We consider a single-period inventory problem with random demand with both directly
observable and unobservable features that impact the demand distribution. With the recent …

The newsvendor problem is one of the most basic and widely applied inventory models. If
the probability distribution of the demand is known, the problem can be solved analytically …

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 …

In retailer management, the Newsvendor problem has widely attracted attention as one of
basic inventory models. In the traditional approach to solving this problem, it relies on the …

Retailers that offer perishable items are required to make ordering decisions for hundreds of
products on a daily basis. This task is non-trivial because the risk of ordering too much or too …

This paper considers a multi-item newsvendor problem with a capacity constraint (Z). The
problem has already been addressed in the literature using the classical newsvendor …

Newsvendor problems (NVP) form a classical and important family of stochastic optimisation
problems. In this paper, we consider a data-driven method proposed recently by Ban and …

In this paper, a data-driven newsvendor problem is studied by mapping high-dimensional
and mixed-frequency features of historical data to replenishment decisions. Instead of …

We investigate the data-driven newsvendor problem when one has n observations of p
features related to the demand as well as historical demand data. Rather than a two-step …

For the newsvendor problem with ambiguous demand, it is known that integrating parameter
estimation and optimization using operational statistics leads to better solutions compared …