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Volume 7 Issue 2
Mar.  2020

IEEE/CAA Journal of Automatica Sinica

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Article Navigation >  IEEE/CAA Journal of Automatica Sinica  > 2020  >  7(2): 546-558
Harish Garg and Nancy, "Linguistic Single-Valued Neutrosophic Power Aggregation Operators and Their Applications to Group Decision-Making Problems," IEEE/CAA J. Autom. Sinica, vol. 7, no. 2, pp. 546-558, Mar. 2020. doi: 10.1109/JAS.2019.1911522
Citation: Harish Garg and Nancy, "Linguistic Single-Valued Neutrosophic Power Aggregation Operators and Their Applications to Group Decision-Making Problems," IEEE/CAA J. Autom. Sinica, vol. 7, no. 2, pp. 546-558, Mar. 2020. doi: 10.1109/JAS.2019.1911522
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Linguistic Single-Valued Neutrosophic Power Aggregation Operators and Their Applications to Group Decision-Making Problems

doi: 10.1109/JAS.2019.1911522
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    Abstract
  • Linguistic single-valued neutrosophic set (LSVNS) is a more reliable tool, which is designed to handle the uncertainties of the situations involving the qualitative data. In the present manuscript, we introduce some power aggregation operators (AOs) for the LSVNSs, whose purpose is to diminish the influence of inevitable arguments about the decision-making process. For it, first we develop some averaging power operators, namely, linguistic single-valued neutrosophic (LSVN) power averaging, weighted average, ordered weighted average, and hybrid averaging AOs along with their desirable properties. Further, we extend it to the geometric power AOs for LSVNSs. Based on the proposed work; an approach to solve the group decision-making problems is given along with the numerical example. Finally, a comparative study and the validity tests are present to discuss the reliability of the proposed operators.

     

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    Highlights

    • A concept of linguistic single-valued neutrosophic set is utilized to handle the uncertainties.
    • Power aggregation operators are proposed to aggregate the information.
    • Group decision making approach is presented to solve the decision-making problems.
    • The effectiveness and feasibility of algorithm are demonstrated by a numerical example.
    • A systematic comparison between the proposed approach results and the other papers results is made.

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