蔬菜类商品自动定价与补货决策的建模研究

Modeling Study on Automatic Pricing and Replenishment Decisions for Vegetable Products

摘要: 基于时间序列分析、灰色预测模型与非线性规划等方法，对蔬菜类商品的自动定价与补货问题进行了系统研究。通过对数据的预处理和建模分析，验证了价格与销量之间的关联规律和分布特性，并结合销量预测结果制定了收益最大化的定价策略。同时，在补货决策中，通过灰色模型和优化模型的结合，综合考虑最低陈列量及历史定价区间等约束条件得出了科学合理的补货方案。此外，通过分析市场动态数据的采集背景，提出了数据的采集方向，这些数据为提升定价与补货决策的精准性提供了一定的支持。

Abstract: ^*通讯作者。This study systematically addresses the challenges of automatic pricing and restocking for vegetable commodities using methods such as time series analysis, grey prediction models, and nonlinear programming. By preprocessing data and constructing models, it verifies the relationship and distribution characteristics between price and sales. Based on sales forecasts, an optimal pricing strategy aimed at maximizing revenue is developed. For restocking decisions, a combination of grey forecasting and optimization models is applied, considering constraints such as minimum display requirements and historical pricing ranges, resulting in scientifically sound replenishment plans. Furthermore, an analysis of the background for collecting market dynamics data identifies key data collection directions. These data provide essential support for enhancing the accuracy of pricing and restocking decisions.