Regret in the Newsvendor Model with Partial Information

By Georgia Perakis, Guillaume Roels. Operational Research, 2008

368 citations recorded by the source corpus.

Subfields: Management Information Systems, Management Science and Operations Research

View Paper: https://www.semanticscholar.org/paper/45630689b19024b2541024f4c5133c2801e3a4a8

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In Management Information Systems

In Management Science and Operations Research

Citations in the corpus

Regret in the Newsvendor Model with Demand and Yield Randomness (2021, methodology): “Indeed, this is an existing result on the optimal minimax regret order quantity when only the range (or support) of the demand distribution is known; see for example, theorem 1 in Perakis and Roels (2008).”
The Big Data Newsvendor: Practical Insights from Machine Learning (2013, background): “Perakis and Roels (2008) considered a minimax regret approach for the newsvendor with partial information about the demand distribution.”
Distributionally Robust Optimization: A Review (2019, methodology): “Perakis and Roels [228] also study the ambiguity sets that preserve the shape of the distribution, including”
Robust Solutions of Optimization Problems Affected by Uncertain Probabilities (2013, positive): “Perakis and Roels [34] study regret in newsvendor models in which only partial information is given, for example, mean, variance, symmetry, or unimodality.”
Pricing Without Priors (2008, neutral): “Prepared for the 2007 Meetings of the European Economic Association. yDepartment of Economics, Yale University, New Haven, CT 06511, dirk.bergemann@yale.edu. zDepartment of Economics and Business, Universitat Pompeu Fabra, E-08005 Barcelona, karl.schlag@upf.edu 1 2”
Stochastic Stackelberg Equilibria with Applications to Time Dependent Newsvendor Models (2013, neutral): “Hence by (19) we get the following first order conditions for the optimal values q̂t = φ1(t, ŵ(t)), R̂t = φ2(t, ŵ(t)): E [ (R̂t − S)X[0,Dt](q̂t)− wt + S ∣∣Et] = 0 (35)”
Production, Manufacturing and LogisticsConfidence-based optimisation for the newsvendor problem under binomial, Poisson and exponential demand (2014, positive): “The class of the distribution may be determined, for instance, by selecting the maximum entropy distribution that matches the structure of the demand process at hand (see also the discussion in Perakis and Roels [2008] p. 190).”