Robust Optimization for the Loss-Averse Newsvendor Problem

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• 作者：Hui Yu ; Jia Zhai ; Guang-Ya Chen
• 关键词：Robust optimization ; Newsvendor problem ; Loss aversion
• 刊名：Journal of Optimization Theory and Applications
• 出版年：2016
• 出版时间：December 2016
• 年：2016
• 卷：171
• 期：3
• 页码：1008-1032
• 全文大小：
• 刊物主题：Calculus of Variations and Optimal Control; Optimization; Optimization; Theory of Computation; Applications of Mathematics; Engineering, general; Operation Research/Decision Theory;
• 出版者：Springer US
• ISSN：1573-2878
• 卷排序：171

文摘

In economics and decision theory, loss aversion refers to people’s tendency to strongly prefer avoiding losses to acquiring gains. Many studies have revealed that losses are more powerful, psychologically, than gains. We initially introduce loss aversion into the decision framework of the robust newsvendor model, to provide the theoretical guidance and referential decision for loss-averse decision makers when only the mean and variance of the demand distribution are known. We obtain the explicit expression for the optimal order policy that maximizes the loss-averse newsvendor’s worst-case expected utility. We find that the robust optimal order policy for the loss-averse newsvendor is quite different from that for the risk-neutral newsvendor. Furthermore, the impacts of loss aversion level on the robust optimal order quantity and on the traditional optimal order quantity are roughly the same.