Research on automatic pricing and replenishment decision of vegetable commodities based on optimization model

Lizhen  Liu

doi:10.54097/d5eece96

Authors

Lizhen Liu

DOI:

https://doi.org/10.54097/d5eece96

Keywords:

Cost-plus pricing; LSTM model; Backpack model; Optimization model.

Abstract

In fresh food superstores, because vegetable commodities are characterized by perishability and high value loss, superstores usually replenish daily commodities based on the historical sales and demand of various commodities. In order to make the optimal replenishment decision, this paper firstly firstly uses Matlab fitting toolbox to get the functional relationship between the total sales volume and the cost-plus pricing, so as to analyze the relationship between the total sales volume and the cost-plus pricing of each vegetable category, and then takes the category as a unit, and then constructs the optimization model, and solves the optimal replenishment volume and pricing strategy. The replenishment decision is obtained by filtering out the most profitable single product among the factors of unit price, sales volume, and total replenishment volume through objective planning under the constraints of considering the single product category and minimum display volume.

Downloads

Download data is not yet available.

References

Herbon A. Optimal pricing and replenishment of an expiring inventoried product under heterogeneous consumer sensitivities [J]. Decision sciences, 2018, 49(3): 522-552.

Ventura J A, Golany B, Mendoza A, et al. A multi-product dynamic supply chain inventory model with supplier selection, joint replenishment, and transportation cost [J]. Annals of Operations Research, 2022, 316(2): 729-762.

Goedhart J, Haijema R, Akkerman R. Inventory rationing and replenishment for an omni-channel retailer [J]. Computers & Operations Research, 2022, 140: 105647.

Adeinat H, Pazhani S, Mendoza A, et al. Coordination of pricing and inventory replenishment decisions in a supply chain with multiple geographically dispersed retailers [J]. International Journal of Production Economics, 2022, 248: 108461.

Zhao N, Wang Q, Wu J. Optimal pricing and ordering decisions with reference effect and quick replenishment policy [J]. International Transactions in Operational Research, 2022, 29(2): 1188-1219.

Wan G, Cao Y, Wang S. Evaluation of a joint replenishment policy with sales-based threshold and stochastic demand [J]. Computers & Industrial Engineering, 2022, 172: 108525.

Castellano D, Santillo L C. Stochastic joint replenishment problem under a fill rate constraint with controllable lead times and shared cost allocation [J]. Operations Research Letters, 2023, 51(4): 385-392.

Otero-Palencia C, Amaya-Mier R, Yie-Pinedo R. A stochastic joint replenishment problem considering transportation and warehouse constraints with gainsharing by Shapley value allocation [J]. International Journal of Production Research, 2019, 57(10): 3036-3059.

Lu Jing. Research on inventory control and dynamic pricing of fresh agricultural products [D]. Tianjin University, 2021.DOI:10.27356/d.cnki.gtjdu.2019.000182.