基于价格弹性的蔬菜类商品自动定价与补货决策  

Automatic Pricing and Replenishment Decisions for Vegetable Products Based on Price Elasticity

作　　者：聂森 潘萱颖 曲浩栋 NIE Sen;PAN Xuanying;QU Haodong(School of Cyber Science and Engineering,Wuhan University,Wuhan,Hubei 430072,China;School of Electrical Engineering and Automation,Wuhan University,Wuhan,Hubei 430072,China;School of Remote Sensing and Information Engineering,Wuhan University,Wuhan,Hubei 430072,China)

机构地区：[1]武汉大学国家网络安全学院,湖北武汉430072 [2]武汉大学电气与自动化学院,湖北武汉430072 [3]武汉大学遥感信息工程学院,湖北武汉430072

出　　处：《数学建模及其应用》2024年第2期66-72,共7页Mathematical Modeling and Its Applications

摘　　要：对于生鲜商超,在尽量满足市场需求的前提下,实现商超收益最大的补货量和定价策略尤为重要.本文探究了蔬菜销量与成本加成定价的关系,选取需求价格弹性的经济学指标,构建双对数需求模型对价格弹性进行估计,基于此建立价格弹性修正函数,对LSTM模型预测出的销量与定价进行修正.为确定各蔬菜品类未来一周的日补货总量与定价策略,建立了收益最大化模型,并通过GBest-PSO算法求解.为确定满足特定需求下各蔬菜单品单日的补货总量与定价策略,根据过去一周的可售品种,采用VIKOR评价方法量化蔬菜单品的需求,建立需求与收益最大化的双目标优化决策模型,通过NSGA-Ⅱ非支配排序遗传算法求解,并在Pareto前沿解中确定了最优方案.Fresh food supermarkets must balance profit maximization with meeting market demand by optimizing replenishment volumes and pricing strategies.This study examines the relationship between vegetable sales and cost-plus pricing,focusing on key economic indicators to estimate demand price elasticity.A double-log demand model refines predictions from an LSTM model,ensuring accurate sales volume and pricing forecasts.For weekly planning,a revenue maximization model is formulated and solved using the GBest-PSO algorithm to determine optimal daily category replenishment and pricing strategies.To tailor daily decisions,the VIKOR method evaluates individual vegetable demand based on past sales data,considering both demand satisfaction and revenue generation.A dual-objective optimization model is established to maximize both demand satisfaction and revenue,with the NSGA-II algorithm yielding Paretooptimal solutions.

关 键 词：需求价格弹性 LSTM模型 VIKOR评价 NSGA-Ⅱ算法 

分 类 号：O29[理学—应用数学]