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Learning to Select Supplier Portfolios for Service Supply Chain.


ABSTRACT: The research on service supply chain has attracted more and more focus from both academia and industrial community. In a service supply chain, the selection of supplier portfolio is an important and difficult problem due to the fact that a supplier portfolio may include multiple suppliers from a variety of fields. To address this problem, we propose a novel supplier portfolio selection method based on a well known machine learning approach, i.e., Ranking Neural Network (RankNet). In the proposed method, we regard the problem of supplier portfolio selection as a ranking problem, which integrates a large scale of decision making features into a ranking neural network. Extensive simulation experiments are conducted, which demonstrate the feasibility and effectiveness of the proposed method. The proposed supplier portfolio selection model can be applied in a real corporation easily in the future.

SUBMITTER: Zhang R 

PROVIDER: S-EPMC4873154 | biostudies-literature | 2016

REPOSITORIES: biostudies-literature

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Learning to Select Supplier Portfolios for Service Supply Chain.

Zhang Rui R   Li Jingfei J   Wu Shaoyu S   Meng Dabin D  

PloS one 20160519 5


The research on service supply chain has attracted more and more focus from both academia and industrial community. In a service supply chain, the selection of supplier portfolio is an important and difficult problem due to the fact that a supplier portfolio may include multiple suppliers from a variety of fields. To address this problem, we propose a novel supplier portfolio selection method based on a well known machine learning approach, i.e., Ranking Neural Network (RankNet). In the proposed  ...[more]

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