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Volume 5 Issue 3
May  2018

IEEE/CAA Journal of Automatica Sinica

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Article Navigation >  IEEE/CAA Journal of Automatica Sinica  > 2018  >  5(3): 741-748
Yang Lin and Yingming Wang, "Group Decision Making With Consistency of Intuitionistic Fuzzy Preference Relations Under Uncertainty," IEEE/CAA J. Autom. Sinica, vol. 5, no. 3, pp. 741-748, Mar. 2018. doi: 10.1109/JAS.2016.7510037
Citation: Yang Lin and Yingming Wang, "Group Decision Making With Consistency of Intuitionistic Fuzzy Preference Relations Under Uncertainty," IEEE/CAA J. Autom. Sinica, vol. 5, no. 3, pp. 741-748, Mar. 2018. doi: 10.1109/JAS.2016.7510037
shu

Group Decision Making With Consistency of Intuitionistic Fuzzy Preference Relations Under Uncertainty

doi: 10.1109/JAS.2016.7510037
  • 1.

    Institute of Decision Science, Fuzhou University, Fuzhou 350116, China, and also with the School of Economics, Fujian Normal University, Fuzhou 350116, China

  • 2.

    Institute of Decision Science, Fuzhou University, Fuzhou 350116, China

Funds:

the National Natural Science Foundation of China 71371053

the Social Science Foundation of Fujian Province FJ2015C111

More Information
    Abstract
  • Intuitionistic fuzzy preference relation (IFPR) is a suitable technique to express fuzzy preference information by decision makers (DMs). This paper aims to provide a group decision making method where DMs use the IFPRs to indicate their preferences with uncertain weights. To begin with, a model to derive weight vectors of alternatives from IFPRs based on multiplicative consistency is presented. Specifically, for any IFPR, by minimizing its absolute deviation from the corresponding consistent IFPR, the weight vectors are generated. Secondly, a method to determine relative weights of DMs depending on preference information is developed. After that we prioritize alternatives based on the obtained weights considering the risk preference of DMs. Finally, this approach is applied to the problem of technical risks assessment of armored equipment to illustrate the applicability and superiority of the proposed method.

     

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