Local Optimum Embranchment Based Convergence Guarantee Particle Swarm Optimization and Its Application in Transmission Network Planning

This paper summarizes some improved methods of particle swarm optimization (PSO), analyses its critical reasons in convergence dilemma, and then puts forward local optimum embranchment optimization method and local depth optimization method according to the characters of transmission network expansi...

Full description

Saved in:
Bibliographic Details
Main Authors: Yi-Xiong Jin, Hao-Zhong Cheng, Jian-Yong Yan, Li Zhang
Format: Conference Proceeding
Language:English
Subjects:
constructive heuristic algorithm
Convergence of numerical methods
embranchment optimization
Gaussian processes
Genetic mutations
global optimum
Heuristic algorithms
local optimum
Numerical simulation
Optimization methods
Particle swarm optimization
Power grids
Power supplies
power transmission network planning
Shape
Online Access:Request full text
Tags: Add Tag
No Tags, Be the first to tag this record!
cited_by
cites
container_end_page 6
container_issue
container_start_page 1
container_title
container_volume
creator Yi-Xiong Jin
Hao-Zhong Cheng
Jian-Yong Yan
Li Zhang
description This paper summarizes some improved methods of particle swarm optimization (PSO), analyses its critical reasons in convergence dilemma, and then puts forward local optimum embranchment optimization method and local depth optimization method according to the characters of transmission network expansion planning. Numerical simulation results demonstrate these two methods can not only overcome the convergence dilemma, but also improve the search efficiency and guarantee its local and global search ability simultaneously. These methods also shed new light on other optimization methods
doi_str_mv 10.1109/TDC.2005.1546847
format conference_proceeding
fullrecord <record><control><sourceid>ieee_6IE</sourceid><recordid>TN_cdi_ieee_primary_1546847</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><ieee_id>1546847</ieee_id><sourcerecordid>1546847</sourcerecordid><originalsourceid>FETCH-LOGICAL-i90t-8a5c8becc7541a53d8b6e61311b29ab6b5244a8ed56307ab6bd7ce0725b967733</originalsourceid><addsrcrecordid>eNo9kM1OwkAcxDd-JCJyN_GyL1Dc7X72iBWRhAiJvZPt9i-uttumu0j0BXxtIRBPk5lfZg6D0C0lY0pJdl885uOUEDGmgkvN1RkapFSSREvOz9E1UZqwjFLOL_4Bk1doFMIHIYRKnTIlBuh30VpT42UXXbNt8LQpe-PtewM-4gcToMJ567-g34C3gGdbs8cRAK9MH52tAb_uTN8c--7HRNd6bHyF5zHgSdfVzh4z53Gxr4bGhXDwLxB3bf-JV7Xx3vnNDbp8M3WA0UmHqHiaFvlzsljO5vlkkbiMxEQbYXUJ1irBqRGs0qUESRmlZZqZUpYi5dxoqIRkRB2CSlkgKhVlJpVibIjujrMOANZd7xrTf69PF7I_tYNlmA</addsrcrecordid><sourcetype>Publisher</sourcetype><iscdi>true</iscdi><recordtype>conference_proceeding</recordtype></control><display><type>conference_proceeding</type><title>Local Optimum Embranchment Based Convergence Guarantee Particle Swarm Optimization and Its Application in Transmission Network Planning</title><source>IEEE Electronic Library (IEL) Conference Proceedings</source><creator>Yi-Xiong Jin ; Hao-Zhong Cheng ; Jian-Yong Yan ; Li Zhang</creator><creatorcontrib>Yi-Xiong Jin ; Hao-Zhong Cheng ; Jian-Yong Yan ; Li Zhang</creatorcontrib><description>This paper summarizes some improved methods of particle swarm optimization (PSO), analyses its critical reasons in convergence dilemma, and then puts forward local optimum embranchment optimization method and local depth optimization method according to the characters of transmission network expansion planning. Numerical simulation results demonstrate these two methods can not only overcome the convergence dilemma, but also improve the search efficiency and guarantee its local and global search ability simultaneously. These methods also shed new light on other optimization methods</description><identifier>ISSN: 2160-8636</identifier><identifier>ISBN: 0780391144</identifier><identifier>ISBN: 9780780391147</identifier><identifier>EISSN: 2160-8644</identifier><identifier>DOI: 10.1109/TDC.2005.1546847</identifier><language>eng</language><publisher>IEEE</publisher><subject>constructive heuristic algorithm ; Convergence of numerical methods ; embranchment