scholarly journals A novel Picture fuzzy linguistic Muirhead Mean aggregation operators and their application to Multiple Attribute Decision Making

2021 ◽  
Author(s):  
Sidong Xian ◽  
Yue Cheng ◽  
Zhou Liu
Keyword(s):  
Decision Making ◽  
Intuitionistic Fuzzy Set ◽  
Score Function ◽  
Multiple Attribute Decision Making ◽  
Linguistic Context ◽  
Scale Functions ◽  
Operational Laws ◽  
Multiple Attribute ◽  
Fuzzy Linguistic ◽  
Selection Of

Abstract The Picture fuzzy linguistic set (PFLS) is an extension of intuitionistic fuzzy set (IFS) and linguistic variables (LVs), which has been applied successfully in the process of decision making. Considering the lack of closeness of extant PFLS operations and the interrelationship among input attributes do not considered. In this paper, for the sake of addressing those limitations, we firstly redefine some novel operational laws for PFLS by introducing linguistic scale functions and the related properties are studied. Then, new score function and accuracy function are also defined to compare PFLSs. Subsequently, in consideration of the superiority of Muirhead Mean (MM) operator in capturing the interaction relationship between the input parameters, we extend the MM operator to the picture fuzzy linguistic context, and then propose picture fuzzy linguistic weighted MM operator and its dual form in a new light. After that, we have adopted these operators to build two novel models to solve multiple attribute decision making (MADM) problems. Finally, a practical example for the selection of the innovative ``Mobike'' sharing bike design is provided to illustrate the practicality and effectiveness of our developed approaches.

scholarly journals Dual Generalized Nonnegative Normal Neutrosophic Bonferroni Mean Operators and Their Application in Multiple Attribute Decision Making

Information ◽  
2018 ◽  
Vol 9 (8) ◽  
pp. 201 ◽  
Author(s):  
Jiongmei Mo ◽  
Han-Liang Huang
Keyword(s):  
Decision Making ◽  
Score Function ◽  
Information Aggregation ◽  
Multiple Attribute Decision Making ◽  
Ranking Method ◽  
Bonferroni Mean ◽  
Operational Laws ◽  
Multiple Attribute ◽  
Geometric Bonferroni Mean ◽  
Neutrosophic Number

For multiple attribute decision making, ranking and information aggregation problems are increasingly receiving attention. In a normal neutrosophic number, the ranking method does not satisfy the ranking principle. Moreover, the proposed operators do not take into account the correlation between any aggregation arguments. In order to overcome the deficiencies of the existing ranking method, based on the nonnegative normal neutrosophic number, this paper redefines the score function, the accuracy function, and partial operational laws. Considering the correlation between any aggregation arguments, the dual generalized nonnegative normal neutrosophic weighted Bonferroni mean operator and dual generalized nonnegative normal neutrosophic weighted geometric Bonferroni mean operator were investigated, and their properties are presented. Here, these two operators are applied to deal with a multiple attribute decision making problem. Example results show that the proposed method is effective and superior.

scholarly journals AN APPROACH TO MULTIPLE ATTRIBUTE DECISION MAKING BASED ON THE INDUCED CHOQUET INTEGRAL WITH FUZZY NUMBER INTUITIONISTIC FUZZY INFORMATION

2014 ◽  
Vol 15 (2) ◽  
pp. 277-298 ◽  
Author(s):  
Guiwu Wei ◽  
Rui Lin ◽  
Xiaofei Zhao ◽  
Hongjun Wang
Keyword(s):  
Decision Making ◽  
Fuzzy Number ◽  
Choquet Integral ◽  
Score Function ◽  
Multiple Attribute Decision Making ◽  
Aggregation Operators ◽  
Fuzzy Information ◽  
Intuitionistic Fuzzy ◽  
Operational Laws ◽  
Multiple Attribute

