Open Access
Survey/Review Study
A Survey of Algorithms, Applications and Trends for Particle Swarm Optimization
Jingzhong Fang1
, Weibo Liu1, *
, Linwei Chen2
, Stanislao Lauria1
, Alina Miron1
, Xiaohui Liu1
Author Information
Submitted: 18 Oct 2022 | Accepted: 28 Nov 2022 | Published: 27 Mar 2023
Abstract
Particle swarm optimization (PSO) is a popular heuristic method, which is capable of effectively dealing with various optimization problems. A detailed overview of the original PSO and some PSO variant algorithms is presented in this paper. An up-to-date review is provided on the development of PSO variants, which include four types i.e., the adjustment of control parameters, the newly-designed updating strategies, the topological structures, and the hybridization with other optimization algorithms. A general overview of some selected applications (e.g., robotics, energy systems, power systems, and data analytics) of the PSO algorithms is also given. In this paper, some possible future research topics of the PSO algorithms are also introduced.
Graphical Abstract
Keywords
References
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Volume 2, Issue 1How to Cite
Fang, J., Liu, W., Chen, L., Lauria, S., Miron, A., & Liu, X. (2023). A Survey of Algorithms, Applications and Trends for Particle Swarm Optimization. International Journal of Network Dynamics and Intelligence, 2(1), 24–50. https://doi.org/10.53941/ijndi0201002
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