The single-period (newsvendor) problem under interval grade uncertainties

Min Guo, Yu-Wang Chen, Hongwei Wang, Jian-Bo Yang, Keyong Zhang

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Traditional stochastic inventory models assume to have complete knowledge about the demand probability distribution. However, in reality it is often difficult to characterize demand precisely, especially with limited historical data or through subjective forecasting. In this paper, we aim to develop a consistent framework of formulating demand uncertainties in single-period (newsvendor) problems, where a set of discrete assessment grades and/or grade intervals are used to represent complex uncertainties in both quantitative and qualitative evaluations. In this uncertainty formulation framework, we use random set theory to study optimal ordering policies for the newsvendor problem under optimistic, pessimistic, minimum regret and maximum entropy criteria respectively. Numerical studies are conducted to illustrate the effectiveness of the proposed approach.
Original languageEnglish
Pages (from-to)198-216
Number of pages9
JournalEuropean Journal of Operational Research
Issue number1
Early online date7 Aug 2018
Publication statusPublished - 16 Feb 2019


  • Inventory
  • Decision analysis
  • Uncertainty expression


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