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Review | Open Access

Swarm intelligence: A survey of model classification and applications

Chao WANGaShuyuan ZHANGaTianhang MAaYuetong XIAOaMichael Zhiqiang CHENbLei WANGa( )
School of Automation Science and Electrical Engineering, Beihang University, Beijing 100191, China
School of Automation, Nanjing University of Science and Technology, Nanjing 210094, China

Peer review under responsibility of Editorial Committee of CJA.

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Abstract

Swarm Intelligence (SI) is a collective behavior that emerges from interaction between individuals in a group. Typical SI includes fish schooling, ant foraging, bird migration, and so on. A great deal of models have been introduced to characterize the mechanism of SI. This article reviews several typical models and classifies them into four categories: self-driven particle models, with Boids model as the primary example; pheromone communication models, including the ant colony pheromone model which serves as the foundation for ant colony optimization; leadership decision models, utilizing the hierarchical dynamics model of pigeon flock as a prime instance; empirical research models, which employ the topological rule model of starling flock as a classic model. On this basis, each type of model is elaborated upon in terms of its typical model overview, applications, and model evaluation. More specifically, multi-agent swarm control, path optimization and obstacle avoidance, formation and consensus control, trajectory tracking in the dense crowd and social networks analysis are surveyed in the application of each category, respectively. Furthermore, the more precise and effective modeling techniques for leadership decision and empirical research models are described. Limitations and potential directions for further exploration in the study of SI are presented.

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Chinese Journal of Aeronautics

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Cite this article:
WANG C, ZHANG S, MA T, et al. Swarm intelligence: A survey of model classification and applications. Chinese Journal of Aeronautics, 2025, 38(3). https://doi.org/10.1016/j.cja.2024.03.019

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Received: 20 November 2023
Revised: 28 December 2023
Accepted: 28 February 2024
Published: 20 March 2024
© 2024 Chinese Society of Aeronautics and Astronautics.

This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).