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dc.contributor.authorMirjalili, S
dc.contributor.authorHashim, SZM
dc.contributor.editorSong Guozhi
dc.date.accessioned2017-05-03T16:08:55Z
dc.date.available2017-05-03T16:08:55Z
dc.date.issued2010
dc.date.modified2013-10-10T22:03:40Z
dc.identifier.isbn9781424485963
dc.identifier.doi10.1109/ICCIA.2010.6141614
dc.identifier.urihttp://hdl.handle.net/10072/48830
dc.description.abstractIn this paper, a new hybrid population-based algorithm (PSOGSA) is proposed with the combination of Particle Swarm Optimization (PSO) and Gravitational Search Algorithm (GSA). The main idea is to integrate the ability of exploitation in PSO with the ability of exploration in GSA to synthesize both algorithms' strength. Some benchmark test functions are used to compare the hybrid algorithm with both the standard PSO and GSA algorithms in evolving best solution. The results show the hybrid algorithm possesses a better capability to escape from local optimums with faster convergence than the standard PSO and GSA.
dc.description.peerreviewedYes
dc.description.publicationstatusYes
dc.format.extent187422 bytes
dc.format.mimetypeapplication/pdf
dc.languageEnglish
dc.language.isoeng
dc.publisherIEEE
dc.publisher.placeUnited States
dc.relation.ispartofstudentpublicationN
dc.relation.ispartofconferencenameICCIA 2010
dc.relation.ispartofconferencetitleProceedings of ICCIA 2010 - 2010 International Conference on Computer and Information Application
dc.relation.ispartofdatefrom2010-12-03
dc.relation.ispartofdateto2010-12-05
dc.relation.ispartoflocationTianjin, China
dc.relation.ispartofpagefrom374
dc.relation.ispartofpageto377
dc.rights.retentionY
dc.subject.fieldofresearchNeural, Evolutionary and Fuzzy Computation
dc.subject.fieldofresearchcode080108
dc.titleA new hybrid PSOGSA algorithm for function optimization
dc.typeConference output
dc.type.descriptionE1 - Conferences
dc.type.codeE - Conference Publications
gro.rights.copyright© 2010 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.
gro.date.issued2010
gro.hasfulltextFull Text
gro.griffith.authorMirjalili, Seyedali


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    Contains papers delivered by Griffith authors at national and international conferences.

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