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Erschienen in:
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2015 | OriginalPaper | Buchkapitel

Solving Manufacturing Cell Design Problems Using an Artificial Fish Swarm Algorithm

verfasst von : Ricardo Soto, Broderick Crawford, Emanuel Vega, Fernando Paredes

Erschienen in: Advances in Artificial Intelligence and Soft Computing

Verlag: Springer International Publishing

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Abstract

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.

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Vorheriges Kapitel A Migrating Birds Optimization Algorithm for Machine-Part Cell Formation Problems
Nächstes Kapitel A Simple Bio-Inspired Model for Synaptogenesis in Artificial Neural Networks
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Metadaten
Titel
Solving Manufacturing Cell Design Problems Using an Artificial Fish Swarm Algorithm
verfasst von
Ricardo Soto
Broderick Crawford
Emanuel Vega
Fernando Paredes
Copyright-Jahr
2015
Buch
Advances in Artificial Intelligence and Soft Computing

Print ISBN: 978-3-319-27059-3

Electronic ISBN: 978-3-319-27060-9

Copyright-Jahr: 2015

DOI
https://doi.org/10.1007/978-3-319-27060-9_23

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