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A New Entropy-based Intuitionistic Fuzzy Multi-attribute Decision Making Method

Received: 6 October 2016     Accepted: 14 October 2016     Published: 7 November 2016
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Abstract

The main task of this paper is to develop a new decision making method based on a novel entropy measure of intuitionistic fuzzy sets. First a novel intuitionistic fuzzy entropy is constructed, then based on this information measure, new weighting methods are proposed for the intuitionistic fuzzy decision making problems with the attribute weights are completely unknown or partly known. Further the intuitionistic fuzzy TOPSIS method is developed in this paper, and two examples are given to illustrate effectiveness and practicability of proposed method.

Published in American Journal of Applied Mathematics (Volume 4, Issue 6)
DOI 10.11648/j.ajam.20160406.13
Page(s) 277-282
Creative Commons

This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited.

Copyright

Copyright © The Author(s), 2016. Published by Science Publishing Group

Keywords

Intuitionistic Fuzzy Number, Entropy, Multi-Attribute Decision Making, TOPSIS Method

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Cite This Article
  • APA Style

    Lanping Li. (2016). A New Entropy-based Intuitionistic Fuzzy Multi-attribute Decision Making Method. American Journal of Applied Mathematics, 4(6), 277-282. https://doi.org/10.11648/j.ajam.20160406.13

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    ACS Style

    Lanping Li. A New Entropy-based Intuitionistic Fuzzy Multi-attribute Decision Making Method. Am. J. Appl. Math. 2016, 4(6), 277-282. doi: 10.11648/j.ajam.20160406.13

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    AMA Style

    Lanping Li. A New Entropy-based Intuitionistic Fuzzy Multi-attribute Decision Making Method. Am J Appl Math. 2016;4(6):277-282. doi: 10.11648/j.ajam.20160406.13

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  • @article{10.11648/j.ajam.20160406.13,
      author = {Lanping Li},
      title = {A New Entropy-based Intuitionistic Fuzzy Multi-attribute Decision Making Method},
      journal = {American Journal of Applied Mathematics},
      volume = {4},
      number = {6},
      pages = {277-282},
      doi = {10.11648/j.ajam.20160406.13},
      url = {https://doi.org/10.11648/j.ajam.20160406.13},
      eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.ajam.20160406.13},
      abstract = {The main task of this paper is to develop a new decision making method based on a novel entropy measure of intuitionistic fuzzy sets. First a novel intuitionistic fuzzy entropy is constructed, then based on this information measure, new weighting methods are proposed for the intuitionistic fuzzy decision making problems with the attribute weights are completely unknown or partly known. Further the intuitionistic fuzzy TOPSIS method is developed in this paper, and two examples are given to illustrate effectiveness and practicability of proposed method.},
     year = {2016}
    }
    

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  • TY  - JOUR
    T1  - A New Entropy-based Intuitionistic Fuzzy Multi-attribute Decision Making Method
    AU  - Lanping Li
    Y1  - 2016/11/07
    PY  - 2016
    N1  - https://doi.org/10.11648/j.ajam.20160406.13
    DO  - 10.11648/j.ajam.20160406.13
    T2  - American Journal of Applied Mathematics
    JF  - American Journal of Applied Mathematics
    JO  - American Journal of Applied Mathematics
    SP  - 277
    EP  - 282
    PB  - Science Publishing Group
    SN  - 2330-006X
    UR  - https://doi.org/10.11648/j.ajam.20160406.13
    AB  - The main task of this paper is to develop a new decision making method based on a novel entropy measure of intuitionistic fuzzy sets. First a novel intuitionistic fuzzy entropy is constructed, then based on this information measure, new weighting methods are proposed for the intuitionistic fuzzy decision making problems with the attribute weights are completely unknown or partly known. Further the intuitionistic fuzzy TOPSIS method is developed in this paper, and two examples are given to illustrate effectiveness and practicability of proposed method.
    VL  - 4
    IS  - 6
    ER  - 

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Author Information
  • Department of Basic Subjects, Hunan University of Finance and Economics, Changsha, China

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