Supplier Evaluation in Supply Chain Environment Based on Radial Basis Function Neural Network

被引:3
|
作者
Liu, Shilin [1 ]
Yu, Guangbin [2 ]
Kim, Youngchul [3 ]
机构
[1] Beijing Univ Posts & Telecommun, Beijing, Peoples R China
[2] Beijing Zhongtianruiheng Technol Co Ltd, Beijing, Peoples R China
[3] Hanyang Univ, Seosan, South Korea
关键词
Analytic Hierarchy Process; Neural Network; Supplier Evaluation; Supply Chain; MODEL;
D O I
10.4018/IJITWE.339186
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
The comprehensive evaluation and selection of suppliers under the environment of supply chain management has become a key factor affecting the success of supply chain. How to select suppliers and the strategic partnership between suppliers under the environment of supply chain management has become an important challenge. To solve this problem, this paper takes the supplier evaluation and selection of Guangzhou Automobile Toyota Company as the research object, constructs the index system of supplier comprehensive evaluation and selection, uses the RBF neural network algorithm to establish the supplier evaluation and selection model, and makes an experimental study. The results show that radial basis function neural network is a local approximation network, which has a unique and definite solution to the problem, and there is no local minimum problem in BP network. It is a method that enables enterprises and suppliers to have a clear understanding and seek further promotion together. The research provides theoretical data support for enterprise managers to make decisions.
引用
收藏
页数:18
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