A New Composite Particle Swarm Optimization Introduced in Random Perturbation Operation

MAN Chun-tao; WANG Su-ju; ZHANG Li-yong; DONG Xiu-jie

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A New Composite Particle Swarm Optimization Introduced in Random Perturbation Operation

更新时间：2026-07-10

- A New Composite Particle Swarm Optimization Introduced in Random Perturbation Operation
- Vol. 14, Issue 1, Pages: 31-34(2009)
- 作者机构：
  
  1. 哈尔滨理工大学自动化学院
  2. 哈尔滨理工大学测控技术与通信工程学院
- 作者简介：
- 基金信息：
- DOI：
  CLC： TP18
- Published：2009
- 稿件说明：
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MAN Chun-tao, WANG Su-ju, ZHANG Li-yong, et al. A New Composite Particle Swarm Optimization Introduced in Random Perturbation Operation[J]. 2009, 14(1): 31-34.
DOI：

MAN Chun-tao, WANG Su-ju, ZHANG Li-yong, et al. A New Composite Particle Swarm Optimization Introduced in Random Perturbation Operation[J]. 2009, 14(1): 31-34. DOI：

摘要

针对传统粒子群优化算法不能根据实际问题自行选择参数

搜索后期容易陷入局部最优的缺点

提出了一种基于随机摄动的复合粒子群优化算法.该算法在利用简单遗传算法优选粒子群三个参数的基础上

根据粒子种群间的相互独立性

引入随机摄动操作

提高了解的精确度和算法的搜索效率

同时通过对种群中的最差粒子重新进行初始化来保持种群的多样性

以避免陷入局部最优解.

Abstract

Traditional Swarm Optimization algorithm can not choose parameters according to practical problem

and plunge into the local extremum point easily at the end of the searching.To solve the above disadvantages

in this paper

a new composite particle swarm optimization introduced in random perturbation operation is presented.It not only expands the application areas of PSO algorithm

but also improves searching efficiency and solving accuracy

at the same time

avoiding plunge into he local extremum point by re-ini...

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