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Increase Methodology of Design of Course Timetabling Problem for Students, Classrooms, and Teachers

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Nature-Inspired Design of Hybrid Intelligent Systems

Part of the book series: Studies in Computational Intelligence ((SCI,volume 667))

Abstract

The aim of the Course Timetabling problem is to ensure that all the students take their required classes and adhere to resources that are available in the school. The set of constraints those must be considered in the design of timetabling involves students, teachers, and classrooms. In the state of the art are different methodologies of design for Course Timetabling problem, in this paper we extend the proposal from Soria in 2013, in which they consider variables of students and classrooms, with four set of generic structures. This paper uses Soria’s methodology to adding two more generic structures considering teacher restriction. We show an application of some different Metaheuristics using this methodology. Finally, we apply nonparametric test Wilcoxon signed-rank with the aim to find which metaheuristic algorithm shows a better performance in terms of quality.

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References

  1. Ortiz-Aguilar Lucero de M.: Diseño de horarios de alumnos y maestros mediante técnicas de Soft Computing, para una Institución Educativa. Master’s thesis, InstitutoTecnológico de León (2016).

    Google Scholar 

  2. De Werra, D.: An introduction to timetabling. European Journal of Operational Research(2), 151 – 162 (1985).

    Google Scholar 

  3. Obit, J. H., Landa-Silva, D., Ouelhadj, D., Khan Vun, T., & Alfred, R.: Designing a multi-agent approach system for distributed course timetabling. IEEE. (2011).

    Google Scholar 

  4. Asratian, A. S., de Werra, D., Luleå.: A generalized class–teacher model for some timetabling problems. University of Technology, Department of Engineering Sciences and Mathematics, Mathematical Science, & Mathematics. European Journal of Operational Re-search, 143(3), 531-542. (2002). doi:10.1016/S0377-2217(01)00342-3.

  5. Deng, X., Zhang, Y., Kang, B., Wu, J., Sun, X., Deng, Y.: An application of genetic algorithm for university course timetabling problem. 2119-2122 (2011). doi:10.1109/CCDC.2011.5968555.

  6. Mahiba, A. A., Durai, C. A. D.: Genetic algorithm with search bank strategies for university course timetabling problem. Procedia Engineering, 38, 253-263. (2012). doi:10.1016/j.proeng.2012.06.033.

  7. Soria-Alcaraz, J. A., Carpio, J. M.; Puga, Hé., Melin, P.; Terashima-Marn, H., Reyes, L. C., Sotelo-Figueroa, M. A. Castillo, O., Melin, P., Pedrycz, W. &Kacprzyk, J.: Generic Memetic Algorithm for Course Timetabling ITC2007 Recent Advances on Hybrid Approaches for Designing Intelligent Systems, Springer, 547, 481-492. (2014).

    Google Scholar 

  8. Nguyen K., Lu T., Le T., Tran N.: Memetic algorithm for a university course timetabling problem, 132(1) 67-71. (2011). doi:10.1007/978-3-642-25899-2_10.

  9. Aladag C., Hocaoglu G. A tabu search algorithm to solve a course timetabling problem. hacettepe journal of mathematics and statistics, 36(1), 53-64. (2007).

    Google Scholar 

  10. Moscato, P.: “On Evolution, Search, Optimization, Genetic Algorithms and Martial Arts: Towards Memetic Algorithms”. Caltech Concurrent Computation Program (report 826). (1989).

    Google Scholar 

  11. Zheng, S., Wang, L., Liu, Y., & Zhang, R.: A simulated annealing algorithm for university course timetabling considering travelling distances. International Journal of Computing Science and Mathematics, 6(2), 139-151. (2015). doi:10.1504/IJCSM.2015.069461.

  12. Joudaki M., Imani M., Mazhari N. Using improved Memetic algorithm and local search to solve University Course Timetabling Problem (UCTTP). Doroud, Iran: Islamic Azad University. (2010).

    Google Scholar 

  13. Thepphakorn T., Pongcharoen P., Hicks C.: An ant colony based timetabling tool. International Journal of Production Economics, 149, 131-144. (2014). doi:10.1016/j.ijpe.2013.04.026.

  14. Soria-Alcaraz J., Ochoa G., Swan J., Carpio M., Puga H., Burke E.: Effective learning hyper-heuristics for the course timetabling problem. European Journal of Operational Research, 238(1), 77-86. (2014) doi:10.1016/j.ejor.2014.03.046.

  15. Lewis, M. R. R.: Metaheuristics for university course timetabling. Ph.D. Thesis, Napier University. (2006).

    Google Scholar 

  16. Cooper, T. B. & Kingston, J. H.: The Complexity of Timetable Construction Problems. PhD thesis, The University of Sydney. (1995).