optimization ; Gaussian processes ; Genetic mutations ; global optimum ; Heuristic algorithms ; local optimum ; Numerical simulation ; Optimization methods ; Particle swarm optimization ; Power grids ; Power supplies ; power transmission network planning ; Shape</subject><ispartof>2005 IEEE/PES Transmission &amp; Distribution Conference &amp; Exposition: Asia and Pacific, 2005, p.1-6</ispartof><woscitedreferencessubscribed>false</woscitedreferencessubscribed></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://ieeexplore.ieee.org/document/1546847$$EHTML$$P50$$Gieee$$H</linktohtml><link.rule.ids>309,310,776,780,785,786,2052,4036,4037,27901,54529,54894,54906</link.rule.ids><linktorsrc>$$Uhttps://ieeexplore.ieee.org/document/1546847$$EView_record_in_IEEE$$FView_record_in_$$GIEEE</linktorsrc></links><search><creatorcontrib>Yi-Xiong Jin</creatorcontrib><creatorcontrib>Hao-Zhong Cheng</creatorcontrib><creatorcontrib>Jian-Yong Yan</creatorcontrib><creatorcontrib>Li Zhang</creatorcontrib><title>Local Optimum Embranchment Based Convergence Guarantee Particle Swarm Optimization and Its Application in Transmission Network Planning</title><title>2005 IEEE/PES Transmission &amp; Distribution Conference &amp; Exposition: Asia and Pacific</title><addtitle>TDC</addtitle><description>This paper summarizes some improved methods of particle swarm optimization (PSO), analyses its critical reasons in convergence dilemma, and then puts forward local optimum embranchment optimization method and local depth optimization method according to the characters of transmission network expansion planning. Numerical simulation results demonstrate these two methods can not only overcome the convergence dilemma, but also improve the search efficiency and guarantee its local and global search ability simultaneously. These methods also shed new light on other optimization methods</description><subject>constructive heuristic algorithm</subject><subject>Convergence of numerical methods</subject><subject>embranchment optimization</subject><subject>Gaussian processes</subject><subject>Genetic mutations</subject><subject>global optimum</subject><subject>Heuristic algorithms</subject><subject>local optimum</subject><subject>Numerical simulation</subject><subject>Optimization methods</subject><subject>Particle swarm optimization</subject><subject>Power grids</subject><subject>Power supplies</subject><subject>power transmission network planning</subject><subject>Shape</subject><issn>2160-8636</issn><issn>2160-8644</issn><isbn>0780391144</isbn><isbn>9780780391147</isbn><fulltext>true</fulltext><rsrctype>conference_proceeding</rsrctype><creationdate>2005</creationdate><recordtype>conference_proceeding</recordtype><sourceid>6IE</sourceid><recordid>eNo9kM1OwkAcxDd-JCJyN_GyL1Dc7X72iBWRhAiJvZPt9i-uttumu0j0BXxtIRBPk5lfZg6D0C0lY0pJdl885uOUEDGmgkvN1RkapFSSREvOz9E1UZqwjFLOL_4Bk1doFMIHIYRKnTIlBuh30VpT42UXXbNt8LQpe-PtewM-4gcToMJ567-g34C3gGdbs8cRAK9MH52tAb_uTN8c--7HRNd6bHyF5zHgSdfVzh4z53Gxr4bGhXDwLxB3bf-JV7Xx3vnNDbp8M3WA0UmHqHiaFvlzsljO5vlkkbiMxEQbYXUJ1irBqRGs0qUESRmlZZqZUpYi5dxoqIRkRB2CSlkgKhVlJpVibIjujrMOANZd7xrTf69PF7I_tYNlmA</recordid><startdate>2005</startdate><enddate>2005</enddate><creator>Yi-Xiong Jin</creator><creator>Hao-Zhong Cheng</creator><creator>Jian-Yong Yan</creator><creator>Li Zhang</creator><general>IEEE</general><scope>6IE</scope><scope>6IH</scope><scope>CBEJK</scope><scope>RIE</scope><scope>RIO</scope></search><sort><creationdate>2005</creationdate><title>Local Optimum Embranchment Based Convergence Guarantee Particle Swarm Optimization and Its Application in Transmission Network Planning</title><author>Yi-Xiong Jin ; Hao-Zhong Cheng ; Jian-Yong Yan ; Li Zhang</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-i90t-8a5c8becc7541a53d8b6e61311b29ab6b5244a8ed56307ab6bd7ce0725b967733</frbrgroupid><rsrctype>conference_proceedings</rsrctype><prefilter>conference_proceedings</prefilter><language>eng</language><creationdate>2005</creationdate><topic>constructive heuristic algorithm</topic><topic>Convergence of numerical methods</topic><topic>embranchment optimization</topic><topic>Gaussian