Solving manufacturing cell design problems using an artificial fish swarm algorithm

Ricardo Soto, Broderick Crawford, Emanuel Vega, Fernando Paredes

Producción científica: Capítulo del libro/informe/acta de congresoContribución a la conferenciarevisión exhaustiva

11 Citas (Scopus)

Resumen

The design of manufacturing cells is a manufacturing strategy that involves the creation of an optimal design of production plants, whose main objective is to minimize movements and exchange of material between these cells. Optimal solution of large scale manufacturing cell design problems (MCDPs) are often computationally unfeasible and only heuristic and approximate methods are able to handle such problems. Artificial fish swarm algorithm (AFSA) belongs to the swarm intelligence algorithms, which based on population search, are able to solve complex optimization problems. In this paper we present an AFSA-based approach to solve the MCDP by using the classic Boctor’s mathematical model. The obtained results show that the proposed algorithm produces optimal solutions for all the 50 studied instances.

Idioma originalInglés
Título de la publicación alojadaAdvances in Artificial Intelligence and Soft Computing - 14th Mexican International Conference on Artificial Intelligence, MICAI 2015, Proceedings
EditoresGrigori Sidorov, SofÍa N. Galicia-Haro
EditorialSpringer Verlag
Páginas282-290
Número de páginas9
ISBN (versión impresa)9783319270593
DOI
EstadoPublicada - 2015
Evento14th Mexican International Conference on Artificial Intelligence, MICAI 2015 - Cuernavaca, Morelos, México
Duración: 25 oct. 201531 oct. 2015

Serie de la publicación

NombreLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volumen9413
ISSN (versión impresa)0302-9743
ISSN (versión digital)1611-3349

Conferencia

Conferencia14th Mexican International Conference on Artificial Intelligence, MICAI 2015
País/TerritorioMéxico
CiudadCuernavaca, Morelos
Período25/10/1531/10/15

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