Close

1. Identity statement
Reference TypeJournal Article
Sitemtc-m16.sid.inpe.br
Holder Codeisadg {BR SPINPE} ibi 8JMKD3MGPCW/3DT298S
Identifier6qtX3pFwXQZGivnJVY/Lixvy
Repositorysid.inpe.br/mtc-m16@80/2006/05.30.12.55   (restricted access)
Last Update2006:05.30.12.55.10 (UTC) administrator
Metadata Repositorysid.inpe.br/mtc-m16@80/2006/05.30.12.55.12
Metadata Last Update2018:06.05.01.28.59 (UTC) administrator
Secondary KeyINPE-13765-PRE/8954
ISSN0377-2217
Citation KeyLorenaLope:1994:SuHeSe
TitleA surrogate heuristic for set covering problems
ProjectOtmização combinatório, algorítmos e heurísticas
Year1994
Access Date2024, Apr. 28
Secondary TypePRE PI
Number of Files1
Size361 KiB
2. Context
Author1 Lorena, Luiz Antonio Nogueira
2 Lopes, Fabio Belo
Resume Identifier1 8JMKD3MGP5W/3C9JHMQ
Group1 LAC-INPE-MCT-BR
2 LAC-INPE-MCT-BR
Affiliation1 Instituto Nacional de Pesquisas Espaciais (INPE)
2 Instituto Nacional de Pesquisas Espaciais (INPE)
JournalEuropean Journal of Operational Research
Volume79
Pages138-150
History (UTC)2006-05-30 12:55:12 :: vinicius -> administrator ::
2009-08-12 00:26:15 :: administrator -> vinicius ::
2010-01-29 17:00:12 :: vinicius -> administrator ::
2018-06-05 01:28:59 :: administrator -> marciana :: 1994
3. Content and structure
Is the master or a copy?is the master
Content Stagecompleted
Transferable1
Content TypeExternal Contribution
Keywordsset covering
optimization
surrogate relaxation
heuristics
AbstractThe purpose of this paper is to present a new heuristic for set covering problems, based upon continuous surrogate relaxations and subgradient optimization. The algorithm combines problem reduction tests, an adequate step size control, and avoid preliminary sorting in solving the continuous surrogate relaxations. Computational tests for large scale set covering problems (up to 1000 rows and 12000 columns) indicate better-quality results than algorithms based on lagrangian relaxations in terms of final solutions and mainly in computer times. Although the solving of a single surrogate optimization problem is slower than a corresponding lagrangian optimization, the overall performance is almost twice as fast. This is due to the smaller number of iterations which is a result of faster convergence and less oscillation.
AreaCOMP
Arrangementurlib.net > BDMCI > Fonds > Produção anterior à 2021 > LABAC > A surrogate heuristic...
doc Directory Contentaccess
source Directory Contentthere are no files
agreement Directory Contentthere are no files
4. Conditions of access and use
Languageen
Target Filelorena-surrogate.pdf
User Groupadministrator
vinicius
Visibilityshown
Copy HolderSID/SCD
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/banon/2003/08.15.17.40
6. Notes
Empty Fieldsalternatejournal archivist callnumber copyright creatorhistory descriptionlevel documentstage doi e-mailaddress electronicmailaddress format isbn label lineage mark mirrorrepository month nextedition notes number orcid parameterlist parentrepositories previousedition previouslowerunit progress readergroup rightsholder schedulinginformation secondarydate secondarymark session shorttitle sponsor subject tertiarymark tertiarytype typeofwork url versiontype
7. Description control
e-Mail (login)marciana
update 


Close