A Fuzzy Multiple Attribute Decision-Making for Evaluating Flexibility in a Supply Chain

Abstract

Evaluation of the flexibility in a supply chain (supply chain flexibility) is very important to determining the competitiveness of supply chain, and is being increasing in the literature on supply chain. Traditional approaches have attempted to quantify SCF theoretically or objectively. The subjective assessment of both importance grade and performance rating for supply chain flexibility dimensions and related metrics has seldom been addressed. The objective of this study is to develop a multiple attribute decision-making model with two-stage assessment to the evaluation of the supply chain flexibility in a supply chain management development. The evaluation problem is solved by a fuzzy fusion method based on maximum entropy linguistic ordered weighted geometric averaging (MELOWGA) operators. We also provided a fuzzy fusion method of linguistic information. While evaluating the degree of supply chain flexibility, one may find the need for improving supply chain flexibility, and determine the dimensions of supply chain flexibility as the best directions for improvement. Example using a case study is used to illustrate the availability of the proposed method. Finally, we also show that the linguistic assessment of supply chain flexibility is reasonable.