IDEAS home Printed from https://ideas.repec.org/a/wsi/ijitdm/v03y2004i03ns0219622004001161.html
   My bibliography  Save this article

Projection Method For Uncertain Multi-Attribute Decision Making With Preference Information On Alternatives

Author

Listed:
  • ZESHUI XU

    (College of Economics and Management, Southeast University, Nanjing, Jiangsu 210096, P.R. China)

  • QINGLI DA

    (College of Economics and Management, Southeast University, Nanjing, Jiangsu 210096, P.R. China)

Abstract

In this paper, we study the uncertain multiple attribute decision making problems with preference information on alternatives (UMADM-PIA, for short), in which the information on attribute weights is not precisely known, but value ranges can be obtained. A projection method is proposed for the UMADM-PIA. To reflect the decision maker's preference information, a projection model is established to determine the weights of attributes, and then to select the most desirable alternative(s). The method can reflect both the objective information and the decision maker's subjective preferences, and can also be performed on computer easily. Finally, an illustrative example is given to verify the proposed method and to demonstrate its feasibility and practicality.

Suggested Citation

  • Zeshui Xu & Qingli Da, 2004. "Projection Method For Uncertain Multi-Attribute Decision Making With Preference Information On Alternatives," International Journal of Information Technology & Decision Making (IJITDM), World Scientific Publishing Co. Pte. Ltd., vol. 3(03), pages 429-434.
  • Handle: RePEc:wsi:ijitdm:v:03:y:2004:i:03:n:s0219622004001161
    DOI: 10.1142/S0219622004001161
    as

    Download full text from publisher

    File URL: http://www.worldscientific.com/doi/abs/10.1142/S0219622004001161
    Download Restriction: Access to full text is restricted to subscribers

    File URL: https://libkey.io/10.1142/S0219622004001161?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. Yan Ni & Hua Zhao & Zeshui Xu & Zeyan Wang, 2022. "Multiple attribute decision-making method based on projection model for dual hesitant fuzzy set," Fuzzy Optimization and Decision Making, Springer, vol. 21(2), pages 263-289, June.

    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:wsi:ijitdm:v:03:y:2004:i:03:n:s0219622004001161. 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: Tai Tone Lim (email available below). General contact details of provider: http://www.worldscinet.com/ijitdm/ijitdm.shtml .

    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.