Supplier Classification Based on Artificial Immune System Clustering Algorithm

Abstract:

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The theory of artificial immune system cluster analysis was studied firstly, the real encoding artificial immune system cluster analysis process was put forward, Then identify indexes of supplier classification were confirmed. Finally, according to a power company some supplier data, supplier were classed, using the cluster analysis with artificial immune system. Suppliers were divided into three categories: the first group includes 3 suppliers, 4 and 3 suppliers for the second group and the third group respectively. The results show that the calculation process of Artificial immune system clustering algorithm is simple, This method can minimize the requirements of professional knowledge and it is suitable to large volume of data while it is not sensitive to the different data order at the same time. So the artificial immune system cluster algorithm has many advantages in obtaining the optimal solution, and the artificial immune system cluster algorithm is feasible to be used in supplier classification.

Info:

Periodical:

Edited by:

Dongye Sun, Wen-Pei Sung and Ran Chen

Pages:

4796-4800

DOI:

10.4028/www.scientific.net/AMM.121-126.4796

Citation:

S. X. Yang et al., "Supplier Classification Based on Artificial Immune System Clustering Algorithm", Applied Mechanics and Materials, Vols. 121-126, pp. 4796-4800, 2012

Online since:

October 2011

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Price:

$35.00

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