A fuzzy multi-granularity linguistic approach under group decision-making for the evaluation of supply chain flexibility

Abstract

With global competition rapidly intensifying and shifting to the supply chain level, supply chain flexibility (SCF) is becoming increasingly important. Despite its importance, the literature on SCF is limited. In group decision-making problems, the experts have their different backgrounds, experience, and knowledge. The experts use different linguistic term sets with different cardinalities (multi-granularity linguistic term sets) to express individual assessment information. Therefore, the objective of this paper is to develop a new fuzzy fusion method to deal with the heterogeneous group of experts’ problem with multi-granularity linguistic assessment information, and used to improve the SCF evaluation process. The results of this study are more objective and unbiased for two reasons. First, the results are generated by heterogeneous group decision-making with multi-granularity linguistic assessment information. Second, the fuzzy linguistic approach has more advantage to preserve no loss of information. Additionally, an example using a case study is used to illustrate the availability of the proposed method. We also show that the linguistic assessment of SCF is reasonable.

Keywords:

• supply chain flexibility
• group decision-making
• linguistic assessment
• consensus analysis
• LHGA operators

Acknowledgments

This research is partially supported by grant number NSE 98-2410-H-253-001 from the National Science Council of the Republic of China. The author would very grateful to senior Editor, Professor Ching-Jung Ting, and the two anonymous referees for their insightful and constructive comments and suggestions that have led to an improved version of this paper.