Clustering problems in a multiobjective framework

 

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Detalles Bibliográficos
Autores: Hernández, Yunay, Beausoleil, Ricardo
Formato: artículo original
Estado:Versión publicada
Fecha de Publicación:2016
Descripción:We propose a new algorithm using tabu search to deal with biobjective clustering problems. A cluster is a collection of records that are similar to one other and dissimilar to records in other clusters. Clustering has applications in VLSI design, protein-protein interaction networks, data mining and many others areas. Clustering problems have been subject of numerous studies; however, most of the work has focused on single-objective problems. In the context of multiobjective optimization our aim is to find a good approximation to the Pareto front and provide a method to make decisions. As an application problem we present the zoning problem by allowing the optimization of two objectives.
País:Portal de Revistas UCR
Institución:Universidad de Costa Rica
Repositorio:Portal de Revistas UCR
Lenguaje:Inglés
OAI Identifier:oai:portal.ucr.ac.cr:article/25270
Acceso en línea:https://revistas.ucr.ac.cr/index.php/matematica/article/view/25270
Palabra clave:combinatorial data analysis
clustering
tabu search
multiobjective optimization
Análisis de datos combinatorio
cluster
búsqueda tabú
optimización multiobjetivo