Single Valued Neutrosophic Trapezoid Linguistic Aggregation Operators Based Multi-attribute Decision Making

نویسندگان

  • Said Broumi
  • Florentin Smarandache
چکیده

Multi-attribute decision making (MADM). Play an important role in many applications, due to the efficiency to handle indeterminate and inconsistent information, single valued neutrosophic sets is widely used to model indeterminate information. In this paper, a new MADM method based on neutrosophic trapezoid linguistic weighted arithmetic averaging aggregation SVNTrLWAA operator and neutrosophic trapezoid linguistic weighted geometric aggregation SVNTrLWGA operator is presented. A numerical example is presented to demonstrate the application and efficiency of the proposed method.

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تاریخ انتشار 2014