A novel efficient approach for supplier selection problem using the OWA-based ranking technique

Abstract

Supplier selection is not only an important issue in the supply chain management but also a critical factor for affecting overall supply chain performance. However, most of the traditional calculating method does not consider the ordered weight of attribute values in a supplier selection problem. It will cause biased conclusions and decision-makers to make the wrong judgment. In order to effectively solve this issue, this paper proposed a novel OWA-based ranking technique to deal with the supplier selection problem. The proposed approach has three major advantages: (1) it has considered the ordered weight of attribute values, (2) it can deal with the insufficient and incomplete information in the supplier selection problem, and (3) the attribute rating values and attribute weights of suppliers, described by linguistic variables, are more flexible and reasonably reflect real-world situations. Finally, a supplier selection numerical example is used to illustrate the use of the proposed approach. After comparing the result that was obtained from the proposed method with both the grey possibility degree method and the grey-related analysis method, it was found that the proposed approach provides a more accurate and efficient ranking for dealing with the supplier selection problem.