Gbest-guided Imperialist Competitive Algorithm for Global Numerical Optimization
Imperialist competitive(IC) optimization algorithm invented recently by Atashpaz Gargari is a heuristics algorithm. However, there is still an insufficiency in IC algorithm regarding its solution search equation, which is good at exploration but poor at exploitation. Inspired by Particle swarm optim...
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| creator | Yang Shi-da Yi Ya-lin Shan Zhi-yong |
| description | Imperialist competitive(IC) optimization algorithm invented recently by Atashpaz Gargari is a heuristics algorithm. However, there is still an insufficiency in IC algorithm regarding its solution search equation, which is good at exploration but poor at exploitation. Inspired by Particle swarm optimization, we propose an improved IC algorithm called gbest-guided IC (GIC) algorithm by incorporating the information of global best (gbest) solution into the solution search equation to improve the exploitation. The experimental results tested on a set of numerical benchmark functions show that GIC algorithm can outperform IC algorithm in most of the experiments. |
| doi_str_mv | 10.1109/CDCIEM.2012.90 |
| format | Conference Proceeding |
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The experimental results tested on a set of numerical benchmark functions show that GIC algorithm can outperform IC algorithm in most of the experiments.</description><subject>Benchmark testing</subject><subject>Equations</subject><subject>Genetic algorithms</subject><subject>Global optimization</subject><subject>Heuristic algorithms</subject><subject>Imperialist competitive algorithm</subject><subject>Integrated circuits</subject><subject>Optimization</subject><subject>Search problems</subject><isbn>1467304581</isbn><isbn>9781467304580</isbn><isbn>9780769546391</isbn><isbn>0769546390</isbn><fulltext>true</fulltext><rsrctype>conference_proceeding</rsrctype><creationdate>2012</creationdate><recordtype>conference_proceeding</recordtype><sourceid>6IE</sourceid><sourceid>RIE</sourceid><recordid>eNotjE1Pg0AURccYE7WydeOGPwC-N5_MssGKJNW66L4Z4FHHgBCYmuivL4nezT03ObmM3SOkiGAf86e83LymHJCnFi5YZE0GRlsltbB4yW5RaiNAqgyvWTTPn7DEAM-EvGHvRUVzSI4n31ATl_1Ik3edn0OcD8sIPvhvitfdcZh8-Ojjdpjiohsq18Vvp36R64V2Y_C9_3XBD1937Kp13UzRf6_Y_nmzz1-S7a4o8_U28RZComQDAmtoZOWg5srWxMGIStROOG4dKYdtLZzTyIELrqVFRSQVWduisWLFHv5uPREdxsn3bvo5aDSZzDJxBsXHT7s</recordid><startdate>201203</startdate><enddate>201203</enddate><creator>Yang Shi-da</creator><creator>Yi Ya-lin</creator><creator>Shan Zhi-yong</creator><general>IEEE</general><scope>6IE</scope><scope>6IL</scope><scope>CBEJK</scope><scope>RIE</scope><scope>RIL</scope></search><sort><creationdate>201203</creationdate><title>Gbest-guided Imperialist Competitive Algorithm for Global Numerical Optimization</title><author>Yang Shi-da ; Yi Ya-lin ; Shan Zhi-yong</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-i90t-54d031c0d4ba0c259ce2073b3ca3a29ae5a1fc3aa612023264915ee45e99f1793</frbrgroupid><rsrctype>conference_proceedings</rsrctype><prefilter>conference_proceedings</prefilter><language>eng</language><creationdate>2012</creationdate><topic>Benchmark testing</topic><topic>Equations</topic><topic>Genetic algorithms</topic><topic>Global optimization</topic><topic>Heuristic algorithms</topic><topic>Imperialist competitive algorithm</topic><topic>Integrated circuits</topic><topic>Optimization</topic><topic>Search problems</topic><toplevel>online_resources</toplevel><creatorcontrib>Yang Shi-da</creatorcontrib><creatorcontrib>Yi Ya-lin</creatorcontrib><creatorcontrib>Shan Zhi-yong</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>Yang Shi-da</au><au>Yi Ya-lin</au><au>Shan Zhi-yong</au><format>book</format><genre>proceeding</genre><ristype>CONF</ristype><atitle>Gbest-guided Imperialist Competitive Algorithm for Global Numerical Optimization</atitle><btitle>2012 International Conference on Computer Distributed Control and Intelligent Environmental Monitoring</btitle><stitle>cdciem</stitle><date>2012-03</date><risdate>2012</risdate><spage>352</spage><epage>355</epage><pages>352-355</pages><isbn>1467304581</isbn><isbn>9781467304580</isbn><eisbn>9780769546391</eisbn><eisbn>0769546390</eisbn><abstract>Imperialist competitive(IC) optimization algorithm invented recently by Atashpaz Gargari is a heuristics algorithm. However, there is still an insufficiency in IC algorithm regarding its solution search equation, which is good at exploration but poor at exploitation. Inspired by Particle swarm optimization, we propose an improved IC algorithm called gbest-guided IC (GIC) algorithm by incorporating the information of global best (gbest) solution into the solution search equation to improve the exploitation. The experimental results tested on a set of numerical benchmark functions show that GIC algorithm can outperform IC algorithm in most of the experiments.</abstract><pub>IEEE</pub><doi>10.1109/CDCIEM.2012.90</doi><tpages>4</tpages></addata></record> |
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| ispartof | 2012 International Conference on Computer Distributed Control and Intelligent Environmental Monitoring, 2012, p.352-355 |
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| language | eng |
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| source | IEEE Electronic Library (IEL) Conference Proceedings |
| subjects | Benchmark testing Equations Genetic algorithms Global optimization Heuristic algorithms Imperialist competitive algorithm Integrated circuits Optimization Search problems |
| title | Gbest-guided Imperialist Competitive Algorithm for Global Numerical Optimization |
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