Vegetables, being an essential part of our daily lives, possess a limited shelf life, rendering the task of stock management crucial for supermarkets aiming to maximize profits. Current research on pricing and replenishment strategies, although existing, lacks the necessary computerization, intelligence, and speed, ultimately resulting in inefficient operations. To address this, the present study utilizes the Nerlove model, incorporates the inventory state transfer equation, and applies multivariate nonlinear regression to elucidate the relationship between price and expected supply. Factoring in storage conditions and expected supply reaction model constraints, a dynamic planning model is formulated. This model offers supermarkets a refined approach to pricing and replenishment decisions for vegetables. Implementing this decision-making framework not only enhances supply chain coordination and efficiency but also optimizes inventory management, ensures supply-demand balance, mitigates inventory wastage and out-of-stock situations, thereby boosting overall economic performance.

Yiner Zhu, Keyu Li. Intelligent Pricing Strategy Analysis for Vegetable Products Using Single-objective Optimization. International Journal of New Developments in Engineering and Society (2024) Vol.8, Issue 2: 28-36. https://doi.org/10.25236/IJNDES.2024.080205.

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