NDLI: A New Solution of Intuitionistic Fuzzy Multiple Attribute Decision-Making Based on Attributes Preference

Content Provider	IEEE Xplore Digital Library
Author	Juan Li Chengyi Zhang
Copyright Year	2009
Abstract	For the situations that the preference information to attributes and estimating information to alternatives are expressed by intuitionistic fuzzy values, a new solution of the multiple attribute decision-making is given. Firstly, the solution of positive-ideal alternatives and negative-ideal alternatives are studied based on the traditional TOPSIS method. We give a method to choose the possible positive-ideal solution and the possible negative-ideal solution, and deal with the uncertainty information by entropy theory to get the only ideal alternatives. Secondly, the new solution of the best attribute weight vector is discussed. A new math model for solving the best attribute weight vector is given based on the isomorphism of intuitionistic fuzzy sets, and the process for solving multiple attribute decision-making is introduced. Finally, a practical example is illustrated to verify the effectiveness of this method.
Starting Page	228
Ending Page	232
File Size	360099
Page Count	5
File Format	PDF
ISBN	9780769537351
DOI	10.1109/FSKD.2009.832
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2009-08-14
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	ideal alternatives Fuzzy sets Uncertainty the best attribute weight multiple attribute decision-making Decision making Investments Entropy Mathematics Fuzzy systems Quality management
Content Type	Text
Resource Type	Article

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1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
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4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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