IDEAS home Printed from https://ideas.repec.org/a/spr/mathme/v57y2003i1p41-48.html
   My bibliography  Save this article

Using an adaptive genetic algorithm with reversals to find good second-order multiple recursive random number generators

Author

Listed:
  • Hui-Chin Tang

Abstract

This paper considers the problem of searching for good second-order multiple recursive generators (MRGs) with long period and good lattice structure. An adaptive genetic algorithm with reversals is proposed. The proposed algorithm is compared with forward/backward and random methods, and its effectiveness and efficiency is numerically confirmed by the experiments. The extensively tested second-order MRG (1259791845, 1433587751) found from the proposed algorithm possesses the properties of long period and good lattice structure and is therefore recommended. Copyright Springer-Verlag Berlin Heidelberg 2003

Suggested Citation

  • Hui-Chin Tang, 2003. "Using an adaptive genetic algorithm with reversals to find good second-order multiple recursive random number generators," Mathematical Methods of Operations Research, Springer;Gesellschaft für Operations Research (GOR);Nederlands Genootschap voor Besliskunde (NGB), vol. 57(1), pages 41-48, April.
    • Handle: RePEc:spr:mathme:v:57:y:2003:i:1:p:41-48
    DOI: 10.1007/s001860200237
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1007/s001860200237
    Download Restriction: Access to full text is restricted to subscribers.
    File URL: https://libkey.io/10.1007/s001860200237?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. Tang, Hui-Chin, 2006. "Theoretical analyses of forward and backward heuristics of multiple recursive random number generators," European Journal of Operational Research, Elsevier, vol. 174(3), pages 1760-1768, November.

    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:spr:mathme:v:57:y:2003:i:1:p:41-48. 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: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.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.