IDEAS home Printed from https://ideas.repec.org/a/taf/lstaxx/v49y2020i13p3313-3328.html
   My bibliography  Save this article

Minimizing the expected time to detect a randomly located lost target using 3-dimensional search technique

Author

Listed:
  • Tomás Caraballo
  • Abd El-Moneim Anwar Teamah
  • Abd Al-Aziz Hosni El-Bagoury

Abstract

This paper considers a new model in search theory to find a randomly located target in the 3-dimensional space. An approximation algorithm that facilitates searching procedures for searchers or robots is presented. The expected time to detect the target is also proved. The statistical analysis by calculating the optimal search strategy which minimizes the time to detect the target, assuming trivariate standard normal distribution is provided, and the technique by flowcharts is designed as well. The effectiveness of this strategy is illustrated by introducing an application from real world.

Suggested Citation

  • Tomás Caraballo & Abd El-Moneim Anwar Teamah & Abd Al-Aziz Hosni El-Bagoury, 2020. "Minimizing the expected time to detect a randomly located lost target using 3-dimensional search technique," Communications in Statistics - Theory and Methods, Taylor & Francis Journals, vol. 49(13), pages 3313-3328, July.
  • Handle: RePEc:taf:lstaxx:v:49:y:2020:i:13:p:3313-3328
    DOI: 10.1080/03610926.2019.1588323
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1080/03610926.2019.1588323
    Download Restriction: Access to full text is restricted to subscribers.

    File URL: https://libkey.io/10.1080/03610926.2019.1588323?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.

    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:lstaxx:v:49:y:2020:i:13:p:3313-3328. 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/lsta .

    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.