Data have been utilised in production research in meaningful ways for decades. Recent
years have offered data in larger volumes and improved quality collected from diverse …

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

Data driven optimisation has become one of the research frontiers in operations
management and operations research. Likewise, the recent academic interest in big data …

In the operations research literature, data driven analyses using big data are receiving more
and more interest and attention. However, big data driven operational analyses are still …

When we use simulation to assess the performance of stochastic systems, the input models
used to drive simulation experiments are often estimated from finite real-world data. There …

We consider an engineer-to-order production system with unknown yield. We model the
yield as a random variable which represents the percentage output obtained from one unit of …

Digital twins have become an important element in smart manufacturing. As any other
product, digital twins also have a lifecycle, starting from specifying the requirements of the …

This study proposes a simulation framework of procurement operations in the container
logistics industry that can support the development of dynamic procurement strategies. The …

The articles included in this dissertation are all related to the topic of predictive or
prescriptive analytics in operations management. We contribute to the literature on the topic …

Most of the literature on supply chain management assumes that the demand distributions
and their parameters are known with certainty. However, this may not be the case in practice …