@inproceedings{28f45900fe7e4b5082db118803188df4,
title = "Solving the manufacturing cell design problem via invasiveweed optimization",
abstract = "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.",
keywords = "Invasive Weed Optimization, Manufacturing Cell Design, Metaheuristics, Optimization",
author = "Ricardo Soto and Broderick Crawford and Carlos Castillo and Fernando Paredes",
note = "Publisher Copyright: {\textcopyright} Springer International Publishing Switzerland 2016.; 5th Computer Science On-line Conference, CSOC 2016 ; Conference date: 27-04-2016 Through 30-04-2016",
year = "2016",
doi = "10.1007/978-3-319-33625-1_11",
language = "English",
isbn = "9783319336237",
series = "Advances in Intelligent Systems and Computing",
publisher = "Springer Verlag",
pages = "115--126",
editor = "Radek Silhavy and Roman Senkerik and Oplatkova, {Zuzana Kominkova} and Petr Silhavy and Zdenka Prokopova",
booktitle = "Artificial Intelligence Perspectives in Intelligent Systems - Proceedings of 5th Computer Science On-line Conference, CSOC 2016",
}