Heterogeneous multigranulation fuzzy rough set-based multiple attribute group decision making with heterogeneous preference information

2018 ◽  
Vol 122 ◽  
pp. 24-38 ◽  
Author(s):  
Bingzhen Sun ◽  
Weimin Ma ◽  
Xiangtang Chen ◽  
Xiaonan Li
Keyword(s):  
Decision Making ◽  
Rough Set ◽  
Group Decision Making ◽  
Group Decision ◽  
Fuzzy Rough Set ◽  
Preference Information ◽  
Multiple Attribute ◽  
Heterogeneous Preference

Dependent Interval 2-Tuple Linguistic Aggregation Operators and Their Application to Multiple Attribute Group Decision Making

2014 ◽  
Vol 22 (05) ◽  
pp. 717-735 ◽  
Author(s):  
Hu-Chen Liu ◽  
Qing-Lian Lin ◽  
Jing Wu
Keyword(s):  
Decision Making ◽  
Group Decision Making ◽  
Group Decision ◽  
Aggregation Operators ◽  
Decision Makers ◽  
Weighted Averaging ◽  
Linguistic Variables ◽  
Preference Information ◽  
Operational Laws ◽  
Multiple Attribute

Consider the various types of uncertain preference information provided by the decision makers and the importance of determining the associated weights for the aggregation operator, the multiple attribute group decision making (MAGDM) methods based on some dependent interval 2-tuple linguistic aggregation operators are proposed in this paper. Firstly some operational laws and possibility degree of interval 2-tuple linguistic variables are introduced. Then, we develop a dependent interval 2-tuple weighted averaging (DITWA) operator and a dependent interval 2-tuple weighted geometric (DITWG) operator, in which the associated weights only depend on the aggregated interval 2-tuple arguments and can relieve the influence of unfair arguments on the aggregated results by assigning low weights to them. Based on the DITWA and the DITWG operators, some approaches for multiple attribute group decision making with interval 2-tuple linguistic information are proposed. Finally, an illustrative example is given to demonstrate the practicality and effectiveness of the proposed approaches.

A Hesitant Fuzzy Multiple Attribute Group Decision Making Approach Based on TOPSIS for Parts Supplier Selection

2013 ◽  
Vol 357-360 ◽  
pp. 2730-2737 ◽  
Author(s):  
Jun Ling Zhang ◽  
Xiao Wen Qi ◽  
Hai Bin Huang
Keyword(s):  
Decision Making ◽  
Group Decision Making ◽  
Supplier Selection ◽  
Distance Measure ◽  
Group Decision ◽  
Hesitant Fuzzy Set ◽  
Fuzzy Information ◽  
Application Study ◽  
Preference Information ◽  
Multiple Attribute

This paper investigates multiple attribute group decision making (MAGDM) with hesitant fuzzy preference information, which is a significantly import issue to be deeply studied in management and industrial engineering. Firstly, simultaneously considering optimistic and pessimistic attitudinal preference information, an improved distance measure for hesitant fuzzy set is defined. Then, utilizing the newly defined distance measure, a hesitant fuzzy multiple attribute group decision making approach based on TOPSIS method is constructed, which can effectively avoid high complexity of aggregating hesitant fuzzy information in traditional methods. Further, an application study on parts supplier selection has verified the practically and effectiveness of developed methods.

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