Optimization Study on Replenishment and Pricing Strategies for Vegetable Commodities
DOI:
https://doi.org/10.54097/m4ww2y41Keywords:
Iterative algorithm, differential evolutionary algorithm, single-objective nonlinear programming, time series models.Abstract
In the face of diverse consumer demand and fierce market competition, it is crucial to optimize replenishment and pricing strategies for perishable vegetables, aiming at scientific and efficient management to maximize revenue. This article visualized and analyzed recent sales data with incoming prices and wastage rates. A time series model was utilized to predict sales trends and develop a purchasing plan. Considering the transportation loss, we choose to sell at a discount. For the treatment of selling price, we use the selling price of the last three years as the initial selling price, and then optimize the up and down fluctuation of the selling price by using single-objective nonlinear programming and differential evolution method to maximize the profit. These strategies help to meet customer needs, enhance satisfaction and loyalty, optimize cost control and supply chain management, enhance market competitiveness, flexibly respond to market fluctuations, and reduce operational risks. An in-depth study of these strategies is crucial for the sustainable development of supermarkets.
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