Abstract
In this paper a non-standard constructive evolutionary approach is described to solve efficiently timetabling problems, so necessary at every school and university. The basic scheme of Genetic Algorithms has been used, but some operators have been adapted to the characteristics of the problem under consideration, improving its resolution capability. Although the design requires more effort, it helps to reduce the search space. Feasible timetables have been considered as hard constraints in the problem formulation. It has been proved that modified genetic algorithms can be very useful in this kind of problems for the easiness of including new constrains and the effectiveness of the resolution, exhibiting a good compromise between computational time and optimal reaching.
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References
Burke, E.K., Elliman, D.G., Weare, R.F.: A Genetic Algorithm Based University Timetabling System. In: 2nd East-West Int. Conf. on Comp. Tech. in Education, Ukraine, vol. 1, pp. 35–40 (1994)
Müller, T.: Some Novel Approaches to Lecture Timetabling. In: Proc. of the 4th Workshop on Constraints programming for Decision and Control, Gliwice, Poland, pp. 31–37 (2002)
Carter, M.W., Laporte, G.: Recent Developments in Practical Course Timetabling. In: Burke, E.K., Carter, M. (eds.) PATAT 1997. LNCS, vol. 1408, pp. 3–19. Springer, Heidelberg (1998)
Caldeira, J.P., Rosa, A.C.: School Timetabling Using Genetic Search. In: Proceedings of the 2nd Int. Conf. on the Practice and Theory of Automated Timetabling, Toronto (1997)
dos Santos, A.M., Marques, E., Ochi, L.S.: Design and Implementation of a Timetable System Using a Genetic Algorithm. In: Proceedings of the 2nd Int. Conf. on the Practice and Theory of Automated Timetabling, Toronto (1997)
Michalewicz, Z., Fogel, D.B.: How to Solve It: Modern Heuristics. Springer, Heidelberg (2000)
Cooper, T.B., Kingston, J.H.: The Complexity of Timetable Construction Problems. In: Burke, E.K., Ross, P. (eds.) PATAT 1995. LNCS, vol. 1153, pp. 283–295. Springer, Heidelberg (1996)
Bartak, R.: Dynamic Constraint Models for Planning and Scheduling. In: Apt, K.R., Kakas, A.C., Monfroy, E., Rossi, F. (eds.) Compulog Net WS 1999. LNCS (LNAI), vol. 1865, pp. 237–255. Springer, Heidelberg (2000)
Michalewicz, Z., Janikow, C.Z.: Handling Constraints in Genetic Algorithms. In: Proc. Of the 4th Int. Conf. on Genetic Algorithms, pp. 151–157. Morgan Kaufmann Publishers, San Francisco (1991)
Meisels, A., Lusternik, N.: Experiments on Networks of Employee Timetabling Problems. In: Proceedings of the 2nd Int. Conf. on the Practice and Theory of Automated Timetabling, Toronto (1997)
Goldberg, D.E.: Genetic Algorithm in Search, Optimization and Machine Learning. Addison-Wesley, Reading (1989)
Michalewicz, Z.: Genetic Algorithms + Data Structures = Evolution Programs, 3rd edn. Springer, New York (1996)
Schaerf, A.: A Survey of Automated Timetabling. Artificial Intelligence Review 13(2), 87–127 (1999)
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Fernández, C., Santos, M. (2003). A Non-standard Genetic Algorithm Approach to Solve Constrained School Timetabling Problems. In: Moreno-Díaz, R., Pichler, F. (eds) Computer Aided Systems Theory - EUROCAST 2003. EUROCAST 2003. Lecture Notes in Computer Science, vol 2809. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-45210-2_4
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DOI: https://doi.org/10.1007/978-3-540-45210-2_4
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