This paper is research on the ordering and transhipment scheme of raw materials in production enterprises. The order and purchase data of 402 raw material suppliers and the transport loss rate data of 8 transporters were collected and analysed. First of all, from the three dimensions of hard power (based on the "Q.C.D.S" principle), soft power and potential, the relevant information of seven indexes such as just-in-time delivery rate, coefficient of variation of supply quantity and proportion of supply quantity is extracted to analyse its supply characteristics quantitatively. Then an improved TOPSIS model based on grey relational analysis is established to comprehensively evaluate the 402 suppliers to ensure the normal production of the enterprise, from which the list of the most important suppliers can be obtained. With the help of the K-means clustering algorithm, we screen the suppliers whose supply proportion and average delivery just-in-time rate are good at the same time and determine that the minimum number of suppliers is 23 (at this time, the two indicators are about 80%). Then, to dig deeply into the raw material supply of suppliers in the next 24 weeks, we build time series models (ARMA, ATLSTM) to forecast. Based on this, we establish the 01 planning model, which minimises capacity gap and cost as the objective function to determine the best ordering plan.
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