Solving the manufacturing cell design problem via invasiveweed optimization

Ricardo Soto, Broderick Crawford, Carlos Castillo, Fernando Paredes

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

8 Citas (Scopus)

Resumen

Manufacturing plants are commonly organized in cells containing machines that process different parts of a given product. The Manufacturing Cell Design Problem (MCDP) aims at efficiently organizing the machines into cells in order to increase productivity by minimizing the inter-cell moves of parts. In this paper, we present a new approach based on Invasive Weed Optimization (IWO) for solving such a problem. The IWO algorithm is a recent metaheuristic inspired on the colonization behavior of the invasive weeds in agriculture. IWO represents the solutions as weeds that grow and produce seeds to be randomly dispersed over the search area. We additionally incorporate a binary neighbor operator in order to efficiently handle the binary nature of the problem. The experimental results demonstrate the efficiency of the proposed approach which is able to reach several global optimums for a set of 90 well-known MCDP instances.

Idioma originalInglés
Título de la publicación alojadaArtificial Intelligence Perspectives in Intelligent Systems - Proceedings of 5th Computer Science On-line Conference, CSOC 2016
EditoresRadek Silhavy, Roman Senkerik, Zuzana Kominkova Oplatkova, Petr Silhavy, Zdenka Prokopova
EditorialSpringer Verlag
Páginas115-126
Número de páginas12
ISBN (versión impresa)9783319336237
DOI
EstadoPublicada - 2016
Publicado de forma externa
Evento5th Computer Science On-line Conference, CSOC 2016 - Prague, República Checa
Duración: 27 abr. 201630 abr. 2016

Serie de la publicación

NombreAdvances in Intelligent Systems and Computing
Volumen464
ISSN (versión impresa)2194-5357

Conferencia

Conferencia5th Computer Science On-line Conference, CSOC 2016
País/TerritorioRepública Checa
CiudadPrague
Período27/04/1630/04/16

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