Particle Swarm Optimization Algorithm and Its Applications: A Systematic Review

Abstract Throughout the centuries, nature has been a source of inspiration, with much still to learn from and discover about. Some technical characteristics, including accuracy, evaluation environments, and proposed case study are involved to investigate the effectiveness of different PSO methods and applications.

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• 1 Among many others, Swarm Intelligence (SI), a substantial branch of Artificial Intelligence, is built on the intelligent collective behavior of social swarms in nature.
• 2 One of the most popular SI paradigms, the Particle Swarm Optimization algorithm (PSO), is presented in this work.
• 3 Many changes have been made to PSO since its inception in the mid 1990s.

This research advances how AI systems learn, reason, and solve problems — with direct implications for automation and scientific discovery.

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