An Interactive Approach to Multiple Attribute Group Decision Making with Multigranular Uncertain Linguistic Information

2008 ◽  
Vol 18 (2) ◽  
pp. 119-145 ◽  
Author(s):  
Zeshui Xu
Keyword(s):  
Decision Making ◽  
Group Decision Making ◽  
Group Decision ◽  
Interactive Approach ◽  
Linguistic Information ◽  
Multiple Attribute

scholarly journals Triangular Cubic Hesitant Fuzzy Einstein Hybrid Weighted Averaging Operator and Its Application to Decision Making

Symmetry ◽  
2018 ◽  
Vol 10 (11) ◽  
pp. 658 ◽  
Author(s):  
Aliya Fahmi ◽  
Fazli Amin ◽  
Florentin Smarandache ◽  
Madad Khan ◽  
Nasruddin Hassan
Keyword(s):  
Decision Making ◽  
Group Decision Making ◽  
Group Decision ◽  
Aggregation Operators ◽  
Weighted Averaging ◽  
Linguistic Information ◽  
Ordered Weighted Averaging ◽  
Averaging Operator ◽  
Multiple Attribute ◽  
The Relationship

In this paper, triangular cubic hesitant fuzzy Einstein weighted averaging (TCHFEWA) operator, triangular cubic hesitant fuzzy Einstein ordered weighted averaging (TCHFEOWA) operator and triangular cubic hesitant fuzzy Einstein hybrid weighted averaging (TCHFEHWA) operator are proposed. An approach to multiple attribute group decision making with linguistic information is developed based on the TCHFEWA and the TCHFEHWA operators. Furthermore, we establish various properties of these operators and derive the relationship between the proposed operators and the existing aggregation operators. Finally, a numerical example is provided to demonstrate the application of the established approach.

Research on Evaluating Theory and Application to Design of Mechanism Scheme with Uncertain Linguistic Information

2012 ◽  
Vol 201-202 ◽  
pp. 749-752
Author(s):  
Tie Jun Wang ◽  
Chang Zhong Hao
Keyword(s):  
Decision Making ◽  
Group Decision Making ◽  
Group Decision ◽  
Primary Phase ◽  
Harmonic Mean ◽  
Linguistic Variables ◽  
Product Lifecycle ◽  
Linguistic Information ◽  
Multiple Attribute ◽  
Magdm Problems

The design of mechanism scheme is the primary phase and the creative and challenging part in product lifecycle. In this paper, we research the multiple attribute group decision making (MAGDM) problems for evaluating the design of mechanism scheme with uncertain linguistic variables. We employ the uncertain linguistic weighted harmonic mean (ULWHM) operator to aggregate the uncertain linguistic information corresponding to each alternative and get the overall value of the alternatives, then rank the alternatives and select the most desirable one(s) by using the formula of the degree of possibility for the comparison between two uncertain linguistic variables. Finally, a practical example for evaluating the design of mechanism scheme is used to illustrate the developed procedures.

QUALIFLEX method for MAGDM with probabilistic uncertain linguistic information and its application to green supplier selection

2020 ◽  
Vol 39 (5) ◽  
pp. 6819-6831
Author(s):  
Fan Lei ◽  
Guiwu Wei ◽  
Jiang Wu ◽  
Cun Wei ◽  
Yanfeng Guo
Keyword(s):  
Decision Making ◽  
Group Decision Making ◽  
Supplier Selection ◽  
Group Decision ◽  
Linguistic Information ◽  
Suitable Alternative ◽  
Green Supplier Selection ◽  
Multiple Attribute ◽  
Selection Of

Probabilistic uncertain linguistic sets (PULTSs) have extensively been employed in multiple attribute group decision making (MAGDM)problem. The QUALIFLEX method, which is relatively a novel MAGDM technique, aims to obtain the optimal alternative. This paper proposes the probabilistic uncertain linguistic QUALIFLEX (PUL-QUALIFLEX) method with CRITIC method. To show the effectiveness of the designed method, an application is given for green supplier selection and the derived results are compared with some existing methods. Thus, the advantage of this proposed method is that it is simple to understand and easy to compute. The proposed method can also contribute to the selection of suitable alternative successfully in other selection issues.

