An approach based on ANFIS input selection and modeling for supplier selection problem

Supplier selection is a key task for firms, enabling them to achieve the objectives of a supply chain. Selecting a supplier is based on multiple conflicting factors, such as quality and cost, which are represented by a multi-criteria description of the problem. In this article, a new approach based on Adaptive Neuro-Fuzzy Inference System (ANFIS) is presented to overcome the supplier selection problem. First, criteria that are determined for the problem are reduced by applying ANFIS input selection method. Then, the ANFIS structure is built using data related to selected criteria and the output of the problem. The proposed method is illustrated by a case study in a textile firm. Finally, results obtained from the ANFIS approach we developed are compared with the results of the multiple regression method, demonstrating that the ANFIS method performed well.

► We develop a new approach based on Adaptive Neuro-Fuzzy Inference System (ANFIS) to overcome supplier selection problem.
► We use ANFIS input selection method to assess effective criteria.
► Selected criteria and determined output build ANFIS model.
► We present efficiency of developed model by applying a case study in a textile firm.