The Convergence Analysis of the Uniform Search Particle Swarm Optimization

WU Xiao-jun; LI Feng; MA Yue; XING Yun-hong

doi:10.3969/j.issn.0372-2112.2012.06.008

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The Convergence Analysis of the Uniform Search Particle Swarm Optimization

更新时间：2025-07-16

- The Convergence Analysis of the Uniform Search Particle Swarm Optimization
- Acta Electronica Sinica Vol. 40, Issue 6, Pages: 1115-1120(2012)
- 作者机构：
  
  1. 陕西师范大学现代教学技术教育部重点实验室,陕西,西安,710062
  2. 陕西师范大学计算机科学学院,陕西,西安,710062
  3. 陕西师范大学物理学与信息技术学院,陕西,西安,710062
  4. 陕西师范大学现代教学技术教育部重点实验室陕西西安,710062
  5. 陕西师范大学计算机科学学院陕西西安,710062
  6. 陕西师范大学物理学与信息技术学院陕西西安,710062
- 作者简介：
- 基金信息：
- DOI：10.3969/j.issn.0372-2112.2012.06.008
  CLC： TP301.6
- Published：2012
- 稿件说明：
移动端阅览
WU Xiao-jun, LI Feng, MA Yue, et al. The Convergence Analysis of the Uniform Search Particle Swarm Optimization[J]. Acta Electronica Sinica, 2012, 40(6): 1115-1120.
DOI：

WU Xiao-jun, LI Feng, MA Yue, et al. The Convergence Analysis of the Uniform Search Particle Swarm Optimization[J]. Acta Electronica Sinica, 2012, 40(6): 1115-1120. DOI： 10.3969/j.issn.0372-2112.2012.06.008.

摘要

本文将均匀搜索粒子群算法(Uniform search Particle Swarm Optimization

简称UPSO)的位置更新公式变换为一个差分方程

求解差分方程得到非递推的位置更新公式

推导解的收敛条件并求出了UPSO对学习系数

及惯性系数

的收敛区域

最后通过6个Benchmark函数仿真实验对收敛区域的正确性进行验证

实验结果表明学习系数和惯性系数在收敛区域内时的UPSO收敛

不在收敛区域外时UPSO发散.

Abstract

The uniform search particle swarm optimization (UPSO) algorithm formula was tsansformed into a differential equation.Solving the differential equation

we get a non-recurrence location update formula

and the UPSO's convergence region for learning coefficient

and inertia coefficient

were concluded by deducing the solution convergence conditions.Finally simulation experiments were provided on the selected location of the region of convergency by 6 Benchmark functions.Experimental results show that UPSO converges when the learning coefficient and inertial coefficient are in the convergence region and diverge outside convergence region.

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