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Applying an Electromagnetism-Like Algorithm for Solving the Manufacturing Cell Design Problem

Applying an Electromagnetism-Like Algorithm for Solving the Manufacturing Cell Design Problem

Jose M. Lanza-Gutierrez, Ricardo Soto, Broderick Crawford, Juan A. Gomez-Pulido, Nicolas Fernandez, Carlos Castillo
Copyright: © 2017 |Pages: 25
ISBN13: 9781522523222|ISBN10: 1522523227|EISBN13: 9781522523239
DOI: 10.4018/978-1-5225-2322-2.ch002
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MLA

Lanza-Gutierrez, Jose M., et al. "Applying an Electromagnetism-Like Algorithm for Solving the Manufacturing Cell Design Problem." Recent Developments in Intelligent Nature-Inspired Computing, edited by Srikanta Patnaik, IGI Global, 2017, pp. 37-61. https://doi.org/10.4018/978-1-5225-2322-2.ch002

APA

Lanza-Gutierrez, J. M., Soto, R., Crawford, B., Gomez-Pulido, J. A., Fernandez, N., & Castillo, C. (2017). Applying an Electromagnetism-Like Algorithm for Solving the Manufacturing Cell Design Problem. In S. Patnaik (Ed.), Recent Developments in Intelligent Nature-Inspired Computing (pp. 37-61). IGI Global. https://doi.org/10.4018/978-1-5225-2322-2.ch002

Chicago

Lanza-Gutierrez, Jose M., et al. "Applying an Electromagnetism-Like Algorithm for Solving the Manufacturing Cell Design Problem." In Recent Developments in Intelligent Nature-Inspired Computing, edited by Srikanta Patnaik, 37-61. Hershey, PA: IGI Global, 2017. https://doi.org/10.4018/978-1-5225-2322-2.ch002

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Abstract

Group technology has acquired a great consideration in the last years. This technique allows including the advantages of serial production to any manufacturing industry by dividing a manufacturing plant into a set of machine-part cells. The identification and formation of the cells are known as the Manufacturing Cell Design Problem (MCDP), which is an NP-hard problem. In this paper, the authors propose to solve the problem through a swarm intelligence metaheuristic called ElectroMagnetism-like (EM-like) algorithm, which is inspired by the attraction-repulsion mechanism of particles in the context of the electromagnetic theory. The original EM-like algorithm was designed for solving continuous optimization problems, while the MCDP is usually formulated by assuming a binary approach. Hence, the authors propose an adaptation of this algorithm for addressing the problem. Such adaptation is applied for solving a freely available dataset of the MCDP, obtaining competitive results compared to recent approaches.

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