Nephron Algorithm

Supplier chain management (SCM) can respond to rapid market changes quickly and hence increase competitive advantage. On the other hand, supplier lies in first node of SCM. So, supplier evaluation and selection is important task to the whole SCM's agility and competition. Besides, there exist several proposed approaches to resolve this problem. However, a different methodology is proposed due to its powerful discriminatory performance, in this work. For this purpose, the nephron algorithm (NA) as a biological computation was inspired based of natural nephron performance because of its intelligent screening. It can be applied as data mining technique in order to cluster as well as to prioritize suppliers according their attributes and scores respectively. To illustrate the proposed model, the large, multinational, and Telecommunication Company was taken into account. Consequently, applied model is supposed to cluster suppliers precisely and accurately according to intellectual logic o nephron.

Autorentext

Reza Behmanesh from Iran, with birth date of 3/2/1979. B.A. degree of mining engineering from IUT, Isfahan, Iran. M.A. degree of Industrial engineering from Yazd university, Yazd, Iran graduated in 30/8/2010. The author's major field of study is supply chain management (SCM), and data mining techniques include Neural Networks (NNs),& Decision tree.