Abstract
The Curriculum-Based Course Timetabling (CB-CTT) is a problem periodically solved in educational institutions, still, because of the diversity of conditions that define it within different educational contexts, selecting the solution approach that best suits the particular requirements of an instance is a complex task that can be properly formulated as an algorithm selection problem. In this paper, we analyze four selection mechanisms that could be used as algorithms recommendation models. From this analysis, it is concluded that the proposed regression approach exhibited the highest performance. Therefore, it could be applied for algorithm recommendation to solve CB-CTT instances.
We gratefully acknowledge the support of CONACYT-Mexico (Reg. 618204/461410).
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de la Rosa-Rivera, F., Nunez-Varela, J.I. (2019). Implementation of Algorithm Recommendation Models for Timetabling Instances. In: Martínez-Villaseñor, L., Batyrshin, I., Marín-Hernández, A. (eds) Advances in Soft Computing. MICAI 2019. Lecture Notes in Computer Science(), vol 11835. Springer, Cham. https://doi.org/10.1007/978-3-030-33749-0_2
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DOI: https://doi.org/10.1007/978-3-030-33749-0_2
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