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Applying neural network and scatter search to optimize parameter design with dynamic characteristics

Author

Listed:
  • Chao-Ton Su

    (National Tsing Hua University)

  • Mu-Chen Chen

    (National Taipei University of Technology)

  • Hsiao-Ling Chan

    (Ta Hwa Institute of Technology)

Abstract

Parameter design is critical to enhancing a system's robustness by identifying specific control factor set points (levels) that make the system least sensitive to noise. Engineers have conventionally applied Taguchi methods to optimize parameter design. However, Taguchi methods can only obtain the optimal solution among the specified control factor levels. They cannot identify the real optimum when the parameter values are continuous. This study proposes a hybrid procedure combining neural networks and scatter search to optimize the continuous parameter design problem. First, neural networks are used to simulate the relationship between the control factor values and corresponding responses. Second, scatter search is employed to obtain the optimal parameter settings. The desirability function is utilized to transform the multiple responses into a single response. A case with dynamic characteristics is carried out in blood glucose strip manufacturing in Taiwan to demonstrate the practicability of the proposed procedure.

Suggested Citation

  • Chao-Ton Su & Mu-Chen Chen & Hsiao-Ling Chan, 2005. "Applying neural network and scatter search to optimize parameter design with dynamic characteristics," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 56(10), pages 1132-1140, October.
    • Handle: RePEc:pal:jorsoc:v:56:y:2005:i:10:d:10.1057_palgrave.jors.2601888
    DOI: 10.1057/palgrave.jors.2601888
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    References listed on IDEAS

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    1. Kwang‐Jae Kim & Dennis K. J. Lin, 2000. "Simultaneous optimization of mechanical properties of steel by maximizing exponential desirability functions," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 49(3), pages 311-325.
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    Cited by:

    1. Abbas Al-Refaie & Wafa’a Al-Alaween & Ali Diabat & Ming-Hsien Li, 2017. "Solving dynamic systems with multi-responses by integrating desirability function and data envelopment analysis," Journal of Intelligent Manufacturing, Springer, vol. 28(2), pages 387-403, February.
    2. Edwin Dam & Bart Husslage & Dick Hertog, 2010. "One-dimensional nested maximin designs," Journal of Global Optimization, Springer, vol. 46(2), pages 287-306, February.

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