Neutrality operations-based Pythagorean fuzzy aggregation operators and its applications to multiple attribute group decision-making process

2019 ◽  
Vol 11 (7) ◽  
pp. 3021-3041 ◽  
Author(s):  
Harish Garg
Keyword(s):  
Decision Making ◽  
Group Decision Making ◽  
Group Decision ◽  
Aggregation Operators ◽  
Decision Making Process ◽  
Multiple Attribute ◽  
Fuzzy Aggregation

Approaches Based on Interval Type-2 Fuzzy Aggregation Operators for Multiple Attribute Group Decision Making

2015 ◽  
Vol 18 (4) ◽  
pp. 697-715 ◽  
Author(s):  
Xiyuan Ma ◽  
Peng Wu ◽  
Ligang Zhou ◽  
Huayou Chen ◽  
Tong Zheng ◽  
...  
Keyword(s):  
Decision Making ◽  
Group Decision Making ◽  
Group Decision ◽  
Aggregation Operators ◽  
Multiple Attribute ◽  
Fuzzy Aggregation ◽  
Interval Type

scholarly journals Multi-attribute group decision-making process based on possibility degree and operators for intuitionistic multiplicative set

2021 ◽  
Author(s):  
Harish Garg
Keyword(s):  
Decision Making ◽  
Group Decision Making ◽  
Group Decision ◽  
Aggregation Operators ◽  
Decision Making Process ◽  
Uncertain Information ◽  
Connection Number ◽  
Possibility Degree ◽  
Multiple Attribute ◽  
The Given

AbstractThis paper aims to present a novel multiple attribute group decision-making process under the intuitionistic multiplicative preference set environment. In it, Saaty’s 1/9-9 scale is used to express the imprecise information which is asymmetrical distribution about 1. To achieve it, the present work is divided into three folds. First, a concept of connection number-based intuitionistic multiplicative set (CN-IMS) is formulated by considering three degrees namely “identity”, “contrary”, and “discrepancy” of the set and study their features. Second, to rank the given number, we define a novel possibility degree measure which compute the degree of possibility within the given objects. Finally, several aggregation operators on the pairs of the given numbers are designed and investigated their fundamental inequalities and relations. To explain the presented measures and operators, a group decision-making approach is promoted to solve the problems with uncertain information and illustrated with several examples. The advantages, comparative, as well as perfection analysis of the proposed framework are furnished to confirm the approach.

scholarly journals A New Ranking Methodology for Pythagorean Trapezoidal Uncertain Linguistic Fuzzy Sets Based on Einstein Operations

Symmetry ◽  
2019 ◽  
Vol 11 (3) ◽  
pp. 440 ◽  
Author(s):  
Arshad Khan ◽  
Saleem Abdullah ◽  
Muhammad Shakeel ◽  
Faisal Khan ◽  
Noor Amin ◽  
...  
Keyword(s):  
Decision Making ◽  
Group Decision ◽  
Aggregation Operators ◽  
Weighted Averaging ◽  
Decision Making Process ◽  
Ordered Weighted Averaging ◽  
Operational Laws ◽  
Multiple Attribute ◽  
Fuzzy Aggregation ◽  
Einstein Operations

In this article, we proposed new Pythagorean trapezoidal uncertain linguistic fuzzy aggregation information—namely, the Pythagorean trapezoidal uncertain linguistic fuzzy Einstein weighted averaging (PTULFEWA) operator, the Pythagorean trapezoidal uncertain linguistic fuzzy Einstein ordered weighted averaging (PTULFEOWA) operator, and the Pythagorean trapezoidal uncertain linguistic fuzzy Einstein hybrid weighted averaging (PTULFEHWA) operator—using the Einstein operational laws. We studied some important properties of the suggested aggregation operators and showed that the PTULFEHWA is more general than the other proposed operators, which simplifies these aggregation operators. Furthermore, we presented a multiple attribute group decision making (MADM) process for the proposed aggregation operators under the Pythagorean trapezoidal uncertain linguistic fuzzy (PTULF) environment. A numerical example was constructed to determine the effectiveness and practicality of the proposed approach. Lastly, a comparative analysis was performed of the presented approach with existing approaches to show that the proposed method is consistent and provides more information that may be useful for complex problems in the decision-making process.

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