A Study on the Convergence of Family Particle Swarm Optimization
The sociological concept of family has been introduced in the particle swarm optimization (PSO) and the family PSO (FPSO) has been proposed, in which the particle swarm consisted of different families, each family consisted of different members, and there were different constraint relationships betw...
Main Authors: | , , |
---|---|
Format: | Article |
Language: | English |
Published: |
Hindawi Limited
2017-01-01
|
Series: | Mathematical Problems in Engineering |
Online Access: | http://dx.doi.org/10.1155/2017/6129865 |
id |
doaj-a9915cff46904f83bc0a63756b5ba2ec |
---|---|
record_format |
Article |
spelling |
doaj-a9915cff46904f83bc0a63756b5ba2ec2020-11-24T22:57:42ZengHindawi LimitedMathematical Problems in Engineering1024-123X1563-51472017-01-01201710.1155/2017/61298656129865A Study on the Convergence of Family Particle Swarm OptimizationZhenzhou An0Xiaoyan Wang1Xinling Shi2Yuxi Normal University, Yuxi 653100, ChinaYuxi Normal University, Yuxi 653100, ChinaYunnan University, Yunnan 650091, ChinaThe sociological concept of family has been introduced in the particle swarm optimization (PSO) and the family PSO (FPSO) has been proposed, in which the particle swarm consisted of different families, each family consisted of different members, and there were different constraint relationships between family members. To further study the sensitivity of FPSO to the control parameters, this paper proposed a special model of FPSO and analyzed the convergence of FPSO theoretically. This model offered a new view to research the particle trajectory and divided the position sequence of particle into the even and odd subsequences. By mathematical analysis, the condition of two subsequences convergence was obtained and the related convergent theories and corollaries were proved. Simulations for benchmark functions showed that the convergence behavior of model and experimental results provided a valuable guideline for selecting control parameters.http://dx.doi.org/10.1155/2017/6129865 |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Zhenzhou An Xiaoyan Wang Xinling Shi |
spellingShingle |
Zhenzhou An Xiaoyan Wang Xinling Shi A Study on the Convergence of Family Particle Swarm Optimization Mathematical Problems in Engineering |
author_facet |
Zhenzhou An Xiaoyan Wang Xinling Shi |
author_sort |
Zhenzhou An |
title |
A Study on the Convergence of Family Particle Swarm Optimization |
title_short |
A Study on the Convergence of Family Particle Swarm Optimization |
title_full |
A Study on the Convergence of Family Particle Swarm Optimization |
title_fullStr |
A Study on the Convergence of Family Particle Swarm Optimization |
title_full_unstemmed |
A Study on the Convergence of Family Particle Swarm Optimization |
title_sort |
study on the convergence of family particle swarm optimization |
publisher |
Hindawi Limited |
series |
Mathematical Problems in Engineering |
issn |
1024-123X 1563-5147 |
publishDate |
2017-01-01 |
description |
The sociological concept of family has been introduced in the particle swarm optimization (PSO) and the family PSO (FPSO) has been proposed, in which the particle swarm consisted of different families, each family consisted of different members, and there were different constraint relationships between family members. To further study the sensitivity of FPSO to the control parameters, this paper proposed a special model of FPSO and analyzed the convergence of FPSO theoretically. This model offered a new view to research the particle trajectory and divided the position sequence of particle into the even and odd subsequences. By mathematical analysis, the condition of two subsequences convergence was obtained and the related convergent theories and corollaries were proved. Simulations for benchmark functions showed that the convergence behavior of model and experimental results provided a valuable guideline for selecting control parameters. |
url |
http://dx.doi.org/10.1155/2017/6129865 |
work_keys_str_mv |
AT zhenzhouan astudyontheconvergenceoffamilyparticleswarmoptimization AT xiaoyanwang astudyontheconvergenceoffamilyparticleswarmoptimization AT xinlingshi astudyontheconvergenceoffamilyparticleswarmoptimization AT zhenzhouan studyontheconvergenceoffamilyparticleswarmoptimization AT xiaoyanwang studyontheconvergenceoffamilyparticleswarmoptimization AT xinlingshi studyontheconvergenceoffamilyparticleswarmoptimization |
_version_ |
1725649680903176192 |