Resultado da Pesquisa
A expressão de busca foi <secondaryty ci and ref conference and firstg DIDOP-CGCPT-INPE-MCTIC-GOV-BR and y 2017 and is * and not booktitle, Resumos and not booktitle, Abstracts>.
1 referência encontrada buscando em 17 dentre 17 Arquivos.
Data e hora local de busca: 20/04/2024 07:22.
1. Identificação
Tipo de ReferênciaArtigo em Evento (Conference Proceedings)
Siteplutao.sid.inpe.br
Código do Detentorisadg {BR SPINPE} ibi 8JMKD3MGPCW/3DT298S
Identificador8JMKD3MGP3W/3P5TDPL
Repositóriosid.inpe.br/plutao/2017/06.21.20.42.18
Última Atualização2017:06.23.12.15.17 (UTC) administrator
Repositório de Metadadossid.inpe.br/plutao/2017/06.21.20.42.19
Última Atualização dos Metadados2021:02.02.03.55.10 (UTC) administrator
DOI10.5220/0006106402030210
ISBN978-989-758-218-9
Rótulolattes: 8920905542032636 1 BarbosaSenn:2017:HeOpMe
Chave de CitaçãoBarbosaSenn:2017:HeOpMe
TítuloA heuristic for optimization of metaheuristics by means of statistical methods
Ano2017
Data de Acesso20 abr. 2024
Tipo SecundárioPRE CI
Número de Arquivos1
Tamanho540 KiB
2. Contextualização
Autor1 Barbosa, Eduardo Batista de Moraes
2 Senne, Edson Luiz França
Grupo1 DIDOP-CGCPT-INPE-MCTIC-GOV-BR
2 SESTS-CGETE-INPE-MCTIC-GOV-BR
Afiliação1 Instituto Nacional de Pesquisas Espaciais (INPE)
2 Instituto Nacional de Pesquisas Espaciais (INPE)
Endereço de e-Mail do Autor1 eduardo.barbosa@inpe.br
2 edson.miranda@inpe.br
Nome do EventoInternational Conference on Operations Research and Enterprise Systems, 6 (ICORES)
Localização do EventoPorto, Portugal
Data23-25 Feb.
Páginas203-210
Título do LivroProceedings
Histórico (UTC)2017-12-11 15:00:18 :: lattes -> administrator :: 2017
2021-02-02 03:55:10 :: administrator -> simone :: 2017
3. Conteúdo e estrutura
É a matriz ou uma cópia?é a matriz
Estágio do Conteúdoconcluido
Transferível1
Tipo do ConteúdoExternal Contribution
Tipo de Versãopublisher
Palavras-ChaveMetaheuristics
Fine-tuning
Combinatorial optimization
Nonparametric statistics
ResumoThe fine-tuning of the algorithms parameters, specially, in metaheuristics, is not always trivial and often is performed by ad hoc methods according to the problem under analysis. Usually, incorrect settings influence both in the algorithms performance, as in the quality of solutions. The tuning of metaheuristics requires the use of innovative methodologies, usually interesting to different research communities. In this context, this paper aims to contribute to the literature by presenting a methodology combining Statistical and Artificial Intelligence methods in the fine-tuning of metaheuristics. The key idea is a heuristic method, called Heuristic Oriented Racing Algorithm (HORA), which explores a search space of parameters, looking for candidate configurations near of a promising alternative, and consistently finds good settings for different metaheuristics. To confirm the validity of this approach, we present a case study for fine-tuning two distinct metaheuristics: Simulated Annealing (SA) and Genetic Algorithm (GA), in order to solve a classical task scheduling problem. The results of the proposed approach are compared with results yielded by the same metaheuristics tuned through different strategies, such as the brute-force and racing. Broadly, the proposed method proved to be effective in terms of the overall time of the tuning process. Our results from experimental studies reveal that metaheuristics tuned by means of HORA reach the same good results than when tuned by the other time-consuming fine-tuning approaches. Therefore, from the results presented in this study it is concluded that HORA is a promising and powerful tool for the fine-tuning of different metaheuristics, mainly when the overall time of tuning process is considered.
ÁreaMET
Arranjo 1urlib.net > Fonds > Produção anterior à 2021 > DIDOP > A heuristic for...
Arranjo 2urlib.net > BDMCI > Fonds > Produção anterior à 2021 > DIDAS > A heuristic for...
Conteúdo da Pasta docacessar
Conteúdo da Pasta sourcenão têm arquivos
Conteúdo da Pasta agreementnão têm arquivos
4. Condições de acesso e uso
URL dos dadoshttp://urlib.net/ibi/8JMKD3MGP3W/3P5TDPL
URL dos dados zipadoshttp://urlib.net/zip/8JMKD3MGP3W/3P5TDPL
Idiomaen
Arquivo Alvobarbosa_a heuristic.pdf
Grupo de Usuárioslattes
Grupo de Leitoresadministrator
lattes
Visibilidadeshown
Permissão de Leituraallow from all
Permissão de Atualizaçãonão transferida
5. Fontes relacionadas
Unidades Imediatamente Superiores8JMKD3MGPCW/43SQKNE
8JMKD3MGPCW/444NC7P
Acervo Hospedeirodpi.inpe.br/plutao@80/2008/08.19.15.01
6. Notas
Campos Vaziosarchivingpolicy archivist callnumber copyholder copyright creatorhistory descriptionlevel dissemination e-mailaddress edition editor format issn lineage mark mirrorrepository nextedition notes numberofvolumes orcid organization parameterlist parentrepositories previousedition previouslowerunit progress project publisher publisheraddress resumeid rightsholder schedulinginformation secondarydate secondarykey secondarymark serieseditor session shorttitle sponsor subject tertiarymark tertiarytype type url volume
7. Controle da descrição
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