Z-MABAC Method for the Selection of Third-Party Logistics Suppliers in Fuzzy Environment

Abstract

As third-party logistics providers occupy an increasingly important position in the operation strategies of various enterprises, choosing a partner that suits them and can bring benefits to them has become an important decision-making issue for each enterprise. A lot of studies have been done with classical fuzzy methods, but there are relatively few studies that consider information reliability. The emergence of Z-numbers makes up for this deficiency, including the restriction on the evaluation object and the corresponding degree of confidence. In this article, making decisions based on Z-numbers can better transform language values into fuzzy numbers. By integrating the existing Multi-Attributive Border Approximation area Comparison (MABAC) method and Z-numbers, a new method for the selection of third-party logistics providers is provided. Finally, the feasibility and effectiveness of the approach are verified by comparing with the classical Multi Criteria Decision Making methods. The Z-number is a relatively new concept that can flexibly represent the confidence of information, which will be a relatively important research direction in the future.