Approaches to Multiple Attribute Group Decision Making Based on the DTOWHA Operator with 2-Tuple Linguistic Information

2016 ◽  
Vol 13 (10) ◽  
pp. 7314-7318
Author(s):  
Yan-Mei Wang
Keyword(s):  
Higher Education ◽  
Decision Making ◽  
Service Quality ◽  
Quality Assessment ◽  
Group Decision Making ◽  
Group Decision ◽  
Linguistic Information ◽  
Multiple Attribute ◽  
Magdm Problems

We investigate the multiple attribute group decision making (MAGDM) problems in which the attribute values take the form of 2-tuple linguistic information. In this paper, we develop the dependent 2-tuple ordered weighted harmonic averaging (DTOWHA) operator, and then apply the DTOWHA operator to develop some approaches for multiple attribute group decision making with 2-tuple linguistic information. Finally, an illustrative example for service quality assessment in special higher education is given to verify the developed approach and to demonstrate its practicality and effectiveness.

scholarly journals SOME HERONIAN MEAN OPERATORS WITH 2-TUPLE LINGUISTIC INFORMATION AND THEIR APPLICATION TO MULTIPLE ATTRIBUTE GROUP DECISION MAKING

2015 ◽  
Vol 21 (5) ◽  
pp. 797-814 ◽  
Author(s):  
Ye Ye ◽  
Peide LIU
Keyword(s):  
Decision Making ◽  
Group Decision Making ◽  
Group Decision ◽  
Aggregation Operators ◽  
Linguistic Information ◽  
Multiple Attribute ◽  
Heronian Mean

With respect to multi-attribute group decision-making problems, in which attribute values take the form of 2-tuple linguistic information, a new decision making method that considers the interrelationships of attribute values is proposed. Firstly, some new aggregation operators of 2-tuple linguistic information based on Heronian mean are proposed, such as 2-tuple linguistic Heronian mean operator (2TLHM) and 2-tuple linguistic weighted Heronian mean operator (2TLWHB), and some desired properties of the proposed operators are studied. Then, a method based on the 2TLHM and 2TLWHB operators for multiple attribute group decision making is developed. In this approach, the interrelationships of attribute values are considered. Finally, an illustrative example is given to verify the developed approach and to demonstrate its practicality and effectiveness.

UNCERTAIN LINGUISTIC PRIORITIZED AGGREGATION OPERATORS AND THEIR APPLICATION TO MULTIPLE ATTRIBUTE GROUP DECISION MAKING

2013 ◽  
Vol 21 (04) ◽  
pp. 603-627 ◽  
Author(s):  
L. Y. ZHOU ◽  
R. LIN ◽  
X. F. ZHAO ◽  
G. W. WEI
Keyword(s):  
Decision Making ◽  
Group Decision Making ◽  
Group Decision ◽  
Aggregation Operators ◽  
Linguistic Information ◽  
Priority Level ◽  
Multiple Attribute ◽  
Prioritized Aggregation Operators ◽  
Magdm Problems

In this paper, we investigate the uncertain linguistic multiple attribute group decision making (MAGDM) problems in which the attributes and experts are in different priority level. Motivated by the idea of prioritized aggregation operators (R. R. Yager, Prioritized aggregation operators, Int. J. Approximate Reasoning48 (2008) 263–274.), we develop some prioritized aggregation operators for aggregating uncertain linguistic information, and then apply them to develops some models for uncertain linguistic multiple attribute group decision making (MAGDM) problems in which the attributes and experts are in different priority level. Finally, a practical example about talent introduction is given to verify the developed approach and to demonstrate its practicality and effectiveness.

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