The ability to understand and explain the outcomes of data analysis methods, with regard to
aiding decision-making, has become a critical requirement for many applications. For …

This work investigates the application of Multi-Agent Deep Reinforcement Learning
(MADRL) on decentralized inventory management problems with multiple echelons …

Advances in computational power and AI have increased interest in reinforcement learning
approaches to inventory management. This paper provides a theoretical foundation for …

Commercial AI solutions provide analysts and managers with data-driven business
intelligence for a wide range of decisions, such as demand forecasting and pricing …

Simulating a single trajectory of a dynamical system under some state-dependent policy is a
core bottleneck in policy optimization algorithms. The many inherently serial policy …

The boom of the e-commerce industry in recent years prompts the focus of inventory
management into large-scale problems with multiple products and multi-echelon supply …

We consider decentralized proactive transshipment between multiple locations where each
retailer aims to maximize their profit by deciding jointly on ordering and transshipment. To …

ASML's customer service network aims to ensure timely availability of the materials needed
for machine maintenance. Most operational decisions in this network are automated by the …