University course timetabling with genetic algorithm: A laboratory excercises case study

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Abstract

This paper describes the application of a hybrid genetic algorithm to a real-world instance of the university course timetabling problem. We address the timetabling of laboratory exercises in a highly constrained environment, for which a formal definition is given. Solution representation technique appropriate to the problem is defined, along with associated genetic operators and a local search algorithm. The approach presented in the paper has been successfully used for timetabling at the authors' institution and it was capable of generating timetables for complex problem instances. ©Springer-Verlag Berlin Heidelberg 2009.

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Bratković, Z., Herman, T., Omrčen, V., Čupić, M., & Jakobović, D. (2009). University course timetabling with genetic algorithm: A laboratory excercises case study. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 5482 LNCS, pp. 240–251). https://doi.org/10.1007/978-3-642-01009-5_21

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