DocumentCode :
2590451
Title :
Generalized intuitionistic fuzzy soft sets and multiattribute decision making
Author :
Geng, Shengling ; Li, Yongming ; Feng, Feng ; Wang, Xin
Author_Institution :
Coll. of Comput. Sci., Shaanxi Normal Univ., Xi´´an, China
Volume :
4
fYear :
2011
fDate :
15-17 Oct. 2011
Firstpage :
2206
Lastpage :
2211
Abstract :
Both Fuzzy set theory and rough set theory are effective tools in dealing with uncertainty problems. However, these theories have their own inherent limitation, which is the inadequacy of the parameterizations tool. Soft set theory is a new mathematical tool in dealing with uncertainties which is free from the above difficulties. Soft set can deal with broader uncertain problems by the combination of them. The present paper aims to further generalize intuitionistic fuzzy soft sets and investigate their application in multiattribute decision making. A new soft computing model called generalized intuitionistic fuzzy soft sets is defined and some related properties are investigated. This new model could give approximate description of concerned objects in an intuitionistic fuzzy environment, together with some additional information on the weights of attributes. We consider the application of generalized intuitionistic fuzzy soft sets in multiattribute decision making. In particular, an effective algorithm to solve such decision making problems is presented and supported by illustrative examples.
Keywords :
decision making; fuzzy set theory; medical computing; fuzzy set theory; generalized intuitionistic fuzzy soft sets; multiattribute decision making; parameterizations tool; rough set theory; soft set theory; uncertainty problems; Computational modeling; Decision making; Fuzzy sets; Mathematical model; Rough sets; Uncertainty; generalized intuitionistic fuzzy soft sets; intuitionistic fuzzy sets; multiattribute decision making; soft sets;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Biomedical Engineering and Informatics (BMEI), 2011 4th International Conference on
Conference_Location :
Shanghai
Print_ISBN :
978-1-4244-9351-7
Type :
conf
DOI :
10.1109/BMEI.2011.6098682
Filename :
6098682
Link To Document :
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