IDEAS home Printed from https://ideas.repec.org/a/pal/jorsoc/v56y2005i10d10.1057_palgrave.jors.2601888.html
   My bibliography  Save this article

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
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1057/palgrave.jors.2601888
    File Function: Abstract
    Download Restriction: Access to full text is restricted to subscribers.
    File URL: https://libkey.io/10.1057/palgrave.jors.2601888?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    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.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    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.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Paul L. Goethals & Natalie M. Scala, 2018. "Eliminating the Weakest Link Approach to Army Unit Readiness," Decision Analysis, INFORMS, vol. 15(2), pages 110-130, June.
    2. Riva, Lorenzo & Nielsen, Henrik Kofoed & Skreiberg, Øyvind & Wang, Liang & Bartocci, Pietro & Barbanera, Marco & Bidini, Gianni & Fantozzi, Francesco, 2019. "Analysis of optimal temperature, pressure and binder quantity for the production of biocarbon pellet to be used as a substitute for coke," Applied Energy, Elsevier, vol. 256(C).
    3. Zhen He & Jing Wang & Jinho Oh & Sung H. Park, 2010. "Robust optimization for multiple responses using response surface methodology," Applied Stochastic Models in Business and Industry, John Wiley & Sons, vol. 26(2), pages 157-171, March.
    4. Jessenberger, J. & Weihs, Claus, 2004. "Desirability to characterize process capability," Technical Reports 2004,73, Technische Universität Dortmund, Sonderforschungsbereich 475: Komplexitätsreduktion in multivariaten Datenstrukturen.
    5. Murat Köksalan & Robert D. Plante, 2003. "Interactive Multicriteria Optimization for Multiple-Response Product and Process Design," Manufacturing & Service Operations Management, INFORMS, vol. 5(4), pages 334-347, May.
    6. Hsiu-Wen Chen & Weng Kee Wong & Hongquan Xu, 2012. "An augmented approach to the desirability function," Journal of Applied Statistics, Taylor & Francis Journals, vol. 39(3), pages 599-613, July.
    7. Mouhamadou Mansour Mbow & Christelle Grandvallet & Frederic Vignat & Philippe Rene Marin & Nicolas Perry & Franck Pourroy, 2022. "Mathematization of experts knowledge: example of part orientation in additive manufacturing," Journal of Intelligent Manufacturing, Springer, vol. 33(5), pages 1209-1227, June.
    8. Bera, Sasadhar & Mukherjee, Indrajit, 2016. "A multistage and multiple response optimization approach for serial manufacturing system," European Journal of Operational Research, Elsevier, vol. 248(2), pages 444-452.
    9. Bera, Sasadhar & Mukherjee, Indrajit, 2012. "An ellipsoidal distance-based search strategy of ants for nonlinear single and multiple response optimization problems," European Journal of Operational Research, Elsevier, vol. 223(2), pages 321-332.
    10. Kazemzadeh, Reza B. & Bashiri, Mahdi & Atkinson, Anthony C. & Noorossana, Rassoul, 2008. "A general framework for multiresponse optimization problems based on goal programming," European Journal of Operational Research, Elsevier, vol. 189(2), pages 421-429, September.
    11. Chiang, Tai-Lin & Su, Chao-Ton, 2003. "Optimization of TQFP molding process using neuro-fuzzy-GA approach," European Journal of Operational Research, Elsevier, vol. 147(1), pages 156-164, May.
    12. Jeong, In-Jun & Kim, Kwang-Jae, 2009. "An interactive desirability function method to multiresponse optimization," European Journal of Operational Research, Elsevier, vol. 195(2), pages 412-426, June.
    13. 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.
    14. Hsu, Chih-Ming, 2004. "An integrated approach to enhance the optical performance of couplers based on neural networks, desirability functions and tabu search," International Journal of Production Economics, Elsevier, vol. 92(3), pages 241-254, December.
    15. Shi, Liangxing & Lin, Dennis K.J. & Peterson, John J., 2016. "A confidence region for the ridge path in multiple response surface optimization," European Journal of Operational Research, Elsevier, vol. 252(3), pages 829-836.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:pal:jorsoc:v:56:y:2005:i:10:d:10.1057_palgrave.jors.2601888. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.palgrave-journals.com/ .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.