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1. Identity statement
Reference TypeJournal Article
Sitemtc-m16b.sid.inpe.br
Holder Codeisadg {BR SPINPE} ibi 8JMKD3MGPCW/3DT298S
Identifier6qtX3pFwXQZGivnK2Y/Sdm9p
Repositorysid.inpe.br/mtc-m17@80/2007/11.20.12.03   (restricted access)
Last Update2007:11.26.12.05.48 (UTC) marciana
Metadata Repositorysid.inpe.br/mtc-m17@80/2007/11.20.12.03.50
Metadata Last Update2018:06.05.03.57.40 (UTC) administrator
Secondary KeyINPE-14976-PRE/9888
DOI10.1016/S0305-0548(96)00032-9
ISSN0305-0548
Citation KeyLorenaNarcBeas:1999:CoGeAl
TitleA Constructive Genetic Algorithm for the generalized assignment problem
Year1999
MonthNov.
Access Date2024, Apr. 28
Secondary TypePRE PI
Number of Files1
Size69 KiB
2. Context
Author1 Lorena, Luiz Antonio Nogueira
2 Narciso, Marcelo G.
3 Beasley, J. E.
Resume Identifier1 8JMKD3MGP5W/3C9JHMQ
Group1 LAC-INPE-MCT-BR
Affiliation1 Instituto Nacional de Pesquisas Espaciais (INPE)
2 Embrapa Informática Agropecuária, Campinas
3 The Management School, Imperial College, England
Author e-Mail Address1 lorena@lac.inpe.br
2 narciso@cnptia.embrapa.br
3 j.beasley@ic.ac.uk
JournalComputers and Operations Research
Volume24
Number1
Pages17-23
History (UTC)2007-11-26 12:05:48 :: adriana -> administrator ::
2008-06-29 02:31:13 :: administrator -> adriana ::
2010-05-14 02:07:31 :: adriana -> administrator ::
2012-10-16 01:22:49 :: administrator -> marciana :: 1999
2013-03-04 13:02:33 :: marciana -> administrator :: 1999
2018-06-05 03:57:40 :: administrator -> marciana :: 1999
3. Content and structure
Is the master or a copy?is the master
Content Stagecompleted
Transferable1
Content TypeExternal Contribution
Version Typepublisher
AbstractWe present in this paper an application of the Constructive Genetic Algorithm (CGA) to the Generalized Assignment Problem (GAP). The CGA presents some new features compared to a traditional genetic algorithm (GA), such as a population formed only by schemata, recombination among schemata, dynamic population, mutation in complete structures, and the possibility of using heuristics in schemata and/or structure representation. The GAP can be described as a problem of assigning n items to m knapsacks, n>m, such that each item is assigned to exactly one knapsack, subject to capacity constraints on the knapsacks. In our application of CGA to GAP, we regard the GAP as a clustering problem. A binary representation is used for schemata and structures, and an assignment heuristic allocates items to knapsacks. Schemata do not consider all the problem data. The schemata are recombined, and they can produce new schemata or structures. New schemata are evaluated and can be added to the population if they pass an evolution test. Structures can result from recombination of schemata or complementing of good schemata. They suffer mutation and the best structure generated is kept in the process. Computational tests have been performed using instances of large scale available in the literature.
AreaCOMP
Arrangementurlib.net > BDMCI > Fonds > Produção anterior à 2021 > LABAC > A Constructive Genetic...
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4. Conditions of access and use
Languageen
Target Filelorena, a constructive genetic....pdf
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Visibilityshown
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Archiving Policydenypublisher denyfinaldraft36
Read Permissiondeny from all and allow from 150.163
Update Permissionnot transferred
5. Allied materials
Next Higher Units8JMKD3MGPCW/3ESGTTP
DisseminationWEBSCI; PORTALCAPES.
Host Collectionlcp.inpe.br/ignes/2004/02.12.18.39
cptec.inpe.br/walmeida/2003/04.25.17.12
6. Notes
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