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We present a novel cross efficiency fuzzy Data Envelopment Analysis (DEA) technique for supplier selection under uncertainty. In order to deal with uncertain input and output suppliers data, triangular fuzzy numbers are employed. A fuzzy triangular efficiency is associated to each supplier through a cross evaluation by a compromise between objectives. The results are defuzzified and a supplier ranking is determined. The method is applied to the evaluation of a set of candidate suppliers of an Italian SME, showing the ease of application and discriminative power among suppliers.

The paper addresses the optimal design of the last branch of the supply chain, i.e., the Distribution Network (DN). We extend a deterministic optimization model previously proposed by the authors, using fuzzy numbers and fuzzy logic to take into account uncertainty in the DN model and in the DN design. Hence, a procedure employing digraph modeling and fuzzy mixed integer linear programming is presented to select the optimal DN configuration. To show the method effectiveness, the optimization model is applied to a case study.

The paper addresses the optimal design of the last branch of the supply chain, i.e., the Distribution Network (DN), starting from manufacturers till the retailers. Considering a distributed system composed of different stages connected by material links labeled with suitable performance indices, a procedure employing digraph modeling and mixed integer linear programming is presented to select the (sub)optimal DN configuration. The optimization model is applied under structural constraints to a case study describing the distribution chain of a large enterprise of southern Italy producing consumer goods. The problem solution provides different structures allowing the improvement of the DN flexibility and performance.