Distributionally robust optimization of a newsvendor model under capital constraint and risk aversion

IF 4.1 2区 工程技术 Q2 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS Computers & Operations Research Pub Date : 2024-10-16 DOI:10.1016/j.cor.2024.106870
Jia Zhai , Hui Yu , Kai-Rong Liang , Kevin W. Li
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Abstract

This paper proposes a capital-constrained newsvendor model with risk aversion under a partially known demand distribution with only knowledge of its mean and variance. We adopt the robust conditional value-at-risk (RCVaR) to characterize the vendor’s risk aversion. Firstly, we obtain the closed-form RCVaR optimal order quantity that depends on the demand volatility level: When demand volatility is low, the vendor has four financing-ordering strategies contingent upon different capital levels. When demand volatility is medium, the vendor does not seek bank loans and is left with two ordering strategies. When demand volatility is high, the vendor does not bother placing an order at all. Then, we investigate the impact of capital constraint, risk aversion and demand volatility on the RCVaR optimal order quantity. Finally, we demonstrate the robustness of the RCVaR optimal ordering policy by numerical experiments based on both randomly generated and real-world data.
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资本约束和风险规避下新闻供应商模型的分布稳健优化
本文提出了一个资本受限的新闻供应商模型,该模型在部分已知需求分布(仅知道其均值和方差)下具有风险规避能力。我们采用稳健条件风险价值(RCVaR)来描述供应商的风险规避。首先,我们得到了取决于需求波动水平的闭式 RCVaR 最佳订货量:当需求波动性较低时,供应商有四种融资订货策略,取决于不同的资本水平。当需求波动性中等时,供应商不寻求银行贷款,只有两种订货策略。当需求波动较大时,供应商根本不需要下订单。然后,我们研究了资本约束、风险规避和需求波动对 RCVaR 最佳订货量的影响。最后,我们通过基于随机生成数据和实际数据的数值实验,证明了 RCVaR 最佳订货政策的稳健性。
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来源期刊
Computers & Operations Research
Computers & Operations Research 工程技术-工程:工业
CiteScore
8.60
自引率
8.70%
发文量
292
审稿时长
8.5 months
期刊介绍: Operations research and computers meet in a large number of scientific fields, many of which are of vital current concern to our troubled society. These include, among others, ecology, transportation, safety, reliability, urban planning, economics, inventory control, investment strategy and logistics (including reverse logistics). Computers & Operations Research provides an international forum for the application of computers and operations research techniques to problems in these and related fields.
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