Supplier selection and evaluation using generalized fuzzy multi-criteria decision making approach

Abstract

Supplier selection and evaluation plays an importance role for companies to gain competitive advantage and achieve the objectives of the whole supply chain. To select the appropriate suppliers, many qualitative and quantitative criteria are needed consider in the decision process. Therefore, supplier selection and evaluation can be seem as a multi-criteria decision making (MCDM) problem in vague environment. However, most existing fuzzy MCDM approaches have been developed using normal fuzzy numbers or converting generalized fuzzy numbers into normal fuzzy numbers through normalization process. This leads to a restriction in the application of the fuzzy MCDM approaches. In this study, a generalized fuzzy MCDM approach is proposed to select and evaluate suppliers. In the proposed approach, the ratings of alternatives and important weights of criteria are expressed in linguistic terms using generalized fuzzy numbers. Then, the membership functions of the final fuzzy evaluation value are developed. To make procedure easier and more practical, the weighted ratings are defuzzified into crisp values by employing the maximizing and minimizing set ranking approach to determine the ranking order of alternatives. Finally, a numerical example is presented to illustrate the applicability and efficiency of the proposed method.