稀缺价格与需求数据驱动的风险规避报童决策  

Scarce Price and Demand Data Driven Risk-averse Newsvendor Decisions

作　　者：赵梦蝶 王长军[1] 周赛玉 Zhao Mengdie;Wang Changjun;Zhou Saiyu(Glorious Sun School of Business and Management,Donghua University,Shanghai 200051,China)

机构地区：[1]东华大学旭日工商管理学院,上海200051

出　　处：《中国管理科学》2025年第2期232-241,共10页Chinese Journal of Management Science

基　　金：国家自然科学基金重点项目(71832001);教育部人文社科规划基金项目(24YJAZH166);上海市自然科学基金项目(20ZR1401900);上海市哲学社会科学规划基金项目(2019BGL036);中央高校基本科研业务费专项资金服务管理与创新基地资助项目(2232018H-07)。

摘　　要：本文研究价格和需求双随机变动下的数据驱动报童决策。其中,考虑决策者可利用的价格和需求历史数据是稀缺的,以及决策者可能具有的风险态度。为此,基于条件风险价值(CVaR)度量,构建两种稀缺数据驱动的鲁棒报童模型:分布式鲁棒CVaR模型和鲁棒Copula-CVaR模型,并分别给出了等价的半定规划和线性规划形式。最后,将两者与现有的Copula-CVaR模型进行仿真比较。结果表明:随着风险容忍程度的降低,决策者趋向规避风险,此时三种模型的最优订货量均下降;且在同一风险程度下,分布式鲁棒CVaR模型给出的订货量最为保守。此外,样本外测试集结果显示:在市场表现上,两种鲁棒模型均优于已有模型。其中,当决策者风险容忍程度较高时,分布式鲁棒CVaR更优;反之,鲁棒Copula-CVaR更优。在市场结果预估上,分布式鲁棒CVaR总体最好。The decision-making of single-period optimal ordering quantity under uncertain setting is a critical issue which has been widely applied.The classic newsvendor model considers uncertain demand that follows an available demand distribution,to optimize the expected benefit or cost.However,not only demand,but also price,are uncertain in practice.Because of the rapidly changing market conditions and shorter product life cycles,demand and price fluctuations becomes more significant.Thus,the data that decisions require is scarce in such setting.Therefore,the scarce-data-driven newsvendor problem under two random variables,i.e.,price and demand,is studied here.Both the data scarcity and the risk attitude of decision makers are taken into account.The Conditional Value-at-Risk(CVaR)criteria is adopted to capture the risk tolerance,and two scarce-data-driven robust newsvendor models are proposed.The first model,namely the robust-Copula model,is developed by considering possible Copula functions.The tractable linear programming equivalence is developed by discretizing the proposed model.The second one is a moment-based distributionally robust model which is based on the ambiguity set under the given mean and variance.The equivalent semi-definite program⁃ming is reformulated by dualization.A simulation experiment is performed and the two robust models are compared with the classic Copula-CVaR model.The results show that,as the decision maker’s risk tolerance decreases,the optimal ordering quantity of all three models decreases.Under the same risk tolerance,the optimal ordering quantity given by the distributionally robust model is the most conservative.Moreover,to simulate future markets,three sets of out-of-sample are generated by using Normal,Gamma and Uniform distributions,and an out-of-sample test is conducted.It is found that the two robust models perform better than the Copula-CVaR model in terms of market performance.To be specific,when the decision maker’s risk toler⁃ance is high,the distributionally robust m

关 键 词：稀缺数据驱动 报童模型 条件风险价值 分布式鲁棒 鲁棒Copula 

分 类 号：C934[经济管理—管理学]