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Volume 6 Issue 2
Mar.  2019

IEEE/CAA Journal of Automatica Sinica

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Article Navigation >  IEEE/CAA Journal of Automatica Sinica  > 2019  >  6(2): 527-539
Huidong Wang, Shifan He, Chengdong Li and Xiaohong Pan, "Pythagorean Uncertain Linguistic Variable Hamy Mean Operator and Its Application to Multi-attribute Group Decision Making," IEEE/CAA J. Autom. Sinica, vol. 6, no. 2, pp. 527-539, Mar. 2019. doi: 10.1109/JAS.2019.1911408
Citation: Huidong Wang, Shifan He, Chengdong Li and Xiaohong Pan, "Pythagorean Uncertain Linguistic Variable Hamy Mean Operator and Its Application to Multi-attribute Group Decision Making," IEEE/CAA J. Autom. Sinica, vol. 6, no. 2, pp. 527-539, Mar. 2019. doi: 10.1109/JAS.2019.1911408
shu

Pythagorean Uncertain Linguistic Variable Hamy Mean Operator and Its Application to Multi-attribute Group Decision Making

doi: 10.1109/JAS.2019.1911408
  • 1.

    School of Management Science and Engineering, Shandong University of Finance and Economics, Jinan 250014, China

  • 2.

    School of Information and Electrical Engineering, Shandong Jianzhu University, Jinan 250101, China

Funds:

the National Natural Science Foundation of China 61402260

the National Natural Science Foundation of China 61473176

Taishan Scholar Project of Shandong Province TSQN201812092

More Information
    Abstract
  • Pythagorean fuzzy set (PFS) can provide more flexibility than intuitionistic fuzzy set (IFS) for handling uncertain information, and PFS has been increasingly used in multi-attribute decision making problems. This paper proposes a new multi-attribute group decision making method based on Pythagorean uncertain linguistic variable Hamy mean (PULVHM) operator and VIKOR method. Firstly, we define operation rules and a new aggregation operator of Pythagorean uncertain linguistic variable (PULV) and explore some properties of the operator. Secondly, taking the decision makers' hesitation degree into account, a new score function is defined, and we further develop a new group decision making approach integrated with VIKOR method. Finally, an investment example is demonstrated to elaborate the validity of the proposed method. Sensibility analysis and comprehensive comparisons with another two methods are performed to show the stability and advantage of our method.

     

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