In this paper, we investigate the multiple attribute decision making problems with fuzzy number intuitionistic fuzzy information. Firstly, some operational laws of fuzzy number intuitionistic fuzzy values, score function and accuracy function of fuzzy number intuitionistic fuzzy values are introduced. Then, we have developed two fuzzy number intuitionistic fuzzy Choquet integral aggregation operators: induced fuzzy number intuitionistic fuzzy choquet ordered averaging (IFNIFCOA) operator and induced fuzzy number intuitionistic fuzzy choquet ordered geometric (IFNIFCOG) operator. The prominent characteristic of the operators is that they can not only consider the importance of the elements or their ordered positions, but also reflect the correlation among the elements or their ordered positions. We have studied some desirable properties of the IFNIFCOA and IFNIFCOG operators, such as commutativity, idempotency and monotonicity, and applied the IFNIFCOA and IFNIFCOGM operators to multiple attribute decision making with fuzzy number intuitionistic fuzzy information. Finally an illustrative example has been given to show the developed method.

scholarly journals CHOQUET INTEGRALS OF WEIGHTED TRIANGULAR FUZZY LINGUISTIC INFORMATION AND THEIR APPLICATIONS TO MULTIPLE ATTRIBUTE DECISION MAKING

2014 ◽  
Vol 15 (5) ◽  
pp. 795-809 ◽  
Author(s):  
Rui Lin ◽  
Guiwu Wei ◽  
Hongjun Wang ◽  
Xiaofei Zhao
Keyword(s):  
Decision Making ◽  
Choquet Integral ◽  
Multiple Attribute Decision Making ◽  
Linguistic Information ◽  
Averaging Operator ◽  
Operational Laws ◽  
Multiple Attribute ◽  
Choquet Integrals ◽  
Geometric Operator ◽  
Fuzzy Linguistic

We investigate the multiple attribute decision making problems in which attribute values take the form of triangular fuzzy linguistic information. Firstly, the definition and some operational laws of triangular fuzzy linguistic are introduced. Then, we have developed three fuzzy linguistic Choquet integral aggregation operators: fuzzy linguistic choquet ordered averaging operator, fuzzy linguistic choquet ordered geometric operator and fuzzy linguistic choquet ordered harmonic mean operator. The prominent characteristic of the operators is that they cannot only consider the importance of the elements or their ordered positions, but also reflect the correlation among the elements or their ordered positions. We have studied some desirable properties of these operators, such as commutativity, idempotency and monotonicity, and applied these operators to multiple attribute decision making with triangular fuzzy linguistic information. Finally an illustrative example has been given to show the developed method.

scholarly journals Fuzzy Linguistic Induced Ordered Weighted Averaging Operator and Its Application

2012 ◽  
Vol 2012 ◽  
pp. 1-10 ◽  
Author(s):  
Sidong Xian
Keyword(s):  
Decision Making ◽  
Group Decision Making ◽  
Group Decision ◽  
Weighted Averaging ◽  
Attribute Weights ◽  
Operational Laws ◽  
Multiple Attribute ◽  
Ordered Weighted Averaging Operator ◽  
Fuzzy Linguistic ◽  
Magdm Problems

With respect to multiple attribute group decision making (MAGDM) problems, in which the attribute weights take the form of real numbers, and the attribute values take the form of fuzzy linguistic scale variables, a decision analysis approach is proposed. In this paper, we develop a new fuzzy linguistic induce OWA (FLIOWA) operator and analyze the properties of it by utilizing some operational laws of fuzzy linguistic scale variables. A method based on the FLIOWA operators for multiple attribute group decision making is presented. Finally, a numerical example is used to illustrate the applicability and effectiveness of the proposed method.

Material Selection Using a Novel Multiple Attribute Decision Making Method

2012 ◽  
pp. 252-266
Author(s):  
R. V. Rao ◽  
B. K. Patel
Keyword(s):  
Decision Making ◽  
Fuzzy Logic ◽  
Decision Maker ◽  
Design Process ◽  
Material Selection ◽  
Multiple Attribute Decision Making ◽  
Decision Makers ◽  
Selection Problem ◽  
Multiple Attribute ◽  
Selection Of

Selection of a most appropriate material is a very important task in design process of every product. There is a need for simple, systematic, and logical methods or mathematical tools to guide decision makers in considering a number of selection attributes and their interrelations and in making right decisions. This paper proposes a novel multiple attribute decision making (MADM) method for solving the material selection problem. The method considers the objective weights of importance of the attributes as well as the subjective preferences of the decision maker to decide the integrated weights of importance of the attributes. Furthermore, the method uses fuzzy logic to convert the qualitative attributes into the quantitative attributes. Two examples are presented to illustrate the potential of the proposed method.

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