scholarly journals Multiple Attribute Decision Making With Interval-Valued Bipolar Fuzzy Information and Their Application to Emerging Technology Commercialization Evaluation

IEEE Access ◽  
2018 ◽  
Vol 6 ◽  
pp. 60930-60955 ◽  
Author(s):  
Guiwu Wei ◽  
Cun Wei ◽  
Hui Gao
Keyword(s):  
Decision Making ◽  
Multiple Attribute Decision Making ◽  
Emerging Technology ◽  
Technology Commercialization ◽  
Fuzzy Information ◽  
Multiple Attribute ◽  
Interval Valued

SOME CONTINUOUS AGGREGATION OPERATORS WITH INTERVAL-VALUED INTUITIONISTIC FUZZY INFORMATION AND THEIR APPLICATION TO DECISION MAKING

2012 ◽  
Vol 20 (02) ◽  
pp. 185-209 ◽  
Author(s):  
JIAN LIN ◽  
QIANG ZHANG
Keyword(s):  
Decision Making ◽  
Fuzzy Numbers ◽  
Multiple Attribute Decision Making ◽  
Aggregation Operators ◽  
Fuzzy Information ◽  
Numerical Examples ◽  
Intuitionistic Fuzzy Numbers ◽  
Intuitionistic Fuzzy ◽  
Multiple Attribute ◽  
Interval Valued

In this paper, some new operators for aggregating interval-valued intuitionistic fuzzy information are proposed to deal with multiple attribute decision making problems. Firstly, the C-IFOWA operator and C-IFOWG operator are developed to aggregate all the values in the interval-valued intuitionistic fuzzy numbers. Some of their desirable properties are also studied. Secondly, in order to aggregate a set of interval-valued intuitionistic fuzzy numbers, some new aggregation operators are proposed based on the C-IFOWA operator and C-IFOWG operator. Thirdly, two methods for multiple attribute decision making, in which the attribute values are given in the forms of interval-valued intuitionistic fuzzy numbers are presented. Finally, two numerical examples are provided to illustrate the practicality and validity of the proposed methods.

A Method for Interval-Valued Hesitant Fuzzy Multiple Attribute Decision Making and Their Application to Wireless Sensor Network Route Security Evaluation

2016 ◽  
Vol 13 (10) ◽  
pp. 7110-7114
Author(s):  
Wei Fu ◽  
Ying-Mei Li ◽  
Ming-Yu Liu
Keyword(s):  
Decision Making ◽  
Wireless Sensor Network ◽  
Sensor Network ◽  
Multiple Attribute Decision Making ◽  
Wireless Sensor ◽  
Security Evaluation ◽  
Fuzzy Information ◽  
Multiple Attribute ◽  
Electre Method ◽  
Interval Valued

Wireless sensor network, as an integrated network which can perform information gathering, processing and delivering, can connect the real world and logistic information world. It is greatly changing the interaction between people and nature. There are wide potential applications for wireless sensor network, such as industry, agriculture, military affairs, environment monitoring, biomedicine, city managing and disaster succoring. The problem of evaluating the security of wireless sensor network route with interval-valued hesitant fuzzy information is the multiple attribute decision making. In this paper, we extend the ELECTRE method to take into account interval-valued hesitant fuzzy information and propose the ELECTRE method to solve the multiple attribute decision making problems. Finally, a practical example for evaluating the wireless sensor network route security is given to verify the developed approach and to demonstrate its practicality and effectiveness.

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.

scholarly journals Methods for Multiple Attribute Decision Making with Interval-Valued Pythagorean Fuzzy Information

Mathematics ◽  
2018 ◽  
Vol 6 (11) ◽  
pp. 228 ◽  
Author(s):  
Zengxian Li ◽  
Guiwu Wei ◽  
Hui Gao
Keyword(s):  
Decision Making ◽  
Fuzzy Numbers ◽  
Multiple Attribute Decision Making ◽  
Fuzzy Information ◽  
Good Tool ◽  
New Methods ◽  
Multiple Attribute ◽  
Pythagorean Fuzzy Numbers ◽  
Interval Valued

Interval-valued Pythagorean fuzzy numbers (IVPFNs) can easily describe the incomplete and indeterminate information by degrees of membership and non-membership, and the Hamy mean (HM) operator and dual HM (DHM) operators are a good tool for dealing with multiple attribute decision making (MADM) problems because it can capture the interrelationship among the multi-input arguments. Motivated by the studies regarding the HM operator and dual HM operator, we expand the HM operator and dual HM (DMM) operator to process the interval-valued Pythagorean fuzzy numbers (IVPFNs) and then to solve the MADM problems. Firstly, we propose some HM and DHM operators with IVPFNs. Moreover, we present some new methods to solve MADM problems with the IVPFNs. Finally, an applicable example is given.

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