Stochastic simulation is an invaluable tool for operations-research practitioners for the
performance evaluation of systems with random behavior and mathematically intractable …

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 …

The inventory control literature generally assumes that the demand distribution and all its
parameters are known. In practical applications it is often suggested to estimate the demand …

Abstract Around 30% to 70% of products in retail and services experience low demand,
including spare parts and components for nearly all types of machinery and equipment …

In this article, we describe representative contributions in several major application areas of
data analytics in operations management to summarize the recent development, discuss the …

We study the data-integrated, price-setting newsvendor problem in which the price–demand
relationship is described by some parametric model with unknown parameters. We develop …

Motivated by the real-world problem of a logistics company, this paper proposes a novel
distribution-free prescriptive analytics approach—termed kernelized empirical risk …

Motivated by a unique agribusiness setting, this paper develops an optimization-based
approach to estimate the mean and standard deviation of probability distributions from noisy …

We introduce a novel strategy to address the issue of demand estimation in single-item
single-period stochastic inventory optimisation problems. Our strategy analytically combines …

As increasingly more shop-floor data becomes available, the performance of a production
system can be improved by developing effective data-driven control methods that utilize this …