OPERATIONAL SPARE PARTS DECISION MAKING WITH DEEP REINFORCEMENT LEARNING

DOUNIEL LAMGHARI-IDRISSI

Biography
Douniel Lamghari-Idrissi worked in emergency response services and in the pharmaceutical industry. He joined ASML Netherlands B.V. in 2013, and he works in customer support. He is also a part-time assistant professor at the department of industrial engineering and innovation sciences at Eindhoven University of Technology. His current research topic is the design of after-sales services that lead to more stable operations for the asset users.

WILLEM VAN JAARSVELD

Biography
Willem van Jaarsveld is Associate Professor in Stochastic Optimization and Machine Learning at Eindhoven University of Technology (TU/e), in the OPAC group. His main research interest is applications of stochastic optimization in supply chain and logistics, using a diverse set of methodologies including Deep Reinforcement Learning, Stochastic Programming and Dynamic Programming. Apart from working towards scientific impact, he aims to make an impact in practice by working with companies to facilitate the implementation of the methods he develops. His research has been applied at various companies, including Shell Global solutions and Fokker Services.

Abstract
Supply chain disruptions have dramatically increased in the recent past. These disruptions create the need for a more optimal way of making stock allocation decisions. We will discuss how ASML and TU/e are partnering to overcome these challenges using deep reinforcement learning.