Application Of Bibliometric Analysis on Root Growth Algorithm

The root growth algorithm has often been used to solve challenging optimization issues. It is one of the metaheuristic algorithms inspired by root growth in plant behaviors. An article reviewed and analyzed bibliographic data on metaheuristics but is not specific on the topic of root growth algorith...

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Bibliographic Details
Main Authors: Tengku Malim Busu, Tengku Nurul Aimi Balqis, Ahmad Kamaruddin, Saadi, Ahad, Nor Aishah, Md Ghani, Nor Azura, Hamid, Hashibah
Format: Article
Language:English
Published: UUM Press 2024
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Online Access:https://repo.uum.edu.my/id/eprint/30423/1/JCIA%2003%2001%202024%201-18.pdf
https://doi.org/10.32890/jcia2024.3.1.1
https://repo.uum.edu.my/id/eprint/30423/
https://e-journal.uum.edu.my/index.php/jcia/article/view/19350
https://doi.org/10.32890/jcia2024.3.1.1
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Summary:The root growth algorithm has often been used to solve challenging optimization issues. It is one of the metaheuristic algorithms inspired by root growth in plant behaviors. An article reviewed and analyzed bibliographic data on metaheuristics but is not specific on the topic of root growth algorithm. Therefore, this article presents a bibliometric analysis based on the topic of the root growth algorithm. It reviews the publication from the Scopus database. Based on the search process done on 14 February 2023 using the keywords of root growth algorithm, this article managed to gather 1836 articles from 1976-2023. However, this article only focuses on Engineering, Computer Science, and Mathematics to ensure it relates to the area the researcher wants to explore. Moreover, articles in the year 2023 will also be excluded due to incomplete data. After the researcher limited the data to those areas, it was reduced to 837 articles. This article uses three types of software: Microsoft Excel, VOSviewer software, and Harzing’s Publish or Perish software to analyze the frequency, visualization mapping, and citation metrics analysis, respectively. The finding from the bibliometric analysis shows the researcher has noticed that the total publication keeps increasing rapidly from 2014 until 2022. The country that contributes the most to the root growth algorithm topic is China. Furthermore, the most productive author is Chen, H. and all the top 10 productive authors are from China except for Christofides, P. D., who comes from the United States. The top 10 sources of root growth algorithm research contributed over a quarter of the total articles (231 or 27.60%). The results of this study have significant implications for increasing the number of practices using the root growth algorithm in future research. Last but not least, bibliometric analysis on the topic of root growth algorithm is needed to identify influential publications, understand research trends, evaluate research impact, and identify potential research gaps in a concise manner, which helps researchers and readers stay informed, make informed decisions, and contribute to the advancement of knowledge in the field.