Bibliometric analysis of the use of genetic algorithms in scientific publications with text mining approach

Genetic Algorithms (GA) are widely used in the fields of optimization and problem solving. In recent years, there has been an increase in scientific publications on the applications of GA in different disciplines. This study examines the use of GA in scientific publications using VOSviewer and R Studio, which are subject modeling techniques and biometric analysis methods. With bibliometric analysis, parameter results related to authors, institutions, collaboration networks, journals and keywords were obtained within the scope of scientific publications in the field of GA. Conceptual maps with terms and topics were created with topic modeling Latent Dirichlet Allocation. In the field of GA, 2143 publications between 1989-2025 in the Web of Science database were analyzed. According to the results of the analysis, it is seen that GA is intensively studied in fields such as engineering, computer science, artificial intelligence and bioinformatics. In 1999, it was determined that there was a remarkable increase in the number of publications and this increase is related to the adoption of GA in different scientific fields. China, the United States of America and Spain are among the leading countries producing the highest number of publications in this field. Turkey's connection with the leading countries in this field is a significant indicator in terms of its productivity. While the study provides researchers with a holistic view of the scientific development of GA, it also reveals potential research themes for future studies.