processes</topic><topic>Genetic mutations</topic><topic>global optimum</topic><topic>Heuristic algorithms</topic><topic>local optimum</topic><topic>Numerical simulation</topic><topic>Optimization methods</topic><topic>Particle swarm optimization</topic><topic>Power grids</topic><topic>Power supplies</topic><topic>power transmission network planning</topic><topic>Shape</topic><toplevel>online_resources</toplevel><creatorcontrib>Yi-Xiong Jin</creatorcontrib><creatorcontrib>Hao-Zhong Cheng</creatorcontrib><creatorcontrib>Jian-Yong Yan</creatorcontrib><creatorcontrib>Li Zhang</creatorcontrib><collection>IEEE Electronic Library (IEL) Conference Proceedings</collection><collection>IEEE Proceedings Order Plan (POP) 1998-present by volume</collection><collection>IEEE Xplore All Conference Proceedings</collection><collection>IEEE/IET Electronic Library</collection><collection>IEEE Proceedings Order Plans (POP) 1998-present</collection></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext_linktorsrc</fulltext></delivery><addata><au>Yi-Xiong Jin</au><au>Hao-Zhong Cheng</au><au>Jian-Yong Yan</au><au>Li Zhang</au><format>book</format><genre>proceeding</genre><ristype>CONF</ristype><atitle>Local Optimum Embranchment Based Convergence Guarantee Particle Swarm Optimization and Its Application in Transmission Network Planning</atitle><btitle>2005 IEEE/PES Transmission &amp; Distribution Conference &amp; Exposition: Asia and Pacific</btitle><stitle>TDC</stitle><date>2005</date><risdate>2005</risdate><spage>1</spage><epage>6</epage><pages>1-6</pages><issn>2160-8636</issn><eissn>2160-8644</eissn><isbn>0780391144</isbn><isbn>9780780391147</isbn><abstract>This paper summarizes some improved methods of particle swarm optimization (PSO), analyses its critical reasons in convergence dilemma, and then puts forward local optimum embranchment optimization method and local depth optimization method according to the characters of transmission network expansion planning. Numerical simulation results demonstrate these two methods can not only overcome the convergence dilemma, but also improve the search efficiency and guarantee its local and global search ability simultaneously. These methods also shed new light on other optimization methods</abstract><pub>IEEE</pub><doi>10.1109/TDC.2005.1546847</doi><tpages>6</tpages></addata></record>
fulltext fulltext_linktorsrc
identifier ISSN: 2160-8636
ispartof 2005 IEEE/PES Transmission & Distribution Conference & Exposition: Asia and Pacific, 2005, p.1-6
issn 2160-8636
2160-8644
language eng
recordid cdi_ieee_primary_1546847
source IEEE Electronic Library (IEL) Conference Proceedings
subjects constructive heuristic algorithm
Convergence of numerical methods
embranchment optimization
Gaussian processes
Genetic mutations
global optimum
Heuristic algorithms
local optimum
Numerical simulation
Optimization methods
Particle swarm optimization
Power grids
Power supplies
power transmission network planning
Shape
title Local Optimum Embranchment Based Convergence Guarantee Particle Swarm Optimization and Its Application in Transmission Network Planning
url http://sfxeu10.hosted.exlibrisgroup.com/loughborough?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-02-25T06%3A06%3A17IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-ieee_6IE&rft_val_fmt=info:ofi/fmt:kev:mtx:book&rft.genre=proceeding&rft.atitle=Local%20Optimum%20Embranchment%20Based%20Convergence%20Guarantee%20Particle%20Swarm%20Optimization%20and%20Its%20Application%20in%20Transmission%20Network%20Planning&rft.btitle=2005%20IEEE/PES%20Transmission%20&%20Distribution%20Conference%20&%20Exposition:%20Asia%20and%20Pacific&rft.au=Yi-Xiong%20Jin&rft.date=2005&rft.spage=1&rft.epage=6&rft.pages=1-6&rft.issn=2160-8636&rft.eissn=2160-8644&rft.isbn=0780391144&rft.isbn_list=9780780391147&rft_id=info:doi/10.1109/TDC.2005.1546847&rft_dat=%3Cieee_6IE%3E1546847%3C/ieee_6IE%3E%3Cgrp_id%3Ecdi_FETCH-LOGICAL-i90t-8a5c8becc7541a53d8b6e61311b29ab6b5244a8ed56307ab6bd7ce0725b967733%3C/grp_id%3E%3Coa%3E%3C/oa%3E%3Curl%3E%3C/url%3E&rft_id=info:oai/&rft_id=info:pmid/&rft_ieee_id=1546847&rfr_iscdi=true