Ranking fuzzy variables by expected value and variance

Authors:
Xiaozhong Li;Wansheng Tang;Ruiqing Zhao
Affiliations:
Institute of Systems Engineering, Tianjin University, Tianjin, China and College of Computer Science and Information Engineering, Tianjin University of Science and Technology, Tianjin, China;Institute of Systems Engineering, Tianjin University, Tianjin, China;Institute of Systems Engineering, Tianjin University, Tianjin, China
Venue:
FSKD'09 Proceedings of the 6th international conference on Fuzzy systems and knowledge discovery - Volume 6
Year:
2009

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Abstract

Ranking fuzzy numbers and fuzzy variables plays an important role in decision-making, data analysis, artificial intelligence and socioeconomic systems. Various approaches have been developed for ranking fuzzy numbers. Each of these techniques has been shown to produce nonintuitive results in certain cases. This paper proposes a new approach for ranking of fuzzy variables based on their expected values and variances within the framework of credibility theory. Some comparative examples are used to illustrate the advantage of the proposed method.