Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
10322259 | Expert Systems with Applications | 2015 | 9 Pages |
Abstract
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.
Related Topics
Physical Sciences and Engineering
Computer Science
Artificial Intelligence
Authors
Muhammad Saad Memon, Young Hae Lee, Sonia Irshad Mari,