Parameter tuning in metaheuristics: a bibliometric and gap analysis

Parameter tuning in metaheuristics: a bibliometric and gap analysis

19 January 2024 | Deepika Kaushik, Mohammad Nadeem
This study by Deepika Kaushik and Mohammad Nadeem focuses on parameter tuning (PT) in metaheuristic algorithms, a critical aspect that controls various aspects of these algorithms. The research employs two main analyses: bibliometric analysis (BA) and gap analysis (GA). The BA provides a quantitative overview of the literature, offering a multi-dimensional view of the studies conducted from 2002 to 2022 using the Scopus database. The GA identifies gaps in the research field, helping researchers understand the existing gaps and directions for future work. This is the first study to present both BA and GA for PT methods. The study aims to provide a structured and comprehensive view of the applicability, relevancy, and future scope of PT. The literature review covers general PT approaches, excluding those specific to applications like energy conservation and logistic management. The data for the study was retrieved on November 9, 2022, and the results are presented in the form of charts and a network map using VOSViewer. The findings highlight the challenges and opportunities in the field of PT, emphasizing the need for more structured and gap-filled research.This study by Deepika Kaushik and Mohammad Nadeem focuses on parameter tuning (PT) in metaheuristic algorithms, a critical aspect that controls various aspects of these algorithms. The research employs two main analyses: bibliometric analysis (BA) and gap analysis (GA). The BA provides a quantitative overview of the literature, offering a multi-dimensional view of the studies conducted from 2002 to 2022 using the Scopus database. The GA identifies gaps in the research field, helping researchers understand the existing gaps and directions for future work. This is the first study to present both BA and GA for PT methods. The study aims to provide a structured and comprehensive view of the applicability, relevancy, and future scope of PT. The literature review covers general PT approaches, excluding those specific to applications like energy conservation and logistic management. The data for the study was retrieved on November 9, 2022, and the results are presented in the form of charts and a network map using VOSViewer. The findings highlight the challenges and opportunities in the field of PT, emphasizing the need for more structured and gap-filled research.
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Understanding Parameter tuning in metaheuristics%3A a bibliometric and gap analysis