%0 Journal Article
%3 costa_advances.pdf
%4 dpi.inpe.br/plutao@80/2010/06.25.16.20.41
%@issn 1867-5662
%A Costa, Tarcisio,
%A Oliveira, Alexandre Cesar Muniz,
%A Lorena, Luiz Antonio Nogueira,
%@secondarytype PRE PI
%B Advances in Intelligent and Soft Computing
%D 2010
%F lattes: 7195702087655314 3 CostaOlivLore:2010:AdClSe
%K Clustering Search, Combinatorial Optimization, numerical optimization.
%@archivingpolicy denypublisher denyfinaldraft12
%O Soft Computing Models in Industrial and Environmental Applications, 5th International Workshop (SOCO 2010)
%P 227-235
%T Advances in Clustering Search
%V 73
%X The Clustering Search (*CS) has been proposed as a generic way of combining search metaheuristics with clustering to detect promising search areas before applying local search procedures. The clustering process may keep representative solutions associated to different search subspaces. Although, recent applications have reached success in combinatorial optimisation problems, nothing new has arisen concerning diversification issues when population metaheuristics, as evolutionary algorithms, are being employed. In this work, recent advances in the *CS are commented and new features are proposed, including, the possibility of keeping population diversified for more generations.
%@area COMP
%@electronicmailaddress lorena@lac.inpe.br
%@e-mailaddress lorena@lac.inpe.br
%@documentstage not transferred
%@group LAC-CTE-INPE-MCT-BR
%@group
%@group LAC-CTE-INPE-MCT-BR
%@usergroup administrator
%@usergroup lattes
%@usergroup marciana
%@nexthigherunit 8JMKD3MGPCW/3ESGTTP
%@affiliation Instituto Nacional de Pesquisas Espaciais (INPE)
%@affiliation
%@affiliation Instituto Nacional de Pesquisas Espaciais (INPE)
%@versiontype publisher
%@holdercode {isadg {BR SPINPE} ibi 8JMKD3MGPCW/3DT298S}
%@doi 10.1007/978-3-642-13161-5_29
%2 dpi.inpe.br/plutao@80/2010/06.25.16.20.42