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A proportional linguistic distribution based model for multiple attribute decision making under linguistic uncertainty

Author

Listed:
  • Wen-Tao Guo

    (Japan Advanced Institute of Science and Technology)

  • Van-Nam Huynh

    (Japan Advanced Institute of Science and Technology)

  • Songsak Sriboonchitta

    (Chiang Mai University)

Abstract

This paper aims at developing a proportional fuzzy linguistic distribution model for multiple attribute decision making problems, which is based on the nature of symbolic linguistic model combined with distributed assessments. Particularly, in this model the evaluation on attributes of alternatives is represented by distributions on the linguistic term set used as an instrument for assessment. In addition, this new model is also able to deal with incomplete linguistic assessments so that it allows evaluators to avoid the dilemma of having to supply complete assessments when not available. As for aggregation and ranking problems of proportional fuzzy linguistic distributions, the extension of conventional aggregation operators as well as the expected utility in this proportional fuzzy linguistic distribution model are also examined. Finally, the proposed model will be illustrated with an application in product evaluation.

Suggested Citation

  • Wen-Tao Guo & Van-Nam Huynh & Songsak Sriboonchitta, 2017. "A proportional linguistic distribution based model for multiple attribute decision making under linguistic uncertainty," Annals of Operations Research, Springer, vol. 256(2), pages 305-328, September.
    • Handle: RePEc:spr:annopr:v:256:y:2017:i:2:d:10.1007_s10479-016-2356-4
    DOI: 10.1007/s10479-016-2356-4
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    References listed on IDEAS

    as
    1. Dong-Ling Xu, 2012. "An introduction and survey of the evidential reasoning approach for multiple criteria decision analysis," Annals of Operations Research, Springer, vol. 195(1), pages 163-187, May.
    2. Keeney,Ralph L. & Raiffa,Howard, 1993. "Decisions with Multiple Objectives," Cambridge Books, Cambridge University Press, number 9780521438834, October.
    3. Yang, Jian-Bo, 2001. "Rule and utility based evidential reasoning approach for multiattribute decision analysis under uncertainties," European Journal of Operational Research, Elsevier, vol. 131(1), pages 31-61, May.
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    Cited by:

    1. Feifei Jin & Chang Li & Jinpei Liu & Ligang Zhou, 2021. "Distribution Linguistic Fuzzy Group Decision Making Based on Consistency and Consensus Analysis," Mathematics, MDPI, vol. 9(19), pages 1-19, October.
    2. Wenyu Yu & Zhen Zhang & Qiuyan Zhong, 2021. "Consensus reaching for MAGDM with multi-granular hesitant fuzzy linguistic term sets: a minimum adjustment-based approach," Annals of Operations Research, Springer, vol. 300(2), pages 443-466, May.
    3. Weidong Zhu & Shaorong Li & Hongtao Zhang & Tianjiao Zhang & Zhimin Li, 2022. "Evaluation of scientific research projects on the basis of evidential reasoning approach under the perspective of expert reliability," Scientometrics, Springer;Akadémiai Kiadó, vol. 127(1), pages 275-298, January.

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