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dc.contributor.authorLewis, Andrewen_US
dc.contributor.editorYuanyuan Yangen_US
dc.date.accessioned2017-05-03T12:49:02Z
dc.date.available2017-05-03T12:49:02Z
dc.date.issued2009en_US
dc.date.modified2011-05-05T07:55:25Z
dc.identifier.refurihttp://www.ipdps.org/ipdps2009/2009_advance_program.htmlen_AU
dc.identifier.doi10.1109/IPDPS.2009.5161125en_AU
dc.identifier.urihttp://hdl.handle.net/10072/25944
dc.description.abstractParticle Swarm Optimisation (PSO) is increasingly being applied to optimisation of multi-objective problems in engineering design and scientific investigation. This paper investigates the behaviour of a novel algorithm based on an extension of the concepts of spatial social networks using a model of the behaviour of locusts and crickets. In particular, observation of locust swarms suggests a specific dependence on population density for ordered behaviour. Computational experiments demonstrate that both the new, spatial, social network algorithm and a conventional MOPSO algorithm exhibit improved performance with increased swarm size and crowding. This observation may have particular significance for design of some forms of distributed PSO algorithms.en_US
dc.description.peerreviewedYesen_US
dc.description.publicationstatusYesen_AU
dc.format.extent1154169 bytes
dc.format.mimetypeapplication/pdf
dc.languageEnglishen_US
dc.language.isoen_AU
dc.publisherIEEE Computer Societyen_US
dc.publisher.placeUnited Statesen_US
dc.publisher.urihttp://ieeexplore.ieee.org/xpl/mostRecentIssue.jsp?punumber=5136864en_AU
dc.relation.ispartofstudentpublicationNen_AU
dc.relation.ispartofconferencename(IPDPS 2009) 23rd IEEE International Symposium on Parallel & Distributed Processingen_US
dc.relation.ispartofconferencetitleConference Proceedings: IEEE International Symposium on Parallel & Distributed Processingen_US
dc.relation.ispartofdatefrom2009-05-25en_US
dc.relation.ispartofdateto2009-05-28en_US
dc.relation.ispartoflocationRome, Italyen_US
dc.rights.retentionYen_AU
dc.subject.fieldofresearchOptimisationen_US
dc.subject.fieldofresearchcode010303en_US
dc.titleThe Effect of Population Density on the Performance of a Spatial Social Network Algorithm for Multi-objective Optimisationen_US
dc.typeConference outputen_US
dc.type.descriptionE1 - Conference Publications (HERDC)en_US
dc.type.codeE - Conference Publicationsen_US
gro.facultyGriffith Sciences, School of Information and Communication Technologyen_US
gro.rights.copyrightCopyright 2009 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.en_AU
gro.date.issued2009
gro.hasfulltextFull Text


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

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