LAUSR

The selection of the optimal supply is an open and crucial issue in supply chain management (SCM), which can be considered as a multi-criteria decision-making (MCDM) problem where the expression and processing of uncertain information could be involved. The purpose of this paper is to develop an elimination and choice translating reality (ELECTRE)-based MCDM method where the evaluation information is expressed and handled by a Dempster–Shafer theory (DST). DST is a primary methodology for uncertainty modeling. In this paper, the weight of the criteria and the performance of each alternative are expressed by linguistic terms and confidence levels, which are then converted to basic probability assignment (BPA) representations. To aggregate evaluations of different experts more rationally and efficiently, a discounting method in DST is presented based on the proposed concept of evidential reliability. In addition, as one family of MCDM models, the ELECTRE method is famous for its outranking relations to rank a set of alternatives. As an extension, synthetic weight, including subjective and objective weights, is applied to determine the concepts of concordance and discordance. The proposed DS-ELECTRE approach not only maintains the advantage of the DST that directly represents and handles uncertainty but also can play the role of the ELECTRE method in analyzing outranking relations among alternatives. An illustrative numerical example is conducted to demonstrate the effectiveness of the DS-ELECTRE method.