Yulong Chen
ABSTRACT
With the continuous improvement of social productivity and the increasingly fierce market competition, supermarkets, as the main suppliers of vegetables, occupy a high proportion in commodity circulation. In order to improve supermarket profit effectively and meet market demand, a profit optimal solution model based on single product constraint was established. In order to maximize the profit function, the summation range of the function is changed to the number of restocked items on the day, and the sales quality and sales type of the goods are constrained. Combining the constraint conditions and the maximum profit objective equation, the optimal profit model based on single product replenishment and pricing was established. On July 1, 2023, the optimal profit situation using genetic algorithm is: net profit of 2678.98 yuan, sales of 677.35 kg. Combining the constraint conditions and the object equation of a single product, an optimal profit model based on the replenishment and pricing of a single product was established.
- Amirgaliyev B, Kuchanskyi O, Andrashko Y, A Dynamic Model of Profit Maximization for Carsharing Services: Astana, Republic of Kazakhstan [J].Urban Science, 2023, 7(3).Google Scholar
- Lv Yongwei, Zhang Ying. Cost-plus pricing [J]. Sales & Marketing,1996, (11):64.Google Scholar
- An Qi. Research on pricing of science and technology novelty search service based on cost plus pricing [J]. Library Research and Work, 2021, (10):25-31+24.Google Scholar
- Zhang Ziying, Zhou Bo. Variable cost pricing under Market economy [J]. Journal of Shenyang University, 2003, (03):57-59.Google Scholar
- Lu Y J. Research on dynamic pricing of high-quality fresh vegetables in Chinese supermarkets [D]. Beijing Jiaotong University, 2010.Google Scholar
- NilumindaO, EkanayakeU. The Novel Efficient Method to Solve Balanced and Unbalanced Profit Maximization in Transportation Problems [J]. American Journal of Mathematical and Computer Modelling, 2023, 8(2).Google Scholar
- Habiba M, Salah M A, René L. Nonlinear dynamic and chaos in a remanufacturing duopoly game with heterogeneous players and nonlinear inverse demand functions [J]. Journal of Difference Equations and Applications, 2023, 29(9-12): 1503-1515.Google ScholarCross Ref
- S. B B, Rajan B, Li L, Mathematical programming methods for reducing inequity due to stock-outs of pharmaceuticals in low-resourced regions using a mobile pharmacy [J]. Computers & Industrial Engineering, 2023, 182.Google Scholar
- Alves F O, Martins E S D, Ricardo S S D, ILS-based algorithms for the profit maximizing uncapacitated hub network design problem with multiple allocation [J]. Computers and Operations Research, 2023, 157.Google Scholar
- Jiawei C, Yingxin H. Optimized Design of a Squeezed-Branch Pile Group Based on an Improved Particle Swarm Algorithm [J]. Sustainability, 2023, 15(3).Google Scholar
Index Terms
- Pricing and replenishment decision of supermarket vegetables based on optimal profit planning model
Recommendations
Replenishment and Pricing Decision Model for Vegetables
BDEIM '23: Proceedings of the 2023 4th International Conference on Big Data Economy and Information ManagementIn fresh food supermarkets, vegetable commodities have a short shelf life and their quality deteriorates with the increase of selling time. Therefore, there is a situation that the variety, quantity, and price of vegetable commodities vary from day to ...
Research NoteUsing Basket Composition Data for Intelligent Supermarket Pricing
How can supermarkets use the vast data they have to design strategies to compete for large-basket shoppers, potentially their most profitable customers? We say, analyze the data to glean basket composition of heterogeneous consumers. Of theoretical and ...
Supermarket Competition: The Case of Every Day Low Pricing
Every Day Low Pricing EDLP strategy has proved to be a successful innovation resulting in higher profits to supermarkets adopting it in competition with Promotional Pricing PROMO. Conventional wisdom attributes this success either to lower costs or to ...
Comments