We consider a repeated newsvendor problem in which the decision maker (DM) does not
have access to the underlying demand distribution. The goal of this paper is to characterize …

We consider the data-driven newsvendor problem in which a manager makes inventory
decisions sequentially and learns the unknown demand distribution based on observed …

Consider the newsvendor model, but under the assumption that the underlying demand
distribution is not known as part of the input. Instead, the only information available is a …

This paper investigates the effect of demand censoring on the optimal policy in newsvendor
inventory models with general parametric demand distributions and unknown parameter …

Motivated by data from a large European retail chain, we tackle the newsvendor problem
with censored demand observations by a distribution-free model based on a data-driven …

Traditional stochastic inventory models assume full knowledge of the demand probability
distribution. However, in practice, it is often difficult to completely characterize the demand …

In this paper, we consider the newsvendor model under partial information, ie, where the
demand distribution D is partly unknown. We focus on the classical case where the retailer …

We study the classical newsvendor problem in which the decision maker must trade off
underage and overage costs. In contrast to the typical setting, we assume that the decision …

In the newsvendor problem, a decision maker facing random demand for a perishable
product decides how much of it to stock for a single selling period. This simple problem with …

We study a risk‐averse newsvendor problem where demand distribution is unknown. The
focal product is new, and only the historical demand information of related products is …