IDEAS home Printed from https://ideas.repec.org/a/taf/tjsmxx/v2y2008i1p29-40.html
   My bibliography  Save this article

On the interaction between stratification and control variates, with illustrations in a call centre simulation

Author

Listed:
  • P L'Ecuyer
  • E Buist

Abstract

Variance reduction techniques (VRTs) are often essential to make simulation quick and accurate enough to be useful. A case in point is simulation-based optimization of complex systems. An obvious idea to push the improvement one step further is to combine several VRTs for a given simulation. But such combinations often give rise to new issues. This paper studies the combination of stratification with control variates. We detail and compare several ways of doing the combination. Nontrivial synergies between the two methods are exhibited. We illustrate this with a telephone call centre simulation, where we combine a control variate with stratification with respect to one of the uniform random variates that drive the simulation. It turns out that using more information in the control variate degrades the performance (significantly) in our example. This seemingly paradoxical behaviour is not rare and our theoretical analysis explains why.

Suggested Citation

  • P L'Ecuyer & E Buist, 2008. "On the interaction between stratification and control variates, with illustrations in a call centre simulation," Journal of Simulation, Taylor & Francis Journals, vol. 2(1), pages 29-40, March.
    • Handle: RePEc:taf:tjsmxx:v:2:y:2008:i:1:p:29-40
    DOI: 10.1057/palgrave.jos.4250035
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1057/palgrave.jos.4250035
    Download Restriction: Access to full text is restricted to subscribers.
    File URL: https://libkey.io/10.1057/palgrave.jos.4250035?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. Pierre L’Ecuyer & Florian Puchhammer & Amal Ben Abdellah, 2022. "Monte Carlo and Quasi–Monte Carlo Density Estimation via Conditioning," INFORMS Journal on Computing, INFORMS, vol. 34(3), pages 1729-1748, May.

    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:tjsmxx:v:2:y:2008:i:1:p:29-40. 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/tjsm .

    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.