4.7 Article

Some q-Rung Orthopai Fuzzy Bonferroni Mean Operators and Their Application to Multi-Attribute Group Decision Making

Journal

INTERNATIONAL JOURNAL OF INTELLIGENT SYSTEMS
Volume 33, Issue 2, Pages 315-347

Publisher

WILEY-HINDAWI
DOI: 10.1002/int.21933

Keywords

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Funding

  1. National Natural Science Foundation of China [71771140, 71471172, 71271124]
  2. Special Funds of Taishan Scholars Project of Shandong Province [ts201511045]
  3. Shandong Provincial Social Science Planning Project [16CGLJ31, 16CKJJ27]
  4. Natural Science Foundation of Shandong Province [ZR2017MG007]
  5. Teaching Reform Research Project of Undergraduate Colleges and Universities in Shandong Province [2015Z057]
  6. Key research and development program of Shandong Province [2016GNC110016]

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In the real multi-attribute group decision making (MAGDM), there will be a mutual relationship between different attributes. As we all know, the Bonferroni mean (BM) operator has the advantage of considering interrelationships between parameters. In addition, in describing uncertain information, the eminent characteristic of q-rung orthopair fuzzy sets (q-ROFs) is that the sum of the qth power of the membership degree and the qth power of the degrees of non-membership is equal to or less than 1, so the space of uncertain information they can describe is broader. In this paper, we combine the BM operator with q-rung orthopair fuzzy numbers (q-ROFNs) to propose the q-rung orthopair fuzzy BM (q-ROFBM) operator, the q-rung orthopair fuzzy weighted BM (q-ROFWBM) operator, the q-rung orthopair fuzzy geometric BM (q-ROFGBM) operator, and the q-rung orthopair fuzzy weighted geometric BM (q-ROFWGBM) operator, then the MAGDM methods are developed based on these operators. Finally, we use an example to illustrate the MAGDM process of the proposed methods. The proposed methods based on q-ROFWBM and q-ROFWGBM operators are very useful to deal with MAGDM problems. (C) 2017 Wiley Periodicals, Inc.

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