A Survey of Algorithms, Applications and Trends for Par-ticle Swarm Optimization

被引:63
作者
Fang, Jingzhong [1 ]
Liu, Weibo [1 ]
Chen, Linwei [2 ]
Lauria, Stanislao [1 ]
Miron, Alina [1 ]
Liu, Xiaohui [1 ]
机构
[1] Brunel Univ London, Dept Comp Sci, Uxbridge UB8 3PH, Middlesex, England
[2] Univ Warwick, Sch Engn, Coventry CV4 7AL, England
来源
INTERNATIONAL JOURNAL OF NETWORK DYNAMICS AND INTELLIGENCE | 2023年 / 2卷 / 01期
关键词
particle swarm optimization; optimization; evolutionary computation; inertia weight; acceler-ation coefficient; INFORMED PARTICLE SWARM; POWER POINT TRACKING; FUZZY C-MEANS; PSO ALGORITHM; UNIT COMMITMENT; DISPATCH; PARAMETERS; PV; IDENTIFICATION; CONTROLLER;
D O I
10.53941/ijndi0201002
中图分类号
学科分类号
摘要
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.
引用
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页码:24 / 50
页数:27
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