Notice of RetractionEvaluation of supply chain performance based on BP neural network

Notice of Retraction

After careful and considered review of the content of this paper by a duly constituted expert committee, this paper has been found to be in violation of IEEE´s Publication Principles.

We hereby retract the content of this paper. Reasonable effort should be made to remove all past references to this paper.

The presenting author of this paper has the option to appeal this decision by contacting TPII@ieee.org.

Evaluation of supply chain performance is vital to the operation and management of supply chain. This paper constructed an evaluation index system of supply chain performance. The index system was composed of satisfaction degree of customer, information sharing degree, logistics level and financial conditions. Then the paper established a supply chain performance evaluation model with multilayer feedforward neural network structure based on error back-propagation (BP) algorithm. The model combined quantitative with qualitative analysis and had strong self-learning, self-adaptation, parallel processing and nonlinear conversion capabilities. Finally the paper developed a case study. The result shows that BP neural network is of fast speed and high accuracy in nonlinear identification and provides a new method to evaluate supply chain performance. Future evaluation method should focus on the combination of quantitative with qualitative analysis and the validity and practicability of management model.