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An Interval-Valued Intuitionistic Fuzzy MADM Method Based on a New Similarity Measure
Haiping Ren1  Guofu Wang2 
[1] School of Software, JiangxiUniversity of Science and Technology, Nanchang 330013, China;School of Mathematics and Statistics, Central South University, Changsha 410000, China; E-Mail:
关键词: similarity measure;    interval-valued intuitionistic fuzzy set;    multi-attribute decision making method;    maximum similarity optimization model;   
DOI  :  10.3390/info6040880
来源: mdpi
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【 摘 要 】

Similarity measure is one of the most important measures of interval-valued intuitionistic fuzzy (IVIF) sets. This article will put forward a new similarity measure, which considers the impacts of membership degree, nonmembership degree and median point of IVIF sets. For cases with partially known attribute weight information in multi-attribute decision-making (MADM) problems, a new weighting method is put forward by establishing the maximum similarity optimization model to solve the optimal weights. Further, a new decision-making method is developed on the basis of proposed similarity measure, and an applied example proves the effectiveness and feasibility of the proposed methods.

【 授权许可】

CC BY   
© 2015 by the authors; licensee MDPI, Basel, Switzerland.

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