Instructions and Formatting Rules

While data envelopment analysis (DEA) models are very sensitive to possible data errors, in many real applications, the data of production processes cannot be precisely measured. For this reason, the possibility of having available a methodology that allows the analyst to deal with imprecise data becomes an issue of great interest in these contexts. In this paper, we develop fuzzy version of the input relaxation model introduced in Jahahshahloo and Khodabakhshi 14 by using some ranking methods based on the comparison of (1-cuts. The resulting auxiliary crisp problems can be solved by the usual DEA software. We show, in a numerical example, how our models become specially useful fordetecting sensitive decision-making units.

Keywords:

Data envelopment analysis , Input relaxation: Fuzzy mathematical programming. Fuzzyintervals , Possibility programming