Multiple Attribute Group Decision Making Method Based on Intuitionistic Fuzzy Einstein Interactive Operations

2020 ◽  
Vol 22 (3) ◽  
pp. 790-809 ◽  
Author(s):  
Peide Liu ◽  
Peng Wang
Keyword(s):  
Decision Making ◽  
Group Decision Making ◽  
Group Decision ◽  
Intuitionistic Fuzzy ◽  
Multiple Attribute ◽  
Interactive Operations

scholarly journals Hybrid Multiattribute Group Decision Making Based on Intuitionistic Fuzzy Information and GRA Method

2013 ◽  
Vol 2013 ◽  
pp. 1-10 ◽  
Author(s):  
Jian Guo
Keyword(s):  
Decision Making ◽  
Group Decision Making ◽  
Group Decision ◽  
Decision Makers ◽  
Ideal Solution ◽  
Decision Matrix ◽  
Intuitionistic Fuzzy ◽  
Multiple Attribute ◽  
Intuitionistic Fuzzy Entropy ◽  
Fuzzy Group Decision Making

Hybrid multiple attribute group decision making involves ranking and selecting competing courses of action available using attributes to evaluate the alternatives. The decision makers assessment information can be expressed in the form of real number, interval-valued number, linguistic variable, and the intuitionistic fuzzy number. All these evaluation information can be transformed to the form of intuitionistic fuzzy numbers. A combined GRA with intuitionistic fuzzy group decision-making approach is proposed. Firstly, the hybrid decision matrix is standardized and then transformed into an intuitionistic fuzzy decision matrix. Then, intuitionistic fuzzy averaging operator is utilized to aggregate opinions of decision makers. Intuitionistic fuzzy entropy is utilized to obtain the entropy weights of the criteria, respectively. After intuitionistic fuzzy positive ideal solution and intuitionistic fuzzy negative ideal solution are calculated, the grey relative relational degree of alternatives is obtained and alternatives are ranked. In the end, a numerical example illustrates the validity and applicability of the proposed method.

scholarly journals Methods for Multiple Attribute Group Decision Making Based on Intuitionistic Fuzzy Dombi Hamy Mean Operators

Symmetry ◽  
2018 ◽  
Vol 10 (11) ◽  
pp. 574 ◽  
Author(s):  
Zengxian Li ◽  
Hui Gao ◽  
Guiwu Wei
Keyword(s):  
Decision Making ◽  
Group Decision Making ◽  
Fuzzy Numbers ◽  
Group Decision ◽  
Intuitionistic Fuzzy Numbers ◽  
Intuitionistic Fuzzy ◽  
Multiple Attribute ◽  
Selection Of

In this paper, we extended the Hamy mean (HM) operator, the Dombi Hamy mean (DHM) operator, the Dombi dual Hamy mean (DDHM), with the intuitionistic fuzzy numbers (IFNs) to propose the intuitionistic fuzzy Dombi Hamy mean (IFDHM) operator, intuitionistic fuzzy weighted Dombi Hamy mean (IFWDHM) operator, intuitionistic fuzzy Dombi dual Hamy mean (IFDDHM) operator, and intuitionistic fuzzy weighted Dombi dual Hamy mean (IFWDDHM) operator. Following this, the multiple attribute group decision-making (MAGDM) methods are proposed with these operators. To conclude, we utilized an applicable example for the selection of a car supplier to prove the proposed methods.

scholarly journals An EDAS Method for Multiple Attribute Group Decision-Making under Intuitionistic Fuzzy Environment and Its Application for Evaluating Green Building Energy-Saving Design Projects

Symmetry ◽  
2020 ◽  
Vol 12 (3) ◽  
pp. 484 ◽  
Author(s):  
Yuan Liang
Keyword(s):  
Decision Making ◽  
Energy Saving ◽  
Group Decision Making ◽  
Group Decision ◽  
Green Building ◽  
Building Energy ◽  
Intuitionistic Fuzzy ◽  
Multiple Attribute ◽  
Building Energy Saving ◽  
Design Projects

