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Solving Machine Part Cell Formation Problem Using Genetic Algorithm Based Evolutionary Computing

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Proceedings of the Eighth International Conference on Soft Computing and Pattern Recognition (SoCPaR 2016) (SoCPaR 2016)

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 614))

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Abstract

Machine part cell formation is the group technology problem, in which the parts with near similar machining requirements are grouped into part families and the corresponding machines into machine cells. In this paper, a genetic algorithm with a fine tuning procedure is proposed to solve the group technology problem considering only one process plan for each part. The grouping efficacy achieved by the proposed method is comparable to the existing methods in general and better for 11.42% of the datasets.

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Author information

Authors and Affiliations

  1. School of Information Technology and Engineering, VIT University, Vellore, India

    N. Sowmiya

  2. Department of Software and Systems Engineering, School of Information Technology and Engineering, VIT University, Vellore, India

    B. Valarmathi

  3. School of Mechanical Engineering, VIT University, Vellore, India

    N. Srinivasa Gupta

Authors
  1. N. Sowmiya
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  2. B. Valarmathi
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  3. N. Srinivasa Gupta
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Corresponding author

Correspondence to N. Srinivasa Gupta .

Editor information

Editors and Affiliations

  1. Scientific Network for Innovation and Research, Machine Intelligence Research Labs (MIR Labs), Auburn, Washington, USA

    Ajith Abraham

  2. VIT University, Vellore, Tamil Nadu, India

    Aswani Kumar Cherukuri

  3. School of Engineering, Polytechnic of Porto (ISEP/IPP), Porto, Portugal

    Ana Maria Madureira

  4. Universiti Teknikal Malaysia Melaka, Durian Tunggal, Malaysia

    Azah Kamilah Muda

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Sowmiya, N., Valarmathi, B., Srinivasa Gupta, N. (2018). Solving Machine Part Cell Formation Problem Using Genetic Algorithm Based Evolutionary Computing. In: Abraham, A., Cherukuri, A., Madureira, A., Muda, A. (eds) Proceedings of the Eighth International Conference on Soft Computing and Pattern Recognition (SoCPaR 2016). SoCPaR 2016. Advances in Intelligent Systems and Computing, vol 614. Springer, Cham. https://doi.org/10.1007/978-3-319-60618-7_20

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  • DOI: https://doi.org/10.1007/978-3-319-60618-7_20

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-60617-0

  • Online ISBN: 978-3-319-60618-7

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