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1. Identity statement
Reference TypeJournal Article
Sitemtc-m16.sid.inpe.br
Holder Codeisadg {BR SPINPE} ibi 8JMKD3MGPCW/3DT298S
Identifier6qtX3pFwXQZsFDuKxG/D7bfb
Repositorysid.inpe.br/marciana/2004/08.09.14.48   (restricted access)
Last Update2004:08.12.03.00.00 (UTC) administrator
Metadata Repositorysid.inpe.br/marciana/2004/08.09.14.48.28
Metadata Last Update2018:06.05.01.21.01 (UTC) administrator
Secondary KeyINPE-11207-PRE/6656
ISBN/ISSN0302-9743
ISSN0302-9743
Citation KeyOliveiraLore:2002:2oPoTr
Title2-opt population training for minimization of open stack problem
ProjectAlgoritmos genéticos
Year2002
Access Date2024, Apr. 27
Secondary TypePRE PI
Number of Files1
Size52 KiB
2. Context
Author1 Oliveira, Alexandre César Muniz de
2 Lorena, Luiz Antonio Nogueira
Resume Identifier1
2 8JMKD3MGP5W/3C9JHMQ
Group1
2 LAC-INPE-MCT-BR
Affiliation1 Universidade Federal do Maranhão (UFMA.DEINF)
2 Instituto Nacional de Pesquisas Espaciais, Laboratório Associado de Computação e Matemática Aplicada (INPE. LAC)
JournalLecture Notes in Artificial Intelligence
Volume2507
Pages313-323
History (UTC)2005-06-13 12:02:49 :: sergio -> administrator ::
2007-04-03 01:17:35 :: administrator -> sergio ::
2008-01-07 12:53:23 :: sergio -> administrator ::
2012-11-24 02:10:01 :: administrator -> marciana :: 2002
2013-02-07 15:03:00 :: marciana -> administrator :: 2002
2013-02-13 22:49:57 :: administrator -> banon :: 2002
2013-02-19 11:52:09 :: banon -> marciana :: 2002
2013-03-21 11:59:33 :: marciana -> administrator :: 2002
2018-06-05 01:21:01 :: administrator -> marciana :: 2002
3. Content and structure
Is the master or a copy?is the master
Content Stagecompleted
Transferable1
Content TypeExternal Contribution
Version Typepublisher
KeywordsCOMPUTER SCIENCE
Genetic algorithms
Minimization Open Stack Problem
COMPUTAÇÃO APLICADA
Algoritmos genéticos
Problema de Minimização de Pilhas Abertas
AbstractThis paper describes an application of a Constructive Genetic Algorithm (CGA) to the Minimization Open Stack Problem (MOSP). The MOSP happens in a production system scenario, and consists of determining a sequence of cut patterns that minimizes the maximum number of opened stacks during the cutting process. The CGA has a number of new features compared to a traditional genetic algorithm, as a population of dynamic size composed of schemata and structures that is trained with respect to some problem specific heuristic. The application of CGA to MOSP uses a 2-Opt like heuristic to define the fitness functions and the mutation operator. Computational tests are presented using available instances taken from the literature.
AreaCOMP
Arrangementurlib.net > BDMCI > Fonds > Produção anterior à 2021 > LABAC > 2-opt population training...
doc Directory Contentaccess
source Directory Contentthere are no files
agreement Directory Contentthere are no files
4. Conditions of access and use
Languageen
Target File2-opt.pdf
User Groupadministrator
banon
marciana
sergio
Visibilityshown
Copy HolderSID/SCD
Archiving Policydenypublisher denyfinaldraft12
Read Permissiondeny from all and allow from 150.163
Update Permissionnot transferred
5. Allied materials
Next Higher Units8JMKD3MGPCW/3ESGTTP
DisseminationWEBSCI; PORTALCAPES.
Host Collectionsid.inpe.br/banon/2003/08.15.17.40
6. Notes
Notes16th Brazilian Symposium on Artificial Intelligence (SBIA 2002) Location: PORTO DE GALINHAS RECIFE, BRAZIL Date: NOV 11-14, 2002
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7. Description control
e-Mail (login)marciana
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