Robust Optimization for the Loss-Averse Newsvendor Problem

Hui Yu (), Jia Zhai () and Guang-Ya Chen ()
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Hui Yu: Chongqing University
Jia Zhai: Chongqing University of Technology
Guang-Ya Chen: Chinese Academy of Sciences

Journal of Optimization Theory and Applications, 2016, vol. 171, issue 3, No 14, 1008-1032

Abstract: Abstract 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.

Keywords: Robust optimization; Newsvendor problem; Loss aversion; 62G35; 90C46; 90C47 (search for similar items in EconPapers)
Date: 2016
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Citations: View citations in EconPapers (3)

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DOI: 10.1007/s10957-016-0870-9

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