“蔬菜类商品的自动定价与补货决策”问题解析

Problem Analysis for Automatic Pricing and Replenishment Decisions of Vegetable Products

给出2023年“高教社杯”全国大学生数学建模竞赛C题“蔬菜类商品的自动定价与补货决策”的可行解法,并对赛题评阅中发现的问题作了简要的评述.该题旨在通过对6个典型蔬菜品类的交易数据进行分析,探索蔬菜类商品的订购和定价问题.蔬菜需求具有明显的时间趋势和价格敏感性,由于保鲜期短,通常采用每日补货的运营方式.首先,通过剥离销量的时间效应,揭示销量的分布规律、价格与销量的耦合关系以及品类之间的相关性;其次,利用随机优化,建立优化模型并对补货和定价策略进行求解;最后,基于成本预测并叠加销量的时间效应,得到最优的补货量和销售价格.

In this paper,the methods for solving"Automatic Pricing and Replenishment Decisions of Vegetable Products",the 2023 CUMCM problem C,is provided.Additionally,the paper provides an overview of comments and suggestions for contest papers.This problem aims to investigate the ordering and pricing decisions of vegetable products by analyzing transaction data from six vegetable categories.Vegetable demand shows clear trends over time and is sensitive to pricing,often requiring daily replenishment due to their short shelf life.The analysis starts with uncovering the distribution patterns of sales,the relationship between price and sales volume,and the interrelation between different vegetable categories by eliminating the time effect on sales volume.Subsequently,a stochastic optimization approach is employed to construct an optimization model and address strategies for replenishment and pricing.Finally,the optimal replenishment quantity and selling price are derived based on cost predictions and the incorporation of the time effect on sales volume.