Information | |
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 | |
【 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.
【 预 览 】
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