Please use this identifier to cite or link to this item: http://repositorio.unicamp.br/jspui/handle/REPOSIP/93913
Type: Artigo de evento
Title: Hybrid Genetic Algorithms And Clustering
Author: Filho F.M.
Gomide F.
Abstract: This paper introduces a hybrid genetic algorithm that uses fuzzy c-means clustering technique as a mechanism to reduce fitness evaluations and to preserve solution quality. Population clustering provides a means to evaluate only the representative individual of each cluster instead of the whole population. The remaining individuals are indirectly evaluated. The aim is to maintain reasonable population size and to obtain near-optimal solutions. This is an important issue especially in large-scale, complex optimization and decision-making problems.
Editor: 
Rights: fechado
Identifier DOI: 
Address: http://www.scopus.com/inward/record.url?eid=2-s2.0-84860520522&partnerID=40&md5=c9c2b94a00e4ae8dd4f3a6c61891b29d
Date Issue: 2005
Appears in Collections:Unicamp - Artigos e Outros Documentos

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