Academic Journal of Computing & Information Science, 2024, 7(10); doi: 10.25236/AJCIS.2024.071012.
Litao Zeng, Yang Gao, Haisen Hu
School of Electronics and Automation, City Institute Dalian University of Technology, Dalian, 116600, China
For the problem of wastage caused by the short freshness duration and perishability of vegetable category goods in fresh produce superstores, this investigation constructed an automatic pricing and replenishment decision support module using historical sales of data. The research firstly adopts a Python-based Long Short-Term Memory Network (LSTM) time-series of forecast model to predict the future wholesale prices of the vegetable category, and achieve a high degree of model fit (r2 ≥ 0.93). Subsequently, this research built an XGBoost sales volume prediction model based on sales unit price and wholesale price, in which the model for most of the categories showed significant prediction results. Furthermore, this study formulated an objective solution model with revenue maximization as the goal, and optimized the solution using genetic algorithm to maximize the total income of the superstore in the next seven days. Additionally, through the sensitivity analysis of the model, this study verified the stability of the model output. The results show that the model is more robust to small changes in the input variables. This study provides the theoretical basis and practical guidance for inventory management and revenue optimization in fresh produce superstores.
Fresh Supermarket, Vegetable Preservation, LSTM, XGBoost, Genetic Algorithm
Litao Zeng, Yang Gao, Haisen Hu. Research on retail pricing strategy of supermarket fresh products based on XGBoost model. Academic Journal of Computing & Information Science (2024), Vol. 7, Issue 10: 82-88. https://doi.org/10.25236/AJCIS.2024.071012.
[1] Hsu P, Teng H, Wee H. Optimal lot sizing for deteriorating items with triangle-shaped demand and uncertain lead time[J]. European J. of Industrial Engineering, 2009, 3(3):247-260.
[2] Liu Xinmin, Yan Xiuxia, Fu Kaiying, et al. Research on pricing strategy of fresh agricultural products in dual-channel supply chain from the perspective of multi-dimensional collaboration [J]. Research of Business Economics, 2020, (11):151-154.
[3] Hu Hanli, Cao Yu, Wu Kan. Research on sales model selection and pricing of fresh supply chain based on pre-sale [J]. Operations Research and Management, 2022, 31(11):128-134.
[4] Duan Yongrui, Lei Wei, Li Guiping. Non-instant spoilage inventory and pricing strategy considering preservation investment [J]. Journal of Systems Management, 2019, 28(04):732-741.
[5] Song Zhilan, Article Review. Fresh product pricing and inventory strategy under the background of new retail [J]. Logistics Technology, 2021, 40(07):89-94.
[6] Yang Z, Zhang Q, Zhang R, et al. Transverse Vibration Response of a Super High-Speed Elevator under Air Disturbance[J]. International Journal of Structural Stability and Dynamics, 2019, 19(9):25.
[7] Chen T, Guestrin C. XGBoost: A Scalable Tree Boosting System [J]. CoRR, 2016, abs/1603.02754
[8] Klein I. Smartphone Location Recognition: A Deep Learning-Based Approach [J]. Sensors, 2019, 20(1): 214-218.
[9] Sourabh K, Singh S C, Vijay K. A review on genetic algorithm: past, present, and future. [J]. Multimedia tools and applications, 2020, 80(5):31-36.
[10] Bo Y, Zhuo C, Xinni W, et al. Influence of logistic service level on multichannel decision of a two-echelon supply chain[J]. International Journal of Production Research, 2020, 58(11):3304-3329.