Multiple attribute group decision-making (MAGDM) methods have a significant influence on decision-making in a variety of strategic fields, including science, business and real-life studies. The problem of evaluation in green building energy-saving design projects could be regarded as a type of MAGDM problem. The evaluation based on distance from average solution (EDAS) method is one of the MAGDM methods, which simplifies the traditional decision-making process. Symmetry among some attributes that are known and unknown as well as between pure attribute sets and fuzzy attribute membership sets can be an effective way to solve MAGDM problems. In this paper, the classical EDAS method is extended to intuitionistic fuzzy environments to solve some MAGDM issues. First, some concepts of intuitionistic fuzzy sets (IFSs) are briefly reviewed. Then, by integrating the EDAS method with IFSs, we establish an IF-EDAS method to solve the MAGDM issues and present all calculating procedures in detail. Finally, we provide an empirical application for evaluating green building energy-saving design projects to demonstrate this novel method. Some comparative analyses are also made to show the merits of the method.

scholarly journals Induced Interval-Valued Intuitionistic Fuzzy Hybrid Aggregation Operators with TOPSIS Order-Inducing Variables

2012 ◽  
Vol 2012 ◽  
pp. 1-24 ◽  
Author(s):  
Jun-Ling Zhang ◽  
Xiao-Wen Qi
Keyword(s):  
Decision Making ◽  
Group Decision Making ◽  
Group Decision ◽  
Aggregation Operators ◽  
Intuitionistic Fuzzy ◽  
Multiple Attribute ◽  
Special Cases ◽  
Wide Range ◽  
Induced Aggregation ◽  
Interval Valued

Two induced aggregation operators with novelly designed TOPSIS order-inducing variables are proposed: Induced Interval-valued Intuitionistic Fuzzy Hybrid Averaging (I-IIFHA) operator and Induced Interval-valued Intuitionistic Fuzzy Hybrid Geometric (I-IIFHG) operator. The merit of two aggregation operators is that they can consider additional preference information of decision maker’s attitudinal characteristics besides argument-dependent information and argument-independent information. Some desirable properties of I-IIFHA and I-IIFHG are studied and theoretical analysis also shows that they can include a wide range of aggregation operators as special cases. Further, we extend these operators to form a novel group decision-making method for selecting the most desirable alternative in multiple attribute multi-interest group decision-making problems with attribute values and decision maker’s interest values taking the form of interval-valued intuitionistic fuzzy numbers, and application research to real estate purchase selection shows its practicality.

scholarly journals NEW GROUP DECISION MAKING METHOD IN INTUITIONISTIC FUZZY SETTING BASED ON TOPSIS

2015 ◽  
Vol 23 (3) ◽  
pp. 441-461 ◽  
Author(s):  
Wei YANG ◽  
Zhiping CHEN ◽  
Fang ZHANG
Keyword(s):  
Decision Making ◽  
Group Decision Making ◽  
Group Decision ◽  
Attribute Weights ◽  
Intuitionistic Fuzzy ◽  
Multiple Attribute ◽  
Order Preference ◽  
Topsis Technique ◽  
Fuzzy Group Decision Making ◽  
Fuzzy Setting

In multiple attribute group decision making, the weights of decision makers are very crucial to ranking results and have gained more and more attentions. A new approach to determining experts’ weights is proposed based on the TOPSIS (Technique for Order Preference by Similarity to an Ideal Solution) method in intuitionistic fuzzy setting. The weights determined by our method have two advantages: the evaluation value has a large weight if it is close to the positive ideal evaluation value and far from negative ideal evaluation values at the same time, otherwise it is assigned a small weight; experts have different weights for different attributes, which are more appropriate for real decision making problems since each expert has his/her own knowledge and expertise. The multiple attribute intuitionistic fuzzy group decision making algorithm has been proposed which is suitable for different situations about the attribute weight information, including the attribute weights are known exactly, partly known and unknown completely. A supplier selection problem and the evaluation of murals in a metro line are finally used to illustrate the feasibility, efficiency and practical advantages of the developed approaches.

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