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Generalized intuitionistic fuzzy soft sets and multiattribute decision making

Authors: Shengling Geng; Yongming Li 0001; Feng Feng 0003; Xin Wang;

Generalized intuitionistic fuzzy soft sets and multiattribute decision making

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.

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
6
Average
Average
Average
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