A PSO-based clustering algorithm for manufacturing cell design

Orlando Durán, Nibaldo Rodriguez, Luiz Airton Consalter

Resultado de la investigación: Capítulo del libro/informe/acta de congresoContribución a la conferenciarevisión exhaustiva

23 Citas (Scopus)

Resumen

Since the last years different metaheuristic methods have been used to solve clustering problems. This paper addresses the problem of manufacturing Cell Formation using a modified particle swarm optimisation (PSO) algorithm. The main modification made to the original PSO algorithm consists on that in this work it is not used the vector of velocities as the standard PSO algorithm does. The proposed algorithm uses the concept of proportional likelihood with modifications, a technique that is used in data mining techniques. Some simulations are presented and compared. The criterion used to group the machines in cells is based on the minimization of inter-cell movements. The computational results show that the PSO algorithm is able to find the optima! solutions on almost all instances.

Idioma originalInglés
Título de la publicación alojadaProceedings - 1st International Workshop on Knowledge Discovery and Data Mining, WKDD
Páginas72-75
Número de páginas4
DOI
EstadoPublicada - 2008
Publicado de forma externa
Evento1st International Workshop on Knowledge Discovery and Data Mining, WKDD - Adelaide, Australia
Duración: 23 ene. 200824 ene. 2008

Serie de la publicación

NombreProceedings - 1st International Workshop on Knowledge Discovery and Data Mining, WKDD

Conferencia

Conferencia1st International Workshop on Knowledge Discovery and Data Mining, WKDD
País/TerritorioAustralia
CiudadAdelaide
Período23/01/0824/01/08

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