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 A New Fuzzy Multiple Attribute Decision Making Method Based on the Utility Transformation Functions

Symmetry ◽  
2019 ◽  
Vol 11 (3) ◽  
pp. 418
Author(s):  
Yuting Zuo ◽  
Chunfang Chen
Keyword(s):  
Decision Making ◽  
Utility Theory ◽  
Weighted Average ◽  
Multiple Attribute Decision Making ◽  
Decision Makers ◽  
Linguistic Information ◽  
Operational Laws ◽  
Multiple Attribute ◽  
Transformation Functions ◽  
The Difference

The 2-tuple linguistic information model (2TLIM) is a useful tool to avoid the loss of information, which has been widely adapted in the study of the multiple attribute decision making (MADM) problem. However, there is a limitation, the limitation is that the difference between the neighboring 2-tuple linguistic information is fixed regardless of the decision-makers’ attitude. In this paper, we define the utility transformation functions based on the 2-tuple linguistic utility to overcome the drawback. Firstly, by introducing the economic utility theory, the 2-tuple linguistic utility is defined, the 2-tuple linguistic utility parameter (2TLUP) and the 2-tuple linguistic marginal utility (2TLMU) are constructed to achieve the measurement of the decision-makers’ attitude. The utility transformation functions are developed on the decision-makers’ attitude. Secondly, the 2-tuple linguistic operational laws are presented with the extended Hamacher T-norm (TN) and T-conorm (TC). Subsequently, we propose the 2-tuple linguistic utility weighted average (2TLUWA) operator and the method of MADM. Lastly, the application and the comparison with the existing methods are summarized to verify the practicality and advantages of the proposed method of MADM.

scholarly journals Multiple Attribute Decision Making Based on Hesitant Fuzzy Einstein Geometric Aggregation Operators

2014 ◽  
Vol 2014 ◽  
pp. 1-14 ◽  
Author(s):  
Xiaoqiang Zhou ◽  
Qingguo Li
Keyword(s):  
Decision Making ◽  
Multiple Attribute Decision Making ◽  
Aggregation Operators ◽  
Fuzzy Decision Making ◽  
Fuzzy Decision ◽  
Fuzzy Information ◽  
Operational Laws ◽  
Multiple Attribute ◽  
Fuzzy Aggregation ◽  
Geometric Operator

We first define an accuracy function of hesitant fuzzy elements (HFEs) and develop a new method to compare two HFEs. Then, based on Einstein operators, we give some new operational laws on HFEs and some desirable properties of these operations. We also develop several new hesitant fuzzy aggregation operators, including the hesitant fuzzy Einstein weighted geometric (HFEWGε) operator and the hesitant fuzzy Einstein ordered weighted geometric (HFEWGε) operator, which are the extensions of the weighted geometric operator and the ordered weighted geometric (OWG) operator with hesitant fuzzy information, respectively. Furthermore, we establish the connections between the proposed and the existing hesitant fuzzy aggregation operators and discuss various properties of the proposed operators. Finally, we apply the HFEWGεoperator to solve the hesitant fuzzy decision making problems.

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.

INDUCED CHOQUET INTEGRALS OF 2-TUPLE LINGUISTIC INFORMATION

2013 ◽  
Vol 21 (02) ◽  
pp. 175-200 ◽  
Author(s):  
WEI YANG
Keyword(s):  
Decision Making ◽  
Group Decision ◽  
Choquet Integral ◽  
Multiple Attribute Decision Making ◽  
Decision Makers ◽  
Multiple Attribute ◽  
Decision Making Problem ◽  
Choquet Integrals ◽  
Supplier Selection Problem ◽  
Associated Variables

The group decision making problem with inter-dependent or interactive attributes is studied. By using the Choquet integral and the inducing variables, we develop the induced 2-tuple correlated averaging (ITCA) operator, the generalized induced 2-tuple correlated averaging (GITCA) operator and the quasi-arithmetic induced 2-tuple correlated averaging (QITCA) operator. The characteristics of the proposed operators are that the evaluation values of decision makers are in linguistic arguments, the correlations among the elements can be reflected and the ordering of the arguments is based on other associated variables instead of their own values. The properties of these operators are studied and new multiple attribute decision making method based on the new operators is proposed. Finally, architecture material supplier selection problem is provided to illustrate the feasibility and efficiency of the proposed method.

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.

Multiple Attribute Group Decision-Making Methods Under Hesitant Fuzzy Linguistic Environment

2017 ◽  
Vol 26 (2) ◽  
pp. 387-406 ◽  
Author(s):  
Xiaodi Liu ◽  
Jianjun Zhu ◽  
Shitao Zhang ◽  
Guodong Liu
Keyword(s):  
Decision Making ◽  
Group Decision Making ◽  
Group Decision ◽  
Aggregation Operators ◽  
Linguistic Information ◽  
Weighted Arithmetic ◽  
Averaging Operator ◽  
Multiple Attribute ◽  
Arithmetic Averaging Operator ◽  
Fuzzy Linguistic

AbstractThe aim of this paper is to develop some aggregation operators for multiple-attribute group decision making (MAGDM) with hesitant fuzzy linguistic information. First, the relationship between uncertain linguistic variable and hesitant fuzzy linguistic term set (HFLTS) is discussed. Some operations and aggregation operators for HFLTSs are developed. Second, based on the hesitant fuzzy linguistic weighted arithmetic averaging operator and the hesitant fuzzy linguistic hybrid averaging operator, an approach to MAGDM problem with hesitant fuzzy linguistic information is proposed. Finally, a practical application of the developed approach to supplier selection in a supply chain and a comparative analysis with other methods are presented.

AN APPROACH TO PURE LINGUISTIC MULTIPLE ATTRIBUTE DECISION MAKING UNDER UNCERTAINTY

2005 ◽  
Vol 04 (02) ◽  
pp. 197-206 ◽  
Author(s):  
ZESHUI XU
Keyword(s):  
Decision Making ◽  
Multiple Attribute Decision Making ◽  
Aggregation Operator ◽  
Aggregation Operators ◽  
Decision Making Under Uncertainty ◽  
Linguistic Variables ◽  
Linguistic Information ◽  
Attribute Weights ◽  
Operational Laws ◽  
Multiple Attribute

The pure linguistic multiple attribute decision making problems are studied, in which the information about the attribute weights are expressed in the form of linguistic variables or uncertain linguistic variables, and the attribute values take the form of uncertain linguistic variables. The operational laws of uncertain linguistic variables are introduced, and two uncertain linguistic aggregation operators called linguistic weighted aggregation operator and uncertain linguistic weighted aggregation operator are developed based on uncertain linguistic variables and their operational laws. An approach based on the developed operators for pure linguistic multiple attribute decision making under uncertainty is proposed. The prominent characteristic of the proposed approach is that it can compute with uncertain linguistic information directly. Furthermore, the approach is straightforward and does not produce any loss of information. Finally, an illustrative example is given.

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