Evolution of Research On Timetable Generation In Higher Education: Bibliometric Analysis From 2014 To 2024

This study presents a bibliometric analysis of scientific output on timetable generation in higher education (University Timetabling) between 2014 and 2024. The research was conducted systematically in the Scopus and Google Scholar databases, using standardized queries and specific keywords. From an initial set of 818 publications, 403 documents were selected based on strict inclusion and exclusion criteria. The results show a sharp increase in scientific production between 2014 and 2020, followed by a significant slowdown from 2021 onwards. The literature analyzed reveals a strong predominance of computational approaches, in particular heuristics and meta-heuristics, such as genetic algorithms, simulated annealing, and hyper-heuristics. Main contributions of the study: (i) it systematizes the evolution of research over a decade, distinguishing clear phases of growth and stagnation; (ii) organizes existing approaches into a taxonomy of optimization methods applied to the problem of schedule generation; and (iii) identifies methodological and thematic gaps, proposing a future research agenda geared towards more robust, adaptive solutions aligned with real institutional contexts.