基于GM(1,1)模型与遗传算法的蔬菜定价与补货策略研究
Research on Vegetable Pricing and Replenishment Strategies Based on GM(1,1)Model and Genetic Algorithm
张懿杭 1赵杰 1张进文1
作者信息
- 1. 中国矿业大学(北京)理学院,北京 100083
- 折叠
摘要
合理订购和销售蔬菜类商品是商家实现收益最大化的重要研究课题.计算Spearman相关系数发现,蔬菜各品类销售量之间有着较强的正相关性;利用高斯函数进行回归拟合发现,蔬菜各品类销售总量与销售价格大致呈负相关.使用灰色预测GM(1,1)模型预测蔬菜各品类未来7日的定价和销售量,同时构建基于多目标规划与遗传算法的商家利润优化模型来研究并给出商家未来7日的单品补货量和定价策略.
Abstract
Reasonably ordering and selling vegetable products is an important research topic for businesses to achieve maximum revenue.Calculating the Spearman correlation coefficient,it was found that there is a strong positive correlation between the sales volume of various categories of vegetables.Using Gaussian function for regression fitting,it was found that the total sales volume of various categories of vegetables is roughly negatively correlated with the sales price.Using the GM(1,1)model to predict the pricing and sales volume of various vegetable categories in the next 7 days,and constructing a business profit optimization model based on multi-objective programming and genetic algorithm to study and provide the single item replenishment volume and pricing strategy of businesses in the next 7 days.
关键词
Spearman相关系数/GM(1/1)模型/多目标规划/遗传算法Key words
Spearman correlation coefficient/GM(1/1)model/multi-objective programming/genetic algorithm引用本文复制引用
基金项目
中国矿业大学(北京)大学生创新训练项目(No.202307006)
出版年
2024
NETL
NSTL
万方数据