A Dynamic Boundary Based Particle Swarm Optimization

LI Ying-qiu; CHI Yu-hong; WEN Tao

doi:10.3969/j.issn.0372-2112.2013.05.006

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A Dynamic Boundary Based Particle Swarm Optimization

更新时间：2025-07-16

- A Dynamic Boundary Based Particle Swarm Optimization
- Acta Electronica Sinica Vol. 41, Issue 5, Pages: 865-870(2013)
- 作者机构：
  
  1. 东北大学软件中心,辽宁,沈阳,110004
  2. 大连东软信息学院计算机系,辽宁,大连,116023
  3. 中国人民解放军65053部队,辽宁,大连,116113
  4. 东北大学软件中心辽宁沈阳,110004
  5. 大连东软信息学院计算机系辽宁大连,116023
  6. 中国人民解放军65053部队辽宁大连,116113
- 作者简介：
- 基金信息：
  
  National Natural Science Foundation of China (No.61170168, No.61170169)
- DOI：10.3969/j.issn.0372-2112.2013.05.006
  CLC： TP18
- Published：2013
- 稿件说明：
移动端阅览
LI Ying-qiu, CHI Yu-hong, WEN Tao. A Dynamic Boundary Based Particle Swarm Optimization[J]. Acta Electronica Sinica, 2013, 41(5): 865-870.
DOI：

LI Ying-qiu, CHI Yu-hong, WEN Tao. A Dynamic Boundary Based Particle Swarm Optimization[J]. Acta Electronica Sinica, 2013, 41(5): 865-870. DOI： 10.3969/j.issn.0372-2112.2013.05.006.

摘要

2007年提出的标准粒子群优化算法(PSO-2007)在进化的后期容易出现停滞现象而导致早熟收敛

为此本文提出了一种基于动态边界的粒子群优化算法(DBPSO).该算法根据停滞期粒子运动的特点

将边界动态调整策略引入到PSO-2007中

通过跟踪粒子飞行位置的分布动态调整搜索空间的边界

引导粒子在更有效的区域内进行搜索

从而减轻早熟收敛

提高收敛精度.典型测试函数的求解实验结果表明DBPSO是可行而有效的.

Abstract

Standard particle swarm optimization presented in 2007(namely

PSO-2007)inclines towards stagnation phenomena in the later stage of evolution

which leads to premature convergence.Therefore

a PSO based on dynamic boundary(namely

DBPSO)is proposed in this paper.According to the movement characteristics of particles at stagnation stage

DBPSO introduces a strategy of boundary adjusting in PSO-2007.By tracking the distribution of the particles’locations

DBPSO adjusts the boundary of search space dynamically

which could guide the particles to more promising region.This strategy helps PSO-2007 decrease premature convergence and improve convergence precision.The results of experiments of four typical functions show that DBPSO are feasible and effective.

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