Intuitionistic Fuzzy Aggregation Operators and Multiattribute Decision-Making Methods with Intuitionistic Fuzzy Sets

2013 ◽  
pp. 47-73 ◽  
Author(s):  
Deng-Feng Li
Keyword(s):  
Decision Making ◽  
Fuzzy Sets ◽  
Intuitionistic Fuzzy Sets ◽  
Aggregation Operators ◽  
Intuitionistic Fuzzy ◽  
Fuzzy Aggregation

scholarly journals Linguistic Intuitionistic Fuzzy Sets and Application in MAGDM

2014 ◽  
Vol 2014 ◽  
pp. 1-11 ◽  
Author(s):  
Huimin Zhang
Keyword(s):  
Decision Making ◽  
Fuzzy Sets ◽  
Score Function ◽  
Intuitionistic Fuzzy Sets ◽  
Aggregation Operators ◽  
Uncertain Information ◽  
Intuitionistic Fuzzy ◽  
Multiple Attribute ◽  
Fuzzy Aggregation ◽  
Linguistic Intuitionistic Fuzzy Sets

To better deal with imprecise and uncertain information in decision making, the definition of linguistic intuitionistic fuzzy sets (LIFSs) is introduced, which is characterized by a linguistic membership degree and a linguistic nonmembership degree, respectively. To compare any two linguistic intuitionistic fuzzy values (LIFVs), the score function and accuracy function are defined. Then, based ont-norm andt-conorm, several aggregation operators are proposed to aggregate linguistic intuitionistic fuzzy information, which avoid the limitations in exiting linguistic operation. In addition, the desired properties of these linguistic intuitionistic fuzzy aggregation operators are discussed. Finally, a numerical example is provided to illustrate the efficiency of the proposed method in multiple attribute group decision making (MAGDM).

New Einstein Hybrid Aggregation Operators for Intuitionistic Fuzzy Sets and Applications in Multi-Criteria Decision-Making

2019 ◽  
pp. 252-283
Author(s):  
Bhagawati Prasad Joshi ◽  
Abhay Kumar
Keyword(s):  
Decision Making ◽  
Fuzzy Sets ◽  
Decision Maker ◽  
Intuitionistic Fuzzy Sets ◽  
Aggregation Operators ◽  
Weighted Averaging ◽  
Multi Criteria Decision Making ◽  
Intuitionistic Fuzzy ◽  
Fuzzy Environment ◽  
Decision Making Processes

The fusion of multidimensional intuitionistic fuzzy information plays an important part in decision making processes under an intuitionistic fuzzy environment. In this chapter, it is observed that existing intuitionistic fuzzy Einstein hybrid aggregation operators do not follow the idempotency and boundedness. This leads to sometimes illogical and even absurd results to the decision maker. Hence, some new intuitionistic fuzzy Einstein hybrid aggregation operators such as the new intuitionistic fuzzy Einstein hybrid weighted averaging (IFEHWA) and the new intuitionistic fuzzy Einstein hybrid weighted geometric (IFEHWG) were developed. The new IFEHWA and IFEHWG operators can weigh the arguments as well as their ordered positions the same as the intuitionistic fuzzy Einstein hybrid aggregation operators do. Further, it is validated that the defined operators are idempotent, bounded, monotonic and commutative. Then, based on the developed approach, a multi-criteria decision-making (MCDM) procedure is given. Finally, a numerical example is conducted to demonstrate the proposed method effectively.

Additive Intuitionistic Fuzzy Aggregation Operators Based on Fuzzy Measure

2016 ◽  
Vol 24 (01) ◽  
pp. 1-12 ◽  
Author(s):  
Zeshui Xu
Keyword(s):  
Decision Making ◽  
Probability Measure ◽  
Choquet Integral ◽  
Intuitionistic Fuzzy Sets ◽  
Aggregation Operators ◽  
Fuzzy Measure ◽  
Intuitionistic Fuzzy ◽  
Fuzzy Aggregation ◽  
The World ◽  
Multi Attribute Decision Making

Intuitionistic fuzzy sets can describe the uncertainty and complexity of the world flexibly, so it has been widely used in multi-attribute decision making. Traditional intuitionistic fuzzy aggregation operators are usually based on the probability measure, namely, they consider that the attributes of objects are independent. But in actual situations, it is difficult to ensure the independence of attributes, so these operators are unsuitable in such situations. Fuzzy measure is able to depict the relationships among the attributes more comprehensively, so it can complement the traditional probability measure in dealing with the multi-attribute decision making problems. In this paper, we first analyze the existing intuitionistic fuzzy operators based on fuzzy measure, then introduce two novel additive intuitionistic fuzzy aggregation operators based on the Shapley value and the Choquet integral, respectively, and show their advantages over other ones.

Sustainable energy selection based on interval-valued intuitionistic fuzzy and neutrosophic aggregation operators

2020 ◽  
Vol 39 (5) ◽  
pp. 6553-6563
Author(s):  
Eda Bolturk ◽  
Murat Gülbay ◽  
Cengiz Kahraman
Keyword(s):  
Decision Making ◽  
Fuzzy Sets ◽  
Sustainable Energy ◽  
Aggregation Operators ◽  
Solution Technique ◽  
Multi Criteria Decision Making ◽  
Selection Problems ◽  
Intuitionistic Fuzzy ◽  
Fuzzy Aggregation ◽  
Interval Valued

Sustainable energy selection has been a very popular problem among the researchers and various models including deterministic, probabilistic and fuzzy approaches have been developed for the solution of this problem. Fuzzy approaches to sustainable energy selection problems have been often handled in the literature. Aggregation operators for multi-expert decision making problems are an alternative solution technique for multi criteria decision making problems. Since neutrosophic and intuitionistic fuzzy aggregation operators are comparable extensions of ordinary fuzzy sets, they have been employed to aggregate multi-expert judgments. An illustrative energy selection problem is presented, solved by two approaches, and results are compared. The same linguistic data have been used for the comparison purpose.

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