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1. Identity statement
Reference TypeJournal Article
Sitemtc-m16c.sid.inpe.br
Holder Codeisadg {BR SPINPE} ibi 8JMKD3MGPCW/3DT298S
Identifier8JMKD3MGP8W/346K3EB
Repositorysid.inpe.br/mtc-m18@80/2008/11.04.17.09   (restricted access)
Last Update2008:11.04.17.09.07 (UTC) administrator
Metadata Repositorysid.inpe.br/mtc-m18@80/2008/11.04.17.09.09
Metadata Last Update2018:06.04.04.05.43 (UTC) administrator
Secondary KeyINPE--PRE/
DOI10.1016/j.cie.2007.11.018
ISSN0360-8352
Citation KeyNaganoRuizLore:2008:CoGeAl
TitleA Constructive Genetic Algorithm for permutation flowshop scheduling
Year2008
MonthAug.
Access Date2024, Apr. 28
Secondary TypePRE PI
Number of Files1
Size325 KiB
2. Context
Author1 Nagano, Marcelo Seido
2 Ruiz, Rubem
3 Lorena, Luiz Antonio Nogueira
Resume Identifier1
2
3 8JMKD3MGP5W/3C9JHMQ
Group1
2
3 LAC-CTE-INPE-MCT-BR
Affiliation1 Universidade de São Paulo (USP)
2 Univ Politecn Valencia
3 Instituto Nacional de Pesquisas Espaciais (INPE)
JournalComputers and Industrial Engineering
Volume55
Number1
Pages195-207
History (UTC)2008-11-19 17:38:00 :: simone -> administrator ::
2018-06-04 04:05:43 :: administrator -> marciana :: 2008
3. Content and structure
Is the master or a copy?is the master
Content Stagecompleted
Transferable1
Content TypeExternal Contribution
Keywordsflowshop
Constructive Genetic Algorithm
makespan
AbstractThe general flowshop scheduling problem is a production problem where a set of n jobs have to be processed with identical flow pattern on in machines. In permutation flowshops the sequence of jobs is the same on all machines. A significant research effort has been devoted for sequencing jobs in a flowshop minimizing the makespan. This paper describes the application of a Constructive Genetic Algorithm (CGA) to makespan minimization on flowshop scheduling. The CGA was proposed recently as an alternative to traditional GA approaches, particularly, for evaluating schemata directly. The population initially formed only by schemata, evolves controlled by recombination to a population of well-adapted structures (schemata instantiation). The CGA implemented is based on the NEH classic heuristic and a local search heuristic used to define the fitness functions. The parameters of the CGA are calibrated using a Design of Experiments (DOE) approach. The computational results are compared against some other successful algorithms from the literature on Taillard's well-known standard benchmark. The computational experience shows that this innovative CGA approach provides competitive results for flowshop scheduling; problems.
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 Filea constructive.pdf
User Groupadministrator
simone
Visibilityshown
Archiving Policydenypublisher denyfinaldraft36
Read Permissiondeny from all and allow from 150.163
5. Allied materials
Next Higher Units8JMKD3MGPCW/3ESGTTP
DisseminationWEBSCI; PORTALCAPES.
Host Collectionsid.inpe.br/mtc-m18@80/2008/03.17.15.17
6. Notes
Empty Fieldsalternatejournal archivist callnumber copyholder copyright creatorhistory descriptionlevel documentstage e-mailaddress electronicmailaddress format isbn label lineage mark mirrorrepository nextedition notes orcid parameterlist parentrepositories previousedition previouslowerunit progress project readergroup rightsholder schedulinginformation secondarydate secondarymark session shorttitle sponsor subject tertiarymark tertiarytype typeofwork url versiontype
7. Description control
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