Bat Optimization Algorithm Research Output from 2010 to 2025 through Bradford’s Law

The present paper aims to evaluate the growth of research output on the Bat Optimization Algorithm (BOA) during the period 2010-2025 using a scientometric approach. The purpose of this study is to evaluate the research status of the Bat Optimization Algorithm (BOA) and to help evaluate the academic development and new research trends and promote faster collaboration. Sources were accessed on 4 February 2026 from Web of Science Core Collection. The growth rate, sources, and citation counts were evaluated thoroughly. The research output of the BOA from 2010-2025 clearly shows the evolution of the BOA from a nascent idea to a well-established and widely used metaheuristic approach. The publication trend shows a slow start with a sudden increase after 2015 and a peak in 2022-2023. The sources were analyzed using Bradford’s Law, which shows a strong core-periphery effect. The BOA research output has clearly moved from a purely theoretical approach to a multitude of applications with a steady growth rate, international cooperation, and diversification. The study provides a comprehensive bibliometric assessment of BOA research output using productivity, citation, collaboration, and Bradford distribution indicators.