & Carlsson, M. (2001). Sweep as a generic pruning technique applied to the non-overlapping rectangles constraint. In Walsh (2001), pp. 377–391.
Brucker, P., & Knust, S. (2001). Resource-constrained project scheduling and timetabling. In Burke and Erben (2001), pp. 277–293.
Burke, E. & Erben, W. (Eds.) (2001). LNCS : Vol. 2079. Practice and theory of automated timetabling III. Berlin: Springer.
Burke, E. & Ross, P. (Eds.) (1996). LNCS : Vol. 1153. Practice and theory of automated timetabling. Berlin: Springer.
Carlsson, M., Ottosson, G., & Carlson, B. (1997). An open-ended finite domain constraint solver. In LNCS : Vol. 1292. Ninth international symposium on programming languages, implementations, logics, and programs (pp. 191–206). Berlin: Springer.
Carrasco, M. P., & Pato, M. V. (2001). A multiobjective genetic algorithm for the class/teacher timetabling problem. In Burke and Erben (2001), pp. 3–17.
Clancey, W. J., & Weld, D. (Eds.) (1996). In Proceedings of the 13th national conference on artificial intelligence. AAAI Press.
Colorni, A., Dorigo, M., & Maniezzo, V. (1998). Metaheuristics for high-school timetabling. Computational Optimization and Applications, 9(3), 277–298.
Costa, D. (1994). A tabu search algorithm for computing an operational timetable. European Journal of Operational Research, 76(1), 98–110.
Dechter, R. (2003). Constraint processing. San Mateo: Morgan Kaufmann.
Drexl, A., & Salewski, F. (1997). Distribution requirements and compactness constraints in school timetabling. European Journal of Operational Research, 102(1), 193–214.
Even, S., Itai, A., & Shamir, A. (1976). On the complexity of timetable and multicommodity flow problems. SIAM Journal on Computing, 5(4), 691–703.
Fernandes, C., Caldeira, J. P., Melicio, F., & Rosa, A. (1999). High-school weekly timetabling by evolutionary algorithms. In ACM symposium on applied computing (pp. 344–350).
Frühwirth, T., & Abdennadher, S. (2003). Essentials of constraint programming. Berlin: Springer.
Goltz, H. -J., & Matzke, D. (1999). University timetabling using constraint logic programming. In LNCS : Vol. 1551. Practical aspects of declarative languages (pp. 320–334). Berlin: Springer.
Gueret, C., Jussien, N., Boizumault, P., & Prins, C. (1996). Building university timetables using constraint logic programming. In Burke and Ross (1996), pp. 130–145.
Henz, M., & Würtz, J. (1996). Using Oz for college timetabling. In Burke and Ross (1996), pp. 283–296.
Intelligent Systems Laboratory, Swedish Institute of Computer Science (2003). SICStus prolog user’s manual, release 3.10.1.
Jaffar, J. (Ed.) (1999). LNCS : Vol. 1713. Fifth international conference on principles and practice of constraint programming. Berlin: Springer.
Junginger, W. (1986). Timetabling in Germany—a survey. Interfaces, 16(4), 66–74.
Kaneko, K., Yoshikawa, M., & Nakakuki, Y. (1999). Improving a heuristic repair method for large-scale school timetabling problems. In Jaffar (1999), pp. 275–288.
Marriott, K., & Stuckey, P. (1998). Programming with constraints: an introduction. Cambridge: MIT Press.
Marte, M. (2002). Models and algorithms for school timetabling—a constraint-programming approach. PhD thesis, Fakultät für Mathematik, Informatik und Statistik der Ludwig-Maximilians-Universität München.
Régin, J.-C. (1994). A filtering algorithm for constraints of difference in CSPs. In B. Hayes-Roth & R. E. Korf (Eds.), Proceedings of the 12th national conference on artificial intelligence (pp. 362–367). AAAI Press.
Régin, J.-C. (1996). Generalized arc consistency for global cardinality constraint. In Clancey and Weld (1996), pp. 209–215.
Régin, J.-C. (1999). Arc consistency for global cardinality constraint with costs. In Jaffar (1999), pp. 390–404
Schaerf, A. (1996). Tabu search techniques for large high-school timetabling problems. In Clancey and Weld (1996), pp. 363–368.
Schaerf, A. (1999). A survey of automated timetabling. Artificial Intelligence Review, 13(2), 87–127.
van Hoeve, W. J. (2001). The alldifferent constraint: a survey. In 6th annual workshop of the ERCIM working group on constraints.
Walsh, T. (Ed.) (2001). LNCS : Vol. 2239. Seventh international conference on principles and practice of constraint programming. Berlin: Springer.
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Marte, M. Towards constraint-based school timetabling. Ann Oper Res 155, 207–225 (2007). https://doi.org/10.1007/s10479-007-0218-9
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DOI: https://doi.org/10.1007/s10479-007-0218-9