@inproceedings{dfd27c8aef774f4d80fed3be895a5d07,
title = "Resolving the manufacturing cell design problem via hunting search",
abstract = "The Manufacturing Cell Design Problems consists in divide a production plant into cells, through which the machines and their processed parts are grouped. The main goal is to build an optimal design that reduces the movements of parts among cells. In this paper, we resolve this problem using a recent population-based metaheuristic called Hunting Search. This technique is inspired by the behavior of a herd of animals working together to hunt a prey. The experimental results demonstrate the efficiency of the proposed approach, which reach all global optimums for a set of 27 well-known instances.",
keywords = "Hunting search, Manufacturing cell design problem, Metaheuristic, Optimization",
author = "Ricardo Soto and Broderick Crawford and Rodrigo Olivares and Nicol{\'a}s Pacheco",
note = "Publisher Copyright: {\textcopyright} 2018, Springer International Publishing AG, part of Springer Nature.; 31st International Conference on Industrial, Engineering and Other Applications of Applied Intelligent Systems IEA/AIE 2018 ; Conference date: 25-06-2018 Through 28-06-2018",
year = "2018",
doi = "10.1007/978-3-319-92058-0_40",
language = "English",
isbn = "9783319920573",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
publisher = "Springer Verlag",
pages = "414--420",
editor = "{Ait Mohamed}, Otmane and Malek Mouhoub and Samira Sadaoui and Moonis Ali",
booktitle = "Recent Trends and Future Technology in Applied Intelligence - 31st International Conference on Industrial Engineering and Other Applications of Applied Intelligent Systems, IEA/AIE 2018, Proceedings",
}