The Research on the Control Methods of Population Diversity in Particle Swarm Algorithm

CHEN Ji-li

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The Research on the Control Methods of Population Diversity in Particle Swarm Algorithm

更新时间：2026-09-04

- The Research on the Control Methods of Population Diversity in Particle Swarm Algorithm
- Vol. 30, Issue 6, Pages: 6-9(2013)
- 作者机构：
  
  1. 1 桂林理工大学机构信息科学与工程学院,广西,桂林,541004
  2. 2 广西空间信息与测绘重点实验室,广西,桂林,541004
- 作者简介：
- 基金信息：
- DOI：
  CLC：
- Published：2013
- 稿件说明：
移动端阅览
陈基漓. 粒子群算法种群多样性控制方法研究[J]. 微电子学与计算机, 2013, 30(6): 6-9.

CHEN Ji-li. The Research on the Control Methods of Population Diversity in Particle Swarm Algorithm[J]. 2013, 30(6): 6-9.
陈基漓. 粒子群算法种群多样性控制方法研究[J]. 微电子学与计算机, 2013, 30(6): 6-9. DOI：

CHEN Ji-li. The Research on the Control Methods of Population Diversity in Particle Swarm Algorithm[J]. 2013, 30(6): 6-9. DOI：

摘要

粒子群算法是一直典型的群体智能算法

种群多样性是影响其优化性能的一个重要因素

对几种影响种群多样性的方法如微粒的初始位置、迭代过程微粒个体执行变异操作、异步更新策略、带线性递减惯性权重的异步更新策略等进行研究.并通过对典型测试函数进行实验

给出了几种能提高微粒群算法优化性能的多样性控制方法.

Abstract

Particle swarm optimization algorithm is a typical swarm intelligence algorithm

the diversity of the population is an important factor to affect the optimize performance of particle swarm optimization algorithm.Several methods that control the population diversity are analyzed

such as the initial position of the particle

the mutation of particle that perform during the iterative process

asynchronous update strategy

and asynchronous update strategy with a linearly decreasing inertia weight.Some test functions are used for simulation experiments

and several control methods of the diversity that can improve the performance of particle swarm optimization are given.

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