Annals of Operations Research

, Volume 239, Issue 1, pp 77–97 | Cite as

GOAL solver: a hybrid local search based solver for high school timetabling

  • George Henrique Godim da Fonseca
  • Haroldo Gambini Santos
  • Túlio Ângelo Machado Toffolo
  • Samuel Souza Brito
  • Marcone Jamilson Freitas Souza
Article

Abstract

This work presents a local search approach to the High School Timetabling Problem. The addressed timetabling model is the one stated in the Third International Timetabling Competition (ITC 2011), which considered many instances from educational institutions around the world and attracted seventeen competitors. Our team, named GOAL (Group of Optimization and Algorithms), developed a solver built upon the Kingston High School Timetabling Engine. Several neighborhood structures were developed and used in a hybrid metaheuristic based on Simulated Annealing and Iterated Local Search. The developed algorithm was the winner of the competition and produced the best known solutions for almost all instances.

Keywords

Third International Timetabling Competition High School Timetabling Problem Simulated Annealing Iterated Local Search Metaheuristics 

References

  1. de Haan, P., Landman, R., Post, G., & Ruizenaar, H. (2007). A case study for timetabling in a dutch secondary school. In: Lecture notes in computer science: VI practice and theory of automated timetabling (Vol. 3867, pp. 267–279). Berlin: Springer.Google Scholar
  2. Even, S., Itai, A., & Shamir, A. (1976). On the complexity of timetable and multicommodity flow problems. SIAM Jounal of Computing, 5(4), 691–703.CrossRefGoogle Scholar
  3. Gendreau, M., & Potvin, J. (Eds.). (2010). Handbook of metaheuristics, international series in operations research and management science, (2nd ed., Vol. 146). Berlin: Springer.Google Scholar
  4. Johnson, D.S., Aragon, C.R., McGeoch, L., & Schevon, C. (1991). Optimization by simulated annealing: An experimental evaluation Part II, graph coloring and number partitioning. Operations Research, 39(3):378–406, doi:10.1287/opre.39.3.378, http://pubsonline.informs.org/doi/abs/10.1287/opre.39.3.378
  5. Kingston, J. (2013). Educational timetabling. In A. S. Uyar, E. Ozcan, & N. Urquhart (Eds.), Automated scheduling and planning, studies in computational intelligence (Vol. 505, pp. 91–108). Berlin: Springer. doi:10.1007/978-3-642-39304-4_4.
  6. Kingston, J.H. (2005). A tiling algorithm for high school timetabling. In: Lecture notes in computer science: V Practice and theory of automated timetabling (Vol. 3616, pp. 208–225). Berlin: Springer.Google Scholar
  7. Kingston, J. H. (2006). Hierarchical timetable construction. In Problems, proceedings of the first international conference on the practice and theory of automated timetabling.Google Scholar
  8. Kingston, J. H. (2012). A software library for school timetabling. http://sydney.edu.au/engineering/it/~jeff/khe/, Retrieved April 2012.
  9. Kirkpatrick, S., Gellat, D. C., & Vecchi, M. P. (1983). Otimization by simulated annealing. Science, 202, 671–680.CrossRefGoogle Scholar
  10. Kristiansen, S., & Stidsen, T. R. (2013). A comprehensive study of educational timetabling, a survey. Report 8.2013, DTU Management Engineering.Google Scholar
  11. Lourenco, H. R., Martin, O. C., & Stutzle, T. (2003). Iterated local search. In F. Glover & G. Kochenberger (Eds.), Handbook of metaheuristics, chap 11. Boston: Kluwer Academic Publishers.Google Scholar
  12. Lú, Z., & Hao, J. K. (2010). Adaptive Tabu Search for course timetabling. European Journal of Operational Research, 200(1), 235–244.CrossRefGoogle Scholar
  13. Muller, T. (2009). ITC2007 solver description: A hybrid approach. Annals of Operations Research, 172(1), 429–446.Google Scholar
  14. Nurmi, K., & Kyngas, J. (2007). A framework for school timetabling problem. In Proceedings of the 3rd multidisciplinary international scheduling conference: theory and applications, Paris (pp. 386–393).Google Scholar
  15. Pillay, N. (2013). A survey of school timetabling research. Annals of Operations Research. doi:10.1007/s10479-013-1321-8.
  16. Post, G., Ahmadi, S., Daskalaki, S., Kingston, J. H., Kyngas, J., Nurmi, C., et al. (2010). An XML format for benchmarks in High School Timetabling. Annals of Operations Research, 3867, 267–279.Google Scholar
  17. Post, G., Kingston, J. H., Ahmadi, S., Daskalaki, S., Gogos, C., Kyngas, J., Nurmi, C., Musliu, N., Pillay, N., Santos, H., & Schaerf, A. (2014). XHSTT: An XML archive for high school timetabling problems in different countries. Annals of Operations Research, 218(1), 295–301. doi:10.1007/s10479-011-1012-2.
  18. Post, G., Gaspero, L., Kingston, J., McCollum, B., & Schaerf, A. (2013). The third international timetabling competition. Annals of Operations Research, 1–7. doi:10.1007/s10479-013-1340-5.
  19. Santos, H. G., Ochi, L. S., & Souza, M. J. F. (2005). A tabu search heuristic with efficient diversification strategies for the class/teacher timetabling problem. ACM Journal of Experimental Algorithmics, 10, 2–9.Google Scholar
  20. Santos, H. G., Uchoa, E., Ochi, L., & Maculan, N. (2012). Strong bounds with cut and column generation for class-teacher timetabling. Annals of Operations Research, 194, 399–412.CrossRefGoogle Scholar
  21. Schaerf, A. (1999). A survey of automated timetabling. Artificial Intelligence Review, 13(2), 87–127.CrossRefGoogle Scholar
  22. Souza, M., Ochi, L., & Maculan, N. (2003). A GRASP-Tabu Search Algorithm for solving School Timetabling Problems. Dordrecht: Kluwer Academic Publishers.CrossRefGoogle Scholar
  23. Valourix, C., & Housos, E. (2003). Constraint programming approach for school timetabling. Computers & Operations Research, 30, 1555–1572.CrossRefGoogle Scholar
  24. Wright, M. (1996). School timetabling using heuristic search. Journal of Operational Research Society, 47, 347–357.CrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media New York 2014

Authors and Affiliations

  • George Henrique Godim da Fonseca
    • 1
  • Haroldo Gambini Santos
    • 2
  • Túlio Ângelo Machado Toffolo
    • 2
  • Samuel Souza Brito
    • 2
  • Marcone Jamilson Freitas Souza
    • 2
  1. 1.Computing and Information Systems DepartmentFederal University of Ouro PretoOuro PretoBrazil
  2. 2.Computer Science DepartmentFederal University of Ouro PretoOuro PretoBrazil

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