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A novel fuzzy Data Envelopment Analysis methodology for performance evaluation in a two-stage supply chain

The paper presents a novel fuzzy Data Envelopment Analysis (DEA) technique for supplier selection under uncertainty. Uncertain input and output data characterizing suppliers are estimated through triangular fuzzy numbers. The resulting fuzzy triangular efficiency is determined by using only a set of weights, derived as a compromise between objectives. The obtained results are defuzzified and compared in order to rank suppliers. The presented method is applied for the evaluation of a set of candidate suppliers of an SME located in Southern Italy, showing the ease of application and the discriminative power between different suppliers under uncertain data.