Theoretical and Natural Science

- The Open Access Proceedings Series for Conferences


Theoretical and Natural Science

Vol. 34, 10 May 2024


Open Access | Article

Automatic pricing and replenishment decision-making for vegetable products based on optimization models

Yifan Chen 1 , Zhong Zheng 2 , Xiaoya Wang 3 , Ziqi Meng 4 , Jiayao Li * 5
1 Hebei University of Economics and Business
2 Hebei University of Economics and Business
3 Hebei University of Economics and Business
4 Hebei University of Economics and Business
5 Hebei University of Economics and Business

* Author to whom correspondence should be addressed.

Theoretical and Natural Science, Vol. 34, 284-290
Published 10 May 2024. © 2023 The Author(s). Published by EWA Publishing
This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Citation Yifan Chen, Zhong Zheng, Xiaoya Wang, Ziqi Meng, Jiayao Li. Automatic pricing and replenishment decision-making for vegetable products based on optimization models. TNS (2024) Vol. 34: 284-290. DOI: 10.54254/2753-8818/34/20241181.

Abstract

Addressing the replenishment and pricing issues of vegetable products is crucial for ensuring product quality and freshness, optimizing sales combinations, refining pricing strategies, and enhancing operational efficiency. Through scientific data analysis and decision-making, supermarkets can better meet consumer demands, enhance competitiveness, and achieve sustainable development. This paper discusses the complex issues of procurement and pricing of fresh vegetable products in current supermarkets. It employs methods such as hierarchical clustering analysis, Topsis evaluation, and optimization models to construct data models, establishing multiple models to address replenishment and pricing decision-making from various perspectives. The research indicates, firstly, the paper categorizes vegetable products into four clusters, explores complementary and substitute products within them, and discovers that reasonable sales combinations among different types of single products can mutually promote sales, leading to higher economic benefits for supermarkets. Secondly, the paper derives a mathematical model describing the relationship between total profit, total sales volume of individual products, and pricing. This model provides valuable recommendations for supermarkets’ replenishment and pricing decisions, ensuring practical implementation of pricing and replenishment plans. Thirdly, the paper establishes a model for maximizing profits under constant replenishment quantities, assisting supermarkets in formulating more scientific replenishment plans for individual products within a limited number of available items. By judiciously applying the innovative mathematical models presented in this paper, supermarkets can obtain reliable market analysis and make corresponding replenishment and pricing decisions.

Keywords

Optimization Models, Hierarchical Clustering Analysis, Topsis Evaluation

References

1. Cui, K. F. (Year not provided). Design and Implementation of Supermarket Commodity Management System.

2. Liu, L. P., Ding, J. J., & Qin, T. (2001). Application of Regression Analysis in Beverage Sales Forecasting. Statistics and Forecasting, 2001(06).

3. Huang, X. M. (2013). Application of Simple Linear Regression Analysis in Supermarket Product Sales. Science and Technology Information, 2013(11).

4. R.J. Kuo; K.C. Xue. A decision support system for sales forecasting through fuzzy neural networks with asymmetric fuzzy weights. [J]. Decision Support Systems.1998(2)

5. Philip Doganis; Alex Alexandridis; Panagiotis Patrinos; Haralambos Sarimveis. Time series sales forecasting for short shelf-life food products based on artificial neural networks and evolutionary computing. [J]. Journal of Food Engineering.2005(2)

Data Availability

The datasets used and/or analyzed during the current study will be available from the authors upon reasonable request.

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Volume Title
Proceedings of the 3rd International Conference on Computing Innovation and Applied Physics
ISBN (Print)
978-1-83558-369-2
ISBN (Online)
978-1-83558-370-8
Published Date
10 May 2024
Series
Theoretical and Natural Science
ISSN (Print)
2753-8818
ISSN (Online)
2753-8826
DOI
10.54254/2753-8818/34/20241181
Copyright
10 May 2024
Open Access
This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited

Copyright © 2023 EWA Publishing. Unless Otherwise Stated