IDEAS home Printed from https://ideas.repec.org/p/iim/iimawp/8336.html
   My bibliography  Save this paper

Evaluating Downside Risks in Reliable Networks

Author

Listed:
  • Sharma, Megha
  • Ghosh, Diptesh

Abstract

Reliable networks are those in which network elements have a positive probability of failing. Conventional performance measures for such networks concern themselves either with expected network performance or with the performance of the network when it is performing well. In reliable networks modeling critical functions, decision makers are often more concerned with network performance when the network is not performing well. In this paper, we study the single-source single-destination maximum flow problem through reliable networks and propose two risk measures to evaluate such downside performance. We propose an algorithm called COMPUTE-RISK to compute downside risk measures, and report our computational experience with the proposed algorithm.

Suggested Citation

  • Sharma, Megha & Ghosh, Diptesh, 2009. "Evaluating Downside Risks in Reliable Networks," IIMA Working Papers WP2009-09-02, Indian Institute of Management Ahmedabad, Research and Publication Department.
  • Handle: RePEc:iim:iimawp:8336
    as

    Download full text from publisher

    File URL: https://www.iima.ac.in/sites/default/files/rnpfiles/2009-09-02Diptesh.pdf
    File Function: English Version
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Megha Sharma & Ghosh, Diptesh, 2009. "Speeding Up the Estimation of Expected Maximum Flows Through Reliable Networks," IIMA Working Papers WP2009-04-05, Indian Institute of Management Ahmedabad, Research and Publication Department.
    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. Sharma, Megha & Ghosh, Diptesh, 2009. "Computing the probability mass function of the maximum flow through a reliable network," IIMA Working Papers WP2009-10-01, Indian Institute of Management Ahmedabad, Research and Publication Department.

    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. Sharma, Megha & Ghosh, Diptesh, 2009. "Computing the probability mass function of the maximum flow through a reliable network," IIMA Working Papers WP2009-10-01, Indian Institute of Management Ahmedabad, Research and Publication Department.

    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:iim:iimawp:8336. 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: the person in charge (email available below). General contact details of provider: https://edirc.repec.org/data/eciimin.html .

    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.