IDEAS home Printed from https://ideas.repec.org/a/taf/tsysxx/v43y2012i12p2275-2287.html
   My bibliography  Save this article

A parameter-tuned genetic algorithm for statistically constrained economic design of multivariate CUSUM control charts: a Taguchi loss approach

Author

Listed:
  • Seyed Niaki
  • Mohammad Ershadi

Abstract

In this research, the main parameters of the multivariate cumulative sum (CUSUM) control chart (the reference value k, the control limit H, the sample size n and the sampling interval h) are determined by minimising the Lorenzen–Vance cost function [Lorenzen, T.J., and Vance, L.C. (1986), ‘The Economic Design of Control Charts: A Unified Approach’, Technometrics, 28, 3–10], in which the external costs of employing the chart are added. In addition, the model is statistically constrained to achieve desired in-control and out-of-control average run lengths. The Taguchi loss approach is used to model the problem and a genetic algorithm, for which its main parameters are tuned using the response surface methodology (RSM), is proposed to solve it. At the end, sensitivity analyses on the main parameters of the cost function are presented and their practical conclusions are drawn. The results show that RSM significantly improves the performance of the proposed algorithm and the external costs of applying the chart, which are due to real-world constraints, do not increase the average total loss very much.

Suggested Citation

  • Seyed Niaki & Mohammad Ershadi, 2012. "A parameter-tuned genetic algorithm for statistically constrained economic design of multivariate CUSUM control charts: a Taguchi loss approach," International Journal of Systems Science, Taylor & Francis Journals, vol. 43(12), pages 2275-2287.
  • Handle: RePEc:taf:tsysxx:v:43:y:2012:i:12:p:2275-2287
    DOI: 10.1080/00207721.2011.570878
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1080/00207721.2011.570878
    Download Restriction: Access to full text is restricted to subscribers.

    File URL: https://libkey.io/10.1080/00207721.2011.570878?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.

    Citations

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


    Cited by:

    1. M.J. Ershadi & R. Noorossana & S.T.A Niaki, 2016. "Economic-statistical design of simple linear profiles with variable sampling interval," Journal of Applied Statistics, Taylor & Francis Journals, vol. 43(8), pages 1400-1418, June.
    2. Jose Jorge Muñoz & Manuel J. Campuzano & Jaime Mosquera, 2022. "Optimized np Attribute Control Chart Using Triple Sampling," Mathematics, MDPI, vol. 10(20), pages 1-21, October.
    3. Amir Ahmadi-Javid & Mohsen Ebadi, 2021. "Economic design of memory-type control charts: The fallacy of the formula proposed by Lorenzen and Vance (1986)," Computational Statistics, Springer, vol. 36(1), pages 661-690, March.

    More about this item

    Statistics

    Access and download statistics

    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:taf:tsysxx:v:43:y:2012:i:12:p:2275-2287. 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.

    We have no bibliographic references for this item. You can help adding them by using 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: Chris Longhurst (email available below). General contact details of provider: http://www.tandfonline.com/TSYS20 .

    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.