Abstract
The reverse logistics cost forecast is the basis of reverse logistics cost control, and the key link related to the success of reverse logistics management. The factors that influence reverse logistics cost are complicated and numerous. The paper begins with analysis of the composition of reverse logistics, introduces the relations between reverse logistics cost and its influence factors, builds the reverse logistics cost prediction Based on BP neural network. An empirical study was carried out on a product of a company. Then simulates the model by Matlab and acquires good forecasting results. It is expected to provide some reference for enterprises to implement reverse logistics cost management.
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