DocumentCode :
3300844
Title :
Some Generalized Uncertain Linguistic Aggregating Operators
Author :
Wei, Guiwu
Author_Institution :
Dept. of Econ. & Manage., Chongqing Univ. of Arts & Sci., Chongqing, China
fYear :
2009
fDate :
11-12 July 2009
Firstpage :
85
Lastpage :
88
Abstract :
With respect to multiple attribute group decision making problem with uncertain linguistic information, in which the attribute weights and expert weights take the form of real numbers, and the attribute preference values take the form of uncertain linguistic variables, some new generalized uncertain linguistic aggregating operators have been proposed: generalized uncertain linguistic weighted aggregating (GULWA) operator, generalized uncertain linguistic ordered weighted aggregating (GULOWA) operator and generalized uncertain linguistic hybrid aggregating (GULHA) operator. It has been shown that both GULWA and GULOWA operators are the special case of the GULHA operator. The GULHA operator generalizes both the GULWA and GULOWA operators, and reflects the importance degrees of both the given arguments and their ordered positions. Based on the GULWA and GULHA operators, an approach has been proposed to solve the MAGDM problems under uncertain linguistic environment. Finally, an illustrative example is given to verify the developed approach and to demonstrate its practicality and effectiveness.
Keywords :
computational linguistics; decision making; decision theory; mathematical operators; attribute preference value; attribute weight; expert weight; generalized uncertain linguistic ordered aggregating operator; generalized uncertain linguistic weighted aggregating operator; linguistic hybrid aggregating operator; multiple attribute group decision making problem; Art; Conference management; Decision making; Engineering management; Environmental economics;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Services Science, Management and Engineering, 2009. SSME '09. IITA International Conference on
Conference_Location :
Zhangjiajie
Print_ISBN :
978-0-7695-3729-0
Type :
conf
DOI :
10.1109/SSME.2009.92
Filename :
5233342
Link To Document :
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