Multi-swarm PSO algorithm based on parallel structure

ZHANG Tianjia; YANG Yongsheng

doi:10.13873/J.1000-9787(2020)09-0119-03

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Multi-swarm PSO algorithm based on parallel structure

更新时间：2025-09-11

- Multi-swarm PSO algorithm based on parallel structure
- Vol. 39, Issue 9, Pages: 119-121(2020)
- 作者机构：
  
  上海交通大学航空航天学院
- 作者简介：
- 基金信息：
- DOI：10.13873/J.1000-9787(2020)09-0119-03
  CLC： TP18
- Published：2020
- 稿件说明：
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[1]张天佳,杨永胜.基于并行结构的多种群粒子群优化算法[J].传感器与微系统,2020,39(09):119-121.

ZHANG Tianjia, YANG Yongsheng. Multi-swarm PSO algorithm based on parallel structure[J]. 2020, 39(9): 119-121.
[1]张天佳,杨永胜.基于并行结构的多种群粒子群优化算法[J].传感器与微系统,2020,39(09):119-121. DOI： 10.13873/J.1000-9787(2020)09-0119-03.

ZHANG Tianjia, YANG Yongsheng. Multi-swarm PSO algorithm based on parallel structure[J]. 2020, 39(9): 119-121. DOI： 10.13873/J.1000-9787(2020)09-0119-03.

摘要

针对粒子群优化（PSO）算法中存在的多样性差、易早熟收敛和鲁棒性不强等缺点

提出一种基于并行结构的多种群PSO算法。并行多种群算法在基本粒子群算法的基础上

增加了分别能加速和减缓粒子移动的两种更新公式

既改善了粒子群算法种群多样性差的缺陷

又能保证算法的计算精度。采用十种典型的标准测试函数对提出的算法进行了仿真实验。测试结果表明:与基本粒子群优化算法相比

并行多种群粒子群算法收敛速度更快

运算时间更短。

Abstract

Aiming at the disadvantages of the particle swarm optimization（ PSO） algorithm

such as poor diversity

premature convergence and weak robustness

a multi-swarm PSO algorithm based on parallel structure is proposed.On the basis of the basic PSO

the parallel multi-swarm algorithm adapts two updating formulas which can accelerate and slow down the particle movement respectively

which not only improves the poor population diversity of PSO

but also ensures the computational precision of the algorithm. Ten typical benchmark functions are used for simulation of the proposed algorithm. The results show that compared with the basic PSO algorithm

the multiswarm PSO algorithm based on the parallel structure has faster convergence speed and shorter operation time.

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