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1. Identity statement
Reference TypeBook Section
Sitemtc-m16.sid.inpe.br
Holder Codeisadg {BR SPINPE} ibi 8JMKD3MGPCW/3DT298S
Identifier6qtX3pFwXQZsFDuKxG/EtsUA
Repositorysid.inpe.br/marciana/2004/12.15.16.06   (restricted access)
Last Update2015:08.25.15.49.54 (UTC) marciana
Metadata Repositorysid.inpe.br/marciana/2004/12.15.16.06.37
Metadata Last Update2018:06.05.01.21.17 (UTC) administrator
Secondary KeyINPE--/
ISBN8589029042
Citation KeyOliveiraLorePretStep:2004:AdHiFa
TitleAn adaptive hierarchical fair competition genetic algorithm for large-scale numerical optimization
Year2004
Access Date2024, May 08
Secondary TypePRE LI
Number of Files1
Size129 KiB
2. Context
Author1 Oliveira, Alexandre Cesar Muniz de
2 Lorena, Luiz Antonio Nogueira
3 Preto, Airam Jonatas
4 Stephany, Stephan
Group1
2 LAC-INPE-MCT-BR
3 LAC-INPE-MCT-BR
4 LAC-INPE-MCT-BR
Affiliation1 Universidade Federal do Maranhão (UFMA)
2 Instituto Nacional de Pesquisas Espaciais (INPE)
3 Instituto Nacional de Pesquisas Espaciais (INPE)
4 Instituto Nacional de Pesquisas Espaciais (INPE)
Author e-Mail Address1 acmo@deinf.ufma.br
2 lorena@lac.inpe.br
3 airam@lac.inpe.br
4 stephan@lac.inpe.br
EditorBarros, Allan
Araujo, Aluizio
Yehia, Hani C.
Teixeira, Roselito
Book TitleProceedings of SBRN 2004 - 8th Brazilian Symposium on Neural Networks
CityCA, USA
Pagesx
History (UTC)2004-12-15 18:06:38 :: jefferson -> administrator ::
2014-09-29 15:41:22 :: administrator -> marciana :: 2004
2015-08-25 15:49:54 :: marciana -> administrator :: 2004
2018-06-05 01:21:17 :: administrator -> jefferson :: 2004
3. Content and structure
Is the master or a copy?is the master
Content Stagecompleted
Transferable1
Content TypeExternal Contribution
Keywordsgenetic algorithms
AbstractGenetic algorithms, inspired by the theory of evolution of species, are intended to be unfair. Individuals compete against each other and the best-adapted ones prevail. Unfairness is due to big differences of skills, generally evaluated by a fitness measure, in a population of individuals competing for survival. However, population diversity is important to preserve some features that are not always associated to high ranked skills. Such diversity can be achieved by imposing fairness rules to the competition. The adaptive hierarchical fair competition genetic algorithm has been proposed to comply with this feature by segregating individuals in casts or demes, according to their fitness. This work proposes a parallel implementation that enhances the capabilities and computational performance of an adaptive hierarchical fair competition genetic algorithm. The code was parallelized using the MPI (Message Passing Interface) communication library and executed in a distributed memory parallel machine, a PC cluster. Test results are shown for standard numerical optimization problems presenting hundreds of variables.
AreaCOMP
Arrangementurlib.net > BDMCI > Fonds > Produção anterior à 2021 > LABAC > An adaptive hierarchical...
doc Directory Contentaccess
source Directory Contentthere are no files
agreement Directory Contentthere are no files
4. Conditions of access and use
Languageen
Target Fileoliveira_an adaptive.pdf
User Groupadministrator
jefferson
Visibilityshown
Read Permissiondeny from all and allow from 150.163
Update Permissionnot transferred
5. Allied materials
Next Higher Units8JMKD3MGPCW/3ESGTTP
DisseminationNTRSNASA; BNDEPOSITOLEGAL.
Host Collectionsid.inpe.br/banon/2003/08.15.17.40
6. Notes
Empty Fieldsarchivingpolicy archivist callnumber copyholder copyright creatorhistory descriptionlevel doi e-mailaddress edition format issn label lineage mark mirrorrepository nextedition notes numberofvolumes orcid parameterlist parentrepositories previousedition previouslowerunit progress project publisher readergroup resumeid rightsholder schedulinginformation secondarydate secondarymark serieseditor seriestitle session shorttitle sponsor subject tertiarymark tertiarytype translator url versiontype volume
7. Description control
e-Mail (login)jefferson
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