蔬菜类商品的自动定价与补货决策  

Automatic pricing and replenishment decision of vegetable commodities

作　　者：陈昊 王震雨 陈旭 朱锋 CHEN Hao;WANG Zhenyu;CHEN Xu;ZHU Feng(School of Mathematics and Statistics,Huaibei Normal University,Huaibei 235000,China)

机构地区：[1]淮北师范大学数学与统计学院,安徽淮北235000

出　　处：《高师理科学刊》2025年第1期17-23,共7页Journal of Science of Teachers'College and University

基　　金：安徽省校企合作科研项目(2024340603000008)。

摘　　要：制定蔬菜类商品的定价和补货决策机制使商超收益最大化,对不同蔬菜品类单品的各项数据进行分析拟合和预测.基于熵权法-Topsis模型先对构建的评价指标进行赋权,根据熵权法的评价指标权重选择可售单品种类,对于多元规划模型借助多目标粒子群优化算法进行求解.在尽量满足市场对各品类蔬菜需求的前提下,给出利益最大化的单品补货量与定价策略.In order to make the pricing and replenishment decision mechanism of vegetable commodities to maximize the profit of supermarket,the data of different vegetable categories are analyzed,fitted and predicted.Based on the Entropy-weighting TOPSIS method,the constructed evaluation indicators are weighted,and the marketable single varieties are selected according to the evaluation index weights of the entropy weight method.Then,the multi-objective particle swarm optimization algorithm is used to solve the multivariate programming model.On the premise of satisfying the market demand for various types of vegetables as far as possible,a single product replenishment quantity and pricing strategy to maximize the benefits is given.

关 键 词：蔬菜品类 成本加成定价 补货决策 Pearson相关系数 粒子群优化算法 

分 类 号：O22[理学—运筹学与控制论]