    Google Scholar 

  17. Wolpert, H., Macready, G.: No free lunch Theorems for Search. Technical report The Santa Fe Institute, 1 (1996).

    Google Scholar 

  18. Adriaen M., De Causmaecker P., Demeester P., VandenBerghe G.: Tackling the university course timetabling problem with an aggregation approach. In Proceedings of the 6th International Conference on the Practice and Theory of Automated Timetabling, Brno.,1, 330-335. (2006).

    Google Scholar 

  19. Soria-Alcaraz, J.A.: Diseño de horarios con respecto al alumno mediante tecnicas de computo evolutivo. Master’s thesis, Instituto Tecnologico de Leon (2010).

    Google Scholar 

  20. McCollum., B. University timetabling: Bridging the gap between research and practice. In Proceedings of the 6th International Conference on the Practice and Theory of Automated Timetabling, Brno, 1, 15-35. (2006).

    Google Scholar 

  21. Conant-Pablos, S.E., Magaa-Lozano, D.J., Terashima-Marin, H.: Pipelining memetic algorithms, constraint satisfaction, and local search for course timetabling. MICAI Mexican international conference on artificial intelligence 1, 408–419 (2009).

    Google Scholar 

  22. DammakAbdelaziz, ElloumiAbdelkarim, K. H. Classroom assignment for exam timetabling. Advances in Engineering Software, 37(10), 659-666. (2006).

    Google Scholar 

  23. Soria-Alcaraz Jorge, A., Carpio, M., Puga, H., Sotelo-Figueroa, M.: Method-ology of design: A novel generic approach applied to the course timetabling problem. In: P. Melin, O. Castillo (eds.) Soft Computing Applications in Op-timization, Control, and Recognition, Studies in Fuzziness and Soft Compu-ting, vol. 294, pp. 287–319. Springer Berlin Heidelberg (2013).

    Google Scholar 

  24. Alcaraz J. A. S.: Integración de un esquema de Diseño en Algoritmos de Dos fases con técnicas CSP para calendarización de eventos. PhD thesis, Instituto Tecnologico de Leon. (2014).

    Google Scholar 

  25. Alba, E.: Parallel Metaheuristics: A New Class of Algorithms. Wiley-Interscience. (2005).

    Google Scholar 

  26. Goldberg, D. E.: Genetic Algorithms in Search, Optimization and Machine Learning. Boston, MA, USA: Addison-Wesley Longman Publishing Co., Inc., 1st edition. (1989).

    Google Scholar 

  27. Alba, E. & Dorronsoro, B.: The state of the art in cellular evolutionary algorithms. Cellular Genetic Algorithms, 1, 21-34. (2008).

    Google Scholar 

  28. Lourenco, H., Martin, O., &Stützle, T. Iterated local search. In F. Glover, G. Kochenberger, & F. S. Hillier (Eds.), Handbook of Metaheuristics, volume 57 of International Series in Operations Research & Management Science, 320-353. Springer New York. (2003).

    Google Scholar 

  29. Talbi, E.-G. Metaheuristics: From Design to Implementation. Wiley Publishing. (2009).

    Google Scholar 

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Acknowledgment

Authors thanks the support received from the Consejo Nacional de Ciencia y Tecnologia (CONACYT) México

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Authors and Affiliations

  1. División de Estudios de Posgrado E Investigación, TNM-Instituto Tecnológico de León, León, Mexico

    Lucero de M. Ortiz-Aguilar, Martín Carpio, Héctor Puga, Manuel Ornelas-Rodríguez & Carlos Lino

  2. Universidad de Guanajuato, Guanajuato, Mexico

    Jorge A. Soria-Alcaraz

Authors
  1. Lucero de M. Ortiz-Aguilar
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  2. Martín Carpio
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  3. Héctor Puga
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  4. Jorge A. Soria-Alcaraz
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  5. Manuel Ornelas-Rodríguez
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  6. Carlos Lino
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Corresponding author

Correspondence to Martín Carpio .

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Editors and Affiliations

  1. Division of Graduate Studies and Research, Tijuana Institute of Technology, Tijuana, BC, Mexico

    Patricia Melin

  2. Division of Graduate Studies and Research, Tijuana Institute of Technology, Tijuana, BC, Mexico

    Oscar Castillo

  3. Polish Academy of Sciences, Systems Research Institute, Warsaw, Poland

    Janusz Kacprzyk

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de M. Ortiz-Aguilar, L., Carpio, M., Puga, H., Soria-Alcaraz, J.A., Ornelas-Rodríguez, M., Lino, C. (2017). Increase Methodology of Design of Course Timetabling Problem for Students, Classrooms, and Teachers. In: Melin, P., Castillo, O., Kacprzyk, J. (eds) Nature-Inspired Design of Hybrid Intelligent Systems. Studies in Computational Intelligence, vol 667. Springer, Cham. https://doi.org/10.1007/978-3-319-47054-2_47

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  • DOI: https://doi.org/10.1007/978-3-319-47054-2_47

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-47053-5

  • Online ISBN: 978-3-319-47054-2

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