A study on vegetable commodity replenishment considering single item quantity limitations—based on gray prediction and linear regression modeling
DOI: 10.23977/acss.2023.070916 | Downloads: 7 | Views: 317
Author(s)
Doudou Zhang 1, Xuemei Xiang 1, Jinyi Yang 1
Affiliation(s)
1 Bussiness College, Southwest University, Chongqing, 402460, China
Corresponding Author
Doudou ZhangABSTRACT
Data elements are beginning to play an important role in the selling of vegetable items in supermarkets. In order to get the best pricing and replenishment strategy under the limitation of the number of vegetable items, this paper firstly calculates the profit contribution rate of each item and sorts out the top 33 available items, and prioritizes the items with the top profit contribution rate for replenishment. Finally, a linear programming model is developed to solve the pricing strategy for maximizing the revenue of the superstore under the constraints of display quantity and weight of individual products.
KEYWORDS
GM(1,1) Model, Linear Programming, Pricing Strategy, Replenishment StrategyCITE THIS PAPER
Doudou Zhang, Xuemei Xiang, Jinyi Yang, A study on vegetable commodity replenishment considering single item quantity limitations—based on gray prediction and linear regression modeling. Advances in Computer, Signals and Systems (2023) Vol. 7: 121-129. DOI: http://dx.doi.org/10.23977/acss.2023.070916.
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