Using data envelopment analysis to defuzzify a group of dependent fuzzy numbers

Abstract

The defuzzification process converts fuzzy numbers to crisp ones and is an important stage in the implementation of fuzzy systems. In many actual applications, relationships among data indicate their mathematical dependence on one another. Hence, this study proposes a new method based on the Data Envelopment Analysis (DEA) model to defuzzify a group of dependent fuzzy numbers. It also aims to obtain the crisp points that satisfy the characteristics of these data as a group by approximating the optimal solutions within the production possibility set of the DEA model.The proposed method partitions the fuzzy numbers, and the relationships among these numbers are observed as constraints. Finally, the usefulness of this new method is illustrated in a real-world problem

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