A Particle Swarm Optimization Algorithm with An Adaptive Escape for A Ring Full Interconnection Structure

JIN Yan-xia; ZHANG Xin; XUE Dan

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A Particle Swarm Optimization Algorithm with An Adaptive Escape for A Ring Full Interconnection Structure

更新时间：2026-09-04

- A Particle Swarm Optimization Algorithm with An Adaptive Escape for A Ring Full Interconnection Structure
- Vol. 35, Issue 2, Pages: 1-5(2018)
- 作者机构：
  
  中北大学机构计算机与控制工程学院,山西,太原,030051
- 作者简介：
- 基金信息：
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- Published：2018
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靳雁霞, 张鑫, 薛丹. 具有自适应逃逸的环状全互连结构粒子群算法[J]. 微电子学与计算机, 2018, 35(2): 1-5, 10.

JIN Yan-xia, ZHANG Xin, XUE Dan. A Particle Swarm Optimization Algorithm with An Adaptive Escape for A Ring Full Interconnection Structure[J]. 2018, 35(2): 1-5.
靳雁霞, 张鑫, 薛丹. 具有自适应逃逸的环状全互连结构粒子群算法[J]. 微电子学与计算机, 2018, 35(2): 1-5, 10. DOI：

JIN Yan-xia, ZHANG Xin, XUE Dan. A Particle Swarm Optimization Algorithm with An Adaptive Escape for A Ring Full Interconnection Structure[J]. 2018, 35(2): 1-5. DOI：

摘要

为了提升粒子群算法在解空间中的寻优性能

提出了一种具有自适应逃逸机制的基于环状全互连拓扑结构的粒子群算法(RSEPSO).该算法首先将种群中的粒子组成环状结构后再连接成全互连结构

其次加入自适应逃逸功能

为防止算法进化时陷入局部极值

同时选取适应值差的粒子进行重新分布

并融入优质粒子环作为学习对象

最后产生足够多的点进行重新搜索

获得全局最优值.通过4个标准测试函数优化

与其他优化算法比较

可以看出RSEPSO能够明显的提升粒子群算法的寻优性能.

Abstract

In order to improve particle swarm optimization algorithm in the solution space to find excellent performance

put forward a with adaptive escape mechanism based on ring interconnection topology of particle swarm optimization algorithm (RSEPSO). In the algorithm

the particle population composition ring structure is connected with perfect interconnection structure. At the same time in order to prevent the algorithm into local extremum

join in adaptive algorithm escape function

selection of poor fitness particles were redistributed

and into high quality particles in the ring as the object of learning. Generate enough points to re search

to obtain the global optimal value. Through 6 standard test function optimization

compared with other algorithms

the RSEPSO can obviously improve the performance of particle swarm optimization algorithm.

关键词

Keywords

references

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冯昌利, 高雷阜. 一种结合混沌和逃逸的自适应粒子群优化方法[J]. 计算机工程与应用, 2011, 47(26): 35-38. DOI: 35

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吕莉, 赵嘉, 孙辉. 具有反向学习和自适应逃逸功能的粒子群优化算法[J]. 计算机应用, 2015, 34(5): 1336-1341. DOI: 1336

Kaveh A, Zolghadr A. Democratic PSO for truss layout and size optimization with frequency constraints[J]. Computers % Structures, 2014, 130(1): 10-21. DOI: 10

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Related Institution

College of Computer Science and Engineering, Shandong University of Science and Technology

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North University of China, School of Computer Science and Control Engineering,, Taiyuan

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