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2013 (Vol. 5, Issue: 10)
Article Information:

Partner Selection Optimization Model of Agricultural Enterprises in Supply Chain

Feipeng Guo and 3Qibei Lu
Corresponding Author:  Qibei Lu 

Key words:  Agricultural supply chain, BP neural network, partner selection, principal component analysis, rough set, ,
Vol. 5 , (10): 1285-1291
Submitted Accepted Published
April 26, 2013 May 07, 2013 October 05, 2013

With more and more importance of correctly selecting partners in supply chain of agricultural enterprises, a large number of partner evaluation techniques are widely used in the field of agricultural science research. This study established a partner selection model to optimize the issue of agricultural supply chain partner selection. Firstly, it constructed a comprehensive evaluation index system after analyzing the real characteristics of agricultural supply chain. Secondly, a heuristic method for attributes reduction based on rough set theory and principal component analysis was proposed which can reduce multiple attributes into some principal components, yet retaining effective evaluation information. Finally, it used improved BP neural network which has self-learning function to select partners. The empirical analysis on an agricultural enterprise shows that this model is effective and feasible for practical partner selection.
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  Cite this Reference:
Feipeng Guo and 3Qibei Lu , 2013. Partner Selection Optimization Model of Agricultural Enterprises in Supply Chain.  Advance Journal of Food Science and Technology, 5(10): 1285-1291.
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ISSN (Online):  2042-4876
ISSN (Print):   2042-4868
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