Group multi-criteria supplier selection using combined grey systems theory and uncertainty theory

• Published in: Expert systems with applications Vol. 42; no. 21; pp. 7951 - 7959
• Main Authors: Memon, Muhammad Saad, Lee, Young Hae, Mari, Sonia Irshad
• Format: Journal Article
• Language: English
• Published: Elsevier Ltd 30.11.2015
• Subjects: Component and supplier management; Construction; Expert systems; Fuzzy; Grey systems theory; Mathematical models; Stochasticity; Supplier selection; Systems theory; Uncertain programming; Uncertainty; Uncertainty theory; Supplier selection; Grey systems theory; Uncertain programming; Uncertainty theory
• ISSN: 0957-4174; 1873-6793
• DOI: 10.1016/j.eswa.2015.06.018

•Developing framework for reducing purchasing risks associated with suppliers.•Combination of grey system theory and uncertainty theory is used.•It neither requires any probability distribution nor fuzzy membership function.•It selects the most appropriate suppliers and allocates optimal purchase quantity. Supplier selection in supply chain is critical strategic decision for organization’s success and has attracted much attention of both academic researchers and practitioners. Supplier selection problem consists of stochastic and recognitive uncertainties. However, the requirement of large sample size and strong subject knowledge to build suitable fuzzy membership function restrict the applicability of probability and fuzzy theories in supplier selection problem. In response, this study proposed a new tool for supplier selection. In this paper, we applied the combination of grey system theory and uncertainty theory which neither requires any probability distribution nor fuzzy membership function. The objective of this paper is to develop framework for reducing the purchasing risks associated with suppliers. The proposed supplier selection method not only selects the most appropriate supplier(s) but also allocate optimal purchase quantity under stochastic and recognitive uncertainties. An example is shown to highlight the procedure of the proposed model at the end of this paper.