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Solving Manufacturing Cell Design Problems Using an Artificial Fish Swarm Algorithm

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Advances in Artificial Intelligence and Soft Computing (MICAI 2015)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 9413))

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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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Acknowledgements

Ricardo Soto is supported by Grant CONICYT/FONDECYT/INICIACION/11130459, Broderick Crawford is supported by Grant CONICYT/FONDECYT/1140897, and Fernando Paredes is supported by Grant CONICYT/FONDECYT/1130455.

Author information

Authors and Affiliations

  1. Pontificia Universidad Católica de Valparaíso, Valparaíso, Chile

    Ricardo Soto, Broderick Crawford & Emanuel Vega

  2. Universidad Autónoma de Chile, Temuco, Chile

    Ricardo Soto

  3. Universidad Cientifica del Sur, Lima, Peru

    Ricardo Soto

  4. Universidad Central de Chile, Santiago, Chile

    Broderick Crawford

  5. Universidad San Sebastián, Santiago, Chile

    Broderick Crawford

  6. Escuela de Ingeniería Industrial, Universidad Diego Portales, Santiago, Chile

    Fernando Paredes

Authors
  1. Ricardo Soto
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  2. Broderick Crawford
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  3. Emanuel Vega
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  4. Fernando Paredes
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Corresponding author

Correspondence to Emanuel Vega .

Editor information

Editors and Affiliations

  1. Instituto Politécnico Nacional, Centro de Investigación en Computación, Mexico City, Mexico

    Grigori Sidorov

  2. Facultad de ciencias, Universidad Autónoma Nacional, México, Distrito Federal, Mexico

    Sofía N. Galicia-Haro

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Soto, R., Crawford, B., Vega, E., Paredes, F. (2015). Solving Manufacturing Cell Design Problems Using an Artificial Fish Swarm Algorithm. In: Sidorov, G., Galicia-Haro, S. (eds) Advances in Artificial Intelligence and Soft Computing. MICAI 2015. Lecture Notes in Computer Science(), vol 9413. Springer, Cham. https://doi.org/10.1007/978-3-319-27060-9_23

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

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-27059-3

  • Online ISBN: 978-3-319-27060-9

  • eBook Packages: Computer ScienceComputer Science (R0)

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