Research on Replenishment Strategy of Vegetable Commodities Based on ARIMA, Random Forest and Optimization Algorithm
DOI:
https://doi.org/10.54097/fxn36417Keywords:
Optimization model; ARIMA; time series model; random forest; vegetable commodity pricing.Abstract
With the improvement of social productivity and the intensification of market competition, urban residents pay more and more attention to fresh vegetables and other fresh products. Therefore, this paper investigates the supply demand, pricing and replenishment strategies of vegetable commodities. First, this paper uses ARIMA model to predict the wholesale price of vegetable commodities. Then, this paper uses the random forest model to estimate the sales volume of vegetable commodities. Both models showed great accuracy on the test set. Finally, based on the model results, an optimization model for developing replenishment strategies was constructed and solved using relevant market information. This study helps to help the fresh produce wholesale industry develop more effective sales strategies in advance and reduce resource waste.
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