Traditionally in supply chain management suppliers and customers are evaluated independently. This is in spite of the fact that supplier performance has direct impact on the performance of the customer. This research develops a mechanism for simultaneous evaluation and prioritization of supplier and customer using the sustainability metrics comprising economic, environment and social measures. In order to quantify the qualitative factors, priority index is introduced to measure the prioritization of customers and suppliers simultaneously. To get the priority index for each customer and supplier, a novel analytical hierarchical process-based fuzzy inference decision support system (AHP-FIDSS) has been introduced. An AHP-FIDSS involves the factor screening, hierarchical structure modeling, quantification of qualitative factors, and their conversion to quantitative values. AHP-FIDSS is knowledge-based system involving expert’s decision alternatives or logical rules. The number of input variables and their levels are proportional to the number of logical rules and rule size. In order to reduce the numbers of rules, a Taguchi orthogonal array is used that reduces the numbers of rules, thereby substantially simplifying the evaluation process A case study of a supply chain of surgical instruments has been presented for the real-time application of the proposed model. The results exhibited the simultaneous classification of customers and suppliers with respect to their priority index. Higher value of priority index indicates higher importance and vice versa. This research is useful for the supply chain mangers in procurement, sales and production to develop an importance classification for customers and suppliers in a supply chain.
Bibliographical notePublisher Copyright:
© 2020, Taiwan Fuzzy Systems Association.
All Science Journal Classification (ASJC) codes
- Theoretical Computer Science
- Computational Theory and Mathematics
- Artificial Intelligence