The pricing and replenishment strategy of vegetables is very important for supermarkets, and accurate prediction and appropriate pricing replenishment strategies are of great significance for saving costs, improving supply chain management, and reducing the loss rate of vegetables. In order to accurately predict the pricing strategy and replenishment of vegetables every day in the coming week, based on the time series prediction model and particle swarm optimization algorithm, combined with the advantages of MATLAB in processing cleaning data, the pricing and replenishment strategy model that maximizes the revenue of supermarkets was constructed. Finally, based on the data, it is concluded that the maximum income of the supermarket in the coming week is 17108 yuan, and the maximum income per day is 2108.20 yuan.

Mengxiao Li, Wei Li, Zhixuan Zhao. Research on vegetable pricing and replenishment strategy based on time series model and particle swarm optimization. Academic Journal of Computing & Information Science (2023), Vol. 6, Issue 13: 138-144. https://doi.org/10.25236/AJCIS.2023.061320.

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