@inproceedings{b9d842002033445aa6965e43e9dc0087,
title = "Solving manufacturing cell design problems using an artificial fish swarm algorithm",
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{\textquoteright}s mathematical model. The obtained results show that the proposed algorithm produces optimal solutions for all the 50 studied instances.",
keywords = "Artificial fish swarm algorithm, Manufacturing cell design problem, Metaheuristic",
author = "Ricardo Soto and Broderick Crawford and Emanuel Vega and Fernando Paredes",
note = "Publisher Copyright: {\textcopyright} Springer International Publishing Switzerland 2015.; 14th Mexican International Conference on Artificial Intelligence, MICAI 2015 ; Conference date: 25-10-2015 Through 31-10-2015",
year = "2015",
doi = "10.1007/978-3-319-27060-9_23",
language = "English",
isbn = "9783319270593",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
publisher = "Springer Verlag",
pages = "282--290",
editor = "Grigori Sidorov and Galicia-Haro, {Sof{\'I}a N.}",
booktitle = "Advances in Artificial Intelligence and Soft Computing - 14th Mexican International Conference on Artificial Intelligence, MICAI 2015, Proceedings",
}