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Study on improved ant colony algorithm of swarm intelligence algorithm
This article first introduces the basic principle and model of ant colony algorithm which is a kind of swarm intelligence algorithm, then analyzes the defect in large-scale optimization problems of basic ant colony algorithm, and concludes with an improved algorithm to improve execution efficiency a...
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container_end_page | V5-641 |
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container_start_page | V5-639 |
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container_volume | 5 |
creator | Cheng Li Miao Xianglin Wang Changying Hu Zhengping Wang Dezhong |
description | This article first introduces the basic principle and model of ant colony algorithm which is a kind of swarm intelligence algorithm, then analyzes the defect in large-scale optimization problems of basic ant colony algorithm, and concludes with an improved algorithm to improve execution efficiency and solution quality in solving large-scale problems. |
doi_str_mv | 10.1109/ICACTE.2010.5579349 |
format | conference_proceeding |
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Miao Xianglin ; Wang Changying ; Hu Zhengping ; Wang Dezhong</creator><creatorcontrib>Cheng Li ; Miao Xianglin ; Wang Changying ; Hu Zhengping ; Wang Dezhong</creatorcontrib><description>This article first introduces the basic principle and model of ant colony algorithm which is a kind of swarm intelligence algorithm, then analyzes the defect in large-scale optimization problems of basic ant colony algorithm, and concludes with an improved algorithm to improve execution efficiency and solution quality in solving large-scale problems.</description><identifier>ISSN: 2154-7491</identifier><identifier>ISBN: 1424465397</identifier><identifier>ISBN: 9781424465392</identifier><identifier>EISSN: 2154-7505</identifier><identifier>EISBN: 1424465427</identifier><identifier>EISBN: 9781424465415</identifier><identifier>EISBN: 9781424465422</identifier><identifier>EISBN: 1424465419</identifier><identifier>DOI: 10.1109/ICACTE.2010.5579349</identifier><language>eng</language><publisher>IEEE</publisher><subject>Algorithm design and analysis ; 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Miao Xianglin ; Wang Changying ; Hu Zhengping ; Wang Dezhong</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-i90t-118814fea8774f9535663a2591518cea793c4232f20780dfadc2299e447979273</frbrgroupid><rsrctype>conference_proceedings</rsrctype><prefilter>conference_proceedings</prefilter><language>eng</language><creationdate>2010</creationdate><topic>Algorithm design and analysis</topic><topic>ant colony algorithm</topic><topic>Computational modeling</topic><topic>Computers</topic><topic>Robustness</topic><topic>routing strategy</topic><topic>TSP problem</topic><toplevel>online_resources</toplevel><creatorcontrib>Cheng Li</creatorcontrib><creatorcontrib>Miao Xianglin</creatorcontrib><creatorcontrib>Wang Changying</creatorcontrib><creatorcontrib>Hu Zhengping</creatorcontrib><creatorcontrib>Wang Dezhong</creatorcontrib><collection>IEEE Electronic Library (IEL) Conference Proceedings</collection><collection>IEEE Proceedings Order Plan All Online (POP All Online) 1998-present by volume</collection><collection>IEEE Xplore All Conference Proceedings</collection><collection>IEEE Electronic Library (IEL)</collection><collection>IEEE Proceedings Order Plans (POP All) 1998-Present</collection></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext_linktorsrc</fulltext></delivery><addata><au>Cheng Li</au><au>Miao Xianglin</au><au>Wang Changying</au><au>Hu Zhengping</au><au>Wang Dezhong</au><format>book</format><genre>proceeding</genre><ristype>CONF</ristype><atitle>Study on improved ant colony algorithm of swarm intelligence algorithm</atitle><btitle>2010 3rd International Conference on Advanced Computer Theory and Engineering(ICACTE)</btitle><stitle>ICACTE</stitle><date>2010-08</date><risdate>2010</risdate><volume>5</volume><spage>V5-639</spage><epage>V5-641</epage><pages>V5-639-V5-641</pages><issn>2154-7491</issn><eissn>2154-7505</eissn><isbn>1424465397</isbn><isbn>9781424465392</isbn><eisbn>1424465427</eisbn><eisbn>9781424465415</eisbn><eisbn>9781424465422</eisbn><eisbn>1424465419</eisbn><abstract>This article first introduces the basic principle and model of ant colony algorithm which is a kind of swarm intelligence algorithm, then analyzes the defect in large-scale optimization problems of basic ant colony algorithm, and concludes with an improved algorithm to improve execution efficiency and solution quality in solving large-scale problems.</abstract><pub>IEEE</pub><doi>10.1109/ICACTE.2010.5579349</doi></addata></record> |
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source | IEEE Electronic Library (IEL) Conference Proceedings |
subjects | Algorithm design and analysis ant colony algorithm Computational modeling Computers Robustness routing strategy TSP problem |
title | Study on improved ant colony algorithm of swarm intelligence algorithm |
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