scholarly journals Interval-Valued Pythagorean Fuzzy Maclaurin Symmetric Mean Operators in Multiple Attribute Decision Making

IEEE Access ◽  
2018 ◽  
Vol 6 ◽  
pp. 67866-67884 ◽  
Author(s):  
Guiwu Wei ◽  
Harish Garg ◽  
Hui Gao ◽  
Cun Wei
Keyword(s):  
Decision Making ◽  
Multiple Attribute Decision Making ◽  
Maclaurin Symmetric Mean ◽  
Multiple Attribute ◽  
Interval Valued

scholarly journals Approaches to Multiple Attribute Decision Making with Interval-Valued 2-Tuple Linguistic Pythagorean Fuzzy Information

Mathematics ◽  
2018 ◽  
Vol 6 (10) ◽  
pp. 201 ◽  
Author(s):  
Jie Wang ◽  
Guiwu Wei ◽  
Hui Gao
Keyword(s):  
Decision Making ◽  
Multiple Attribute Decision Making ◽  
Fuzzy Information ◽  
Maclaurin Symmetric Mean ◽  
Operator Interval ◽  
Multiple Attribute ◽  
Fusion Theory ◽  
Pythagorean Fuzzy Numbers ◽  
Interval Valued ◽  
The Ideal

The Maclaurin symmetric mean (MSM) operator is a classical mean type aggregation operator used in modern information fusion theory, which is suitable to aggregate numerical values. The prominent characteristic of the MSM operator is that it can capture the interrelationship among multi-input arguments. Motivated by the ideal characteristic of the MSM operator, in this paper, we expand the MSM operator, generalized MSM (GMSM), and dual MSM (DMSM) operator with interval-valued 2-tuple linguistic Pythagorean fuzzy numbers (IV2TLPFNs) to propose the interval-valued 2-tuple linguistic Pythagorean fuzzy MSM (IV2TLPFMSM) operator, interval-valued 2-tuple linguistic Pythagorean fuzzy weighted MSM (IV2TLPFWMSM) operator, interval-valued 2-tuple linguistic Pythagorean fuzzy GMSM (IN2TLPFGMSM) operator, interval-valued 2-tuple linguistic Pythagorean fuzzy weighted GMSM (IV2TLPFWGMSM) operator, interval-valued 2-tuple linguistic Pythagorean fuzzy DMSM (IN2TLPFDMSM) operator, Interval-valued 2-tuple linguistic Pythagorean fuzzy weighted DMSM (IV2TLPFWDMSM) operator. Then the multiple attribute decision making (MADM) methods are developed with these three operators. Finally, an example of green supplier selection is used to show the proposed methods.

An Approach to Interval-Valued Intuitionistic Fuzzy Multiple Attribute Decision Making Based on the MSM Operator and Their Applications to Online Advertising Publisher Evaluation

2016 ◽  
Vol 13 (10) ◽  
pp. 7280-7284 ◽  
Author(s):  
Xiaoli Liang
Keyword(s):  
Decision Making ◽  
Online Advertising ◽  
Multiple Attribute Decision Making ◽  
Fuzzy Decision Making ◽  
Intuitionistic Fuzzy ◽  
Fuzzy Environment ◽  
Maclaurin Symmetric Mean ◽  
Multiple Attribute ◽  
Special Cases ◽  
Interval Valued

The Maclaurin symmetric mean (MSM) was originally introduced by Maclaurin. The prominent characteristic of the MSM is that it can capture the interrelationship among the multi-input arguments. However, the researches on MSM are very rare, especially in fuzzy decision making. In this paper, we investigate the MSM operator and extend the MSM operator to interval-valued intuitionistic fuzzy environment and develop the interval-valued intuitionistic fuzzy Maclaurin symmetric mean (IVIFMSM) operator. Some desirable properties and special cases of IVIFMSM operator are discussed in detail. Based on IVIFMSM operator, an approach to multiple attribute decision making problems with interval-valued intuitionistic fuzzy information is developed. Finally, an illustrative example for online advertising publisher evaluation is given to verify the developed approach and to demonstrate its practicality and effectiveness.

Multiple Attribute Decision-Making Methods with Unbalanced Linguistic Variables Based on Maclaurin Symmetric Mean Operators

2019 ◽  
Vol 18 (01) ◽  
pp. 105-146 ◽  
Author(s):  
Fei Teng ◽  
Peide Liu ◽  
Li Zhang ◽  
Juan Zhao
Keyword(s):  
Decision Making ◽  
Multiple Attribute Decision Making ◽  
Aggregation Operators ◽  
Linguistic Variables ◽  
Numerical Example ◽  
Maclaurin Symmetric Mean ◽  
Multiple Attribute ◽  
Linguistic Term

In this paper, we firstly introduced the unbalanced linguistic term sets, the linguistic transforming methodology, the Maclaurin symmetric mean (MSM) operator and dual MSM (DMSM) operator. Then, we proposed the closed operational rules of unbalanced linguistic variables, and several new MSM aggregation operators, including unbalanced linguistic MSM (ULMSM) operator, weighted unbalanced linguistic MSM (WULMSM) operator, unbalanced linguistic DMSM (ULDMSM) operator and weighted unbalanced linguistic DMSM (WULDMSM) operator. Further, we proposed two multiple attribute decision-making (MADM) methods under unbalanced linguistic environments based on the WULMSM operator and WULDMSM operator, respectively. Finally, a numerical example is used to show the applicability and effectiveness of the proposed MADM methods and to reveal their advantages by comparing with the existing methods.

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