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An Approach To Pure Linguistic Multiple Attribute Decision Making Under Uncertainty

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  • ZESHUI XU

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

Abstract

The pure linguistic multiple attribute decision making problems are studied, in which the information about the attribute weights are expressed in the form of linguistic variables or uncertain linguistic variables, and the attribute values take the form of uncertain linguistic variables. The operational laws of uncertain linguistic variables are introduced, and two uncertain linguistic aggregation operators called linguistic weighted aggregation operator and uncertain linguistic weighted aggregation operator are developed based on uncertain linguistic variables and their operational laws. An approach based on the developed operators for pure linguistic multiple attribute decision making under uncertainty is proposed. The prominent characteristic of the proposed approach is that it can compute with uncertain linguistic information directly. Furthermore, the approach is straightforward and does not produce any loss of information. Finally, an illustrative example is given.

Suggested Citation

  • Zeshui Xu, 2005. "An Approach To Pure Linguistic Multiple Attribute Decision Making Under Uncertainty," International Journal of Information Technology & Decision Making (IJITDM), World Scientific Publishing Co. Pte. Ltd., vol. 4(02), pages 197-206.
    • Handle: RePEc:wsi:ijitdm:v:04:y:2005:i:02:n:s0219622005001465
    DOI: 10.1142/S0219622005001465
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    Cited by:

    1. Yongming Song, 2018. "Deriving the priority weights from probabilistic linguistic preference relation with unknown probabilities," PLOS ONE, Public Library of Science, vol. 13(12), pages 1-17, December.
    2. Peide Liu & Hongyu Yang & Haiquan Wu & Meilong Ju & Fawaz E. Alsaadi, 2019. "Some Maclaurin Symmetric Mean Aggregation Operators Based on Cloud Model and Their Application to Decision-Making," International Journal of Information Technology & Decision Making (IJITDM), World Scientific Publishing Co. Pte. Ltd., vol. 18(03), pages 981-1007, May.

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