Asymmetry and Ambiguity in Newsvendor Models

@article{Natarajan2018AsymmetryAA,
  title={Asymmetry and Ambiguity in Newsvendor Models},
  author={Karthik Natarajan and Melvyn Sim and Joline Uichanco},
  journal={Manag. Sci.},
  year={2018},
  volume={64},
  pages={3146-3167}
}
A basic assumption of the classical newsvendor model is that the probability distribution of the random demand is known. But in most realistic settings, only partial distribution information is available or reliably estimated. The distributionally robust newsvendor model is often used in this case where the worst-case expected profit is maximized over the set of distributions satisfying the known information, which is usually the mean and covariance of demands. However, covariance does not… 
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References

SHOWING 1-10 OF 73 REFERENCES
Regret in the Newsvendor Model with Partial Information
TLDR
This paper derives the order quantities that minimize the newsvendor's maximum regret of not acting optimally, which can be extended to a variety of problems that require a robust but not conservative solution.
Newsvendor optimization with limited distribution information
TLDR
This model tries to minimize the regret that is defined as the ratio of the expected cost based on limited information to that based on complete information, called Relative Expected Value of Distribution (REVD), and shows how to derive an optimal solution to the REVD model.
Expected Value of Distribution Information for the Newsvendor Problem
TLDR
This paper aims at computing the maximum EVDI over all f ∈ F for any order quantity, and an optimization procedure is provided to calculate the order quantity that minimizes themaximum EVDI.
The Newsvendor Under Demand Ambiguity: Combining Data with Moment and Tail Information
TLDR
This work proves the proposed approach is (weakly) consistent under some technical regularity conditions and analytically characterize its rate of convergence, and develops theoretical and numerical results for the ambiguity-averse, repeated newsvendor setting.
A Maximum Entropy Approach to the Newsvendor Problem with Partial Information
TLDR
This paper considers the newsvendor model under partial information, i.e., where the demand distribution D is partly unknown, and shows that the average performance of the maximum entropy approach is considerably better than either minimax regret or Scarf's rule.
Technical Note - A Risk-Averse Newsvendor Model Under the CVaR Criterion
TLDR
A risk-averse newsvendor with stochastic price-dependent demand with Conditional Value-at-Risk (CVaR) as the decision criterion is considered to investigate the optimal pricing and ordering decisions in such a setting.
Distributionally robust multi-item newsvendor problems with multimodal demand distributions
TLDR
This work presents a risk-averse multi-dimensional newsvendor model for a class of products whose demands are strongly correlated and subject to fashion trends that are not fully understood at the time when orders are placed and demonstrates that disregarding ambiguity or multimodality can lead to unstable solutions that perform poorly in stress test experiments.
How Larger Demand Variability May Lead to Lower Costs in the Newsvendor Problem
TLDR
It is shown that there exist demand distributions for which the intuition is misleading, i.e., for which larger variances occur in combination with lower costs.
TRACTABLE ROBUST EXPECTED UTILITY AND RISK MODELS FOR PORTFOLIO OPTIMIZATION
TLDR
This paper derives exact and approximate optimal trading strategies for a robust (maximin) expected utility model, where the investor maximizes his worst‐case expected utility over a set of ambiguous distributions.
Technical Note - A Risk- and Ambiguity-Averse Extension of the Max-Min Newsvendor Order Formula
TLDR
This article provides and analyzes the newsvendor order quantity that maximizes the worst-case expected profit versus risk trade-off (risk-averse) when only the mean and standard deviation of the product's demand distribution are known (ambiguity- averse).
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