INTERVAL-VALUED DUAL HESITANT FUZZY INFORMATION AGGREGATION AND ITS APPLICATION IN MULTIPLE ATTRIBUTE DECISION MAKING

2018 ◽  
Vol 8 (4) ◽  
pp. 361-382 ◽  
Author(s):  
Xindong Peng ◽  
Jingguo Dai ◽  
Lin Liu
Keyword(s):  
Decision Making ◽  
Information Aggregation ◽  
Multiple Attribute Decision Making ◽  
Fuzzy Information ◽  
Multiple Attribute ◽  
Interval Valued

scholarly journals Hesitant Triangular Fuzzy Information Aggregation Operators Based on Bonferroni Means and Their Application to Multiple Attribute Decision Making

2014 ◽  
Vol 2014 ◽  
pp. 1-15 ◽  
Author(s):  
Chunyong Wang ◽  
Qingguo Li ◽  
Xiaoqiang Zhou ◽  
Tian Yang
Keyword(s):  
Decision Making ◽  
Information Aggregation ◽  
Multiple Attribute Decision Making ◽  
Aggregation Operators ◽  
Fuzzy Information ◽  
Fuzzy Environment ◽  
Operational Laws ◽  
Multiple Attribute ◽  
Special Cases ◽  
Fuzzy Aggregation

We investigate the multiple attribute decision-making (MADM) problems with hesitant triangular fuzzy information. Firstly, definition and some operational laws of hesitant triangular fuzzy elements are introduced. Then, we develop some hesitant triangular fuzzy aggregation operators based on Bonferroni means and discuss their basic properties. Some existing operators can be viewed as their special cases. Next, we apply the proposed operators to deal with multiple attribute decision-making problems under hesitant triangular fuzzy environment. Finally, an illustrative example is given to show the developed method and demonstrate its practicality and effectiveness.

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.

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