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dc.contributor.authorScriven, Ianen_US
dc.contributor.authorLewis, Andrewen_US
dc.contributor.authorMostaghim, Sanazen_US
dc.contributor.editorAndy Tyrrellen_US
dc.date.accessioned2017-04-24T09:52:55Z
dc.date.available2017-04-24T09:52:55Z
dc.date.issued2009en_US
dc.date.modified2010-07-28T06:58:24Z
dc.identifier.refurihttp://www.cec-2009.org/en_AU
dc.identifier.doi10.1109/CEC.2009.4983122en_AU
dc.identifier.urihttp://hdl.handle.net/10072/29236
dc.description.abstractPeer-to-peer based distributed computing environments can be expected to be dynamic to greater of lesser degree. While node losses will not usually lead to catastrophic failure of a population-based optimisation algorithm, such as particle swarm optimisation, performance will be degraded unless the lost computational power is replaced. When resources are replaced, one must consider how to utilise newly available nodes as well as the loss of existing nodes. In order to take advantage of newly available nodes, new particles must be generated to populate them. This paper proposes two methods of generating new particles during algorithm execution and compares the performance of each approach, then investigates a hybridised approach incorporating both mechanisms.en_US
dc.description.peerreviewedYesen_US
dc.description.publicationstatusYesen_AU
dc.format.extent202612 bytes
dc.format.mimetypeapplication/pdf
dc.languageEnglishen_US
dc.language.isoen_AU
dc.publisherIEEEen_US
dc.publisher.placePiscataway, NJ, USAen_US
dc.relation.ispartofstudentpublicationNen_AU
dc.relation.ispartofconferencename(CEC 2009) IEEE Congress on Evolutionary Computation,en_US
dc.relation.ispartofconferencetitleConference Proceedings: IEEE Congress on Evolutionary Computation 2009en_US
dc.relation.ispartofdatefrom2009-05-18en_US
dc.relation.ispartofdateto2009-05-21en_US
dc.relation.ispartoflocationTrondheim, Norwayen_US
dc.rights.retentionYen_AU
dc.subject.fieldofresearchDistributed Computing not elsewhere classifieden_US
dc.subject.fieldofresearchOptimisationen_US
dc.subject.fieldofresearchcode080599en_US
dc.subject.fieldofresearchcode010303en_US
dc.titleDynamic Search Initialisation Strategies for Multi-Objective Optimisation in Peer-to-peer Networksen_US
dc.typeConference outputen_US
dc.type.descriptionE1 - Conference Publications (HERDC)en_US
dc.type.codeE - Conference Publicationsen_US
gro.facultyGriffith Sciences, Griffith School of Engineeringen_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. This paper was first published in the Proceedings of IEEE Congress on Evolutionary Computation, 2009.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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