Algorithm Research & Explore
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App. Res. of Comp. Printed Article
Vol. 37, 2020 No. 8
2344-2348,2370

Particle swarm optimization for dynamic spatial variability of superior quality individuals

Sun Huia,b,c
Deng Zhichenga,b,c
Zhao Jiaa,b,c
Wang Huia,b,c
a. School of Information Engineering, b. National-Local Joint Engineering Laboratory of Water Engineering Safety & Effective Utilization of Resources in Poyang Lake Area, c. Jiangxi Province Key Laboratory of Water Information Cooperative Sensing & Intelligent Processing, Nanchang Institute of Technology, Nanchang 330099, China
DOI: 10.19734/j.issn.1001-3695.2019.03.0056

Abstract

In the early stage of evolution, the particle swarm optimization requires large dimensional changes to search for more new regions. Later, only a few dimensions fail to reach the optimal solution and fall into local optimum. Aiming at the above problems, this paper proposed a particle swarm optimization for dynamic spatial variability of superior quality individuals. After selecting the superior quality individuals, it picked two different dimensions, let one of the dimensions fly to the other dimension with Lévy flight to obtain the new variation dimension value, and the proceed dimension of variation decreased as the number of iterations increased. The diversity of the population was further enhanced and the exploration and exploitation capabilities were balanced. Compared the proposed algorithm with the state of the art particle swarm optimization variants on the 12 benchmark function, and the experimental results show that the proposed algorithm is more advantageous in convergence speed and precision.

Foundation Support

国家自然科学基金资助项目(61663029,51669014,61663028)
江西省杰出青年基金资助项目(2018ACB21029)
江西省杰出青年人才计划资助项目(20171BCB23075)
江西省自然科学基金资助项目(20171BAB202035)
江西省教育厅落地计划资质项目(KJLD13096)
江西省2018年度研究生创新专项资金项目(YC2018-S422)
南昌工程学院2018年大学生创新创业训练计划项目

Publish Information

DOI: 10.19734/j.issn.1001-3695.2019.03.0056
Publish at: Application Research of Computers Printed Article, Vol. 37, 2020 No. 8
Section: Algorithm Research & Explore
Pages: 2344-2348,2370
Serial Number: 1001-3695(2020)08-021-2344-05

Publish History

[2020-08-05] Printed Article

Cite This Article

孙辉, 邓志诚, 赵嘉, 等. 优质个体最优动态空间变异的粒子群优化算法 [J]. 计算机应用研究, 2020, 37 (8): 2344-2348,2370. (Sun Hui, Deng Zhicheng, Zhao Jia, et al. Particle swarm optimization for dynamic spatial variability of superior quality individuals [J]. Application Research of Computers, 2020, 37 (8): 2344-2348,2370. )

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  • Application Research of Computers Monthly Journal
  • Journal ID ISSN 1001-3695
    CN  51-1196/TP

Application Research of Computers, founded in 1984, is an academic journal of computing technology sponsored by Sichuan Institute of Computer Sciences under the Science and Technology Department of Sichuan Province.

Aiming at the urgently needed cutting-edge technology in this discipline, Application Research of Computers reflects the mainstream technology, hot technology and the latest development trend of computer application research at home and abroad in a timely manner. The main contents of the journal include high-level academic papers in this discipline, the latest scientific research results and major application results. The contents of the columns involve new theories of computer discipline, basic computer theory, algorithm theory research, algorithm design and analysis, blockchain technology, system software and software engineering technology, pattern recognition and artificial intelligence, architecture, advanced computing, parallel processing, database technology, computer network and communication technology, information security technology, computer image graphics and its latest hot application technology.

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