A decision support system for single-period single sourcing problem in supply chain management

A basic part of the logistic management of organizations is purchasing function, and appropriate supplier selection is one of the main responsibilities of this function. Appropriate supplier selection has an important role in reducing costs, increasing competitiveness and the share of market as well as improving customers' satisfaction. Hence, the use of accurate and efficient techniques for supplier selection problems is out of question. Due to the importance of appropriate supplier selection, lots of research have been focused on this topic, but only a few of them considered the supplier selection problem with the process of reducing the set of all suppliers to a smaller set of eligible suppliers. Therefore, in this paper, based on data envelopment analysis models, a new hybrid methodology is presented for evaluating potential suppliers and selecting the best supplier (single sourcing) under certainty environment for a single-period by applying the strategy of reducing the number of potential suppliers. This methodology includes two phases: (1) classifying suppliers into efficient and inefficient suppliers, and hence reducing the set of all suppliers into a smaller set of eligible suppliers, and (2) evaluating the efficient (eligible) suppliers. Finally, a sample problem is demonstrated to examine the proposed methodology in comparison with traditional methods.