Research on Vegetable Pricing and Replenishment Strategies Based on Time Series and Linear Programming Models

RuiBing Wang; ZhiYi Niu; HuiKang Gao

doi:10.54097/gwfs8ihi

Authors

RuiBing Wang
ZhiYi Niu
HuiKang Gao

DOI:

https://doi.org/10.54097/gwfs8ihi

Keywords:

Time Series Model, Linear Programming, Linear Regression Model

Abstract

In this paper, an optimization model for pricing and replenishment of vegetable commodities was established based on historical sales data, wholesale price and wastage rate using linear regression, time series forecasting and linear programming. The model is analyzed and solved by Python, MATLAB, SPSS and other software, and the optimization strategy for commodity pricing and replenishment is proposed. First, bar charts and line graphs of sales volume changes were plotted using the matplotlib library in Python, and heat maps of correlation coefficients were plotted by the Pearson correlation coefficient method. Secondly, the relationship between sales volume and pricing is analyzed by scatter plot and linear regression model, and the time series model is constructed by using SPSS for sales volume forecasting. Finally, the restocking volume and pricing strategy for the vegetable category in the coming week are given based on the linear programming model to maximize the superstore revenue.

References

Li Y, Xu Q, Wang Y, et al. Genetic Algorithms Application for Pricing Optimization in Commodity Markets[J]. Mathematics, 2024, 12(9): 1289.

Pan H, You X, Liu S, et al. Pearson correlation coefficient-based pheromone refactoring mechanism for multi-colony ant colony optimization[J]. Applied Intelligence, 2021, 51: 752-774.

Osgood D W. Poisson-based regression analysis of aggregate crime rates[M]//Quantitative methods in criminology. Routledge, 2017: 577-599.

Dimri T, Ahmad S, Sharif M. Time series analysis of climate variables using seasonal ARIMA approach[J]. Journal of Earth System Science, 2020, 129: 1-16.

Anwar M Y, Lewnard J A, Parikh S, et al. Time series analysis of malaria in Afghanistan: using ARIMA models to predict future trends in incidence[J]. Malaria journal, 2016, 15: 1-10.

Bellingeri A, Gallo A, Liang D, et al. Development of a linear programming model for the optimal allocation of nutritional resources in a dairy herd[J]. Journal of dairy science, 2020, 103(11): 10898-10916.