Bibliometric analysis of particle swarm optimization algorithm.
DOI:
https://doi.org/10.5281/Keywords:
Algorithm, Analysis, Bibliometric, Optimization, Particle, SwarmAbstract
Nowadays, metaheuristic algorithms are used in large-scale work environments in order to reach the optimum solution in the solution space faster by using efficient search operations and to find solutions to optimization problems. One of these algorithms, the Particle Swarm Optimization algorithm, has been popularly preferred in recent years due to its ease of coding and high performance, and its successful results in various optimization problems, especially in complex and multi-dimensional problems. Within the scope of this study, a bibliometric analysis of the researches conducted in the literature in the last five years (2020-2024) using the Particle Swarm Optimization algorithm was conducted. In the study, 29867 publications were reached by searching the keywords “Particle”, “Swarm” and “Optimization” in the Web of Science database. The data obtained from the Web of Science database was analyzed using literature analysis, network analysis and visual data discovery methods in the VOSviewer program. As a result of the analyzes, studies related to various criteria such as category distribution, distribution of publications over the years, document types of publications, index distribution of publications, distribution of publications by country were given quantitatively with all their details.
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