Research on strategies of trade optimization model based on risk assessment of large data

Inhalt:
Based on the selection principle of suppliers, this paper uses the technical means of big data analysis to evaluate the risk of suppliers, uses the analytic hierarchy process evaluation method to determine the weight of primary and secondary indicators, and completes the construction of the risk evaluation system, which is expected to greatly improve the efficiency of the company's material procurement operation. This paper establishes a supply chain model, takes the weekly order quantity as the decision variable and the weekly inventory quantity as the state variable, quantitatively finds out the corresponding relationship between the weekly order quantity, the inventory quantity and the loss quantity, and puts forward the state transition equation and the basic equation. On the premise of meeting the capacity demand, according to the recursive relationship and considering the weekly loss rate of forwarders, this paper obtains the loss function of minimizing the 24-week loss rate of all forwarders. According to the uncertainty of the actual ordering process, this paper uses the random factor to randomly simulate the random difference between the supply quantity and the order quantity for five times, and accurately locate the supply chain strategy. Finally, the effect of the scheme is visually analyzed with image data.