Abstract
Since its inception in 2014, the Competitive Swarm Optimizer (CSO) has emerged as a significant advancement in the field of swarm intelligence, particularly in addressing large-scale optimization challenges. This paper offers a comprehensive review of a decade of developments in CSO research, synthesizing a vast array of research efforts to underscore the pivotal CSO variants, their foundational principles, and notable achievements. It encompasses a broad spectrum of applications, including single-objective, multi-objective, and engineering optimization problems, and introduces a meticulously constructed taxonomy to facilitate further investigation into CSO-related research. Additionally, this paper incorporates comparative analyses and in-depth investigations, thereby providing enhanced insight into both the historical evolution and future research directions of CSO.
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