The objective of DDQC 2022 was to highlight and discuss contemporary approaches to the management of service systems, with a focus on data collection, methodological insights, and analysis of decision making. The recordings of the lectures are below. For a full overview of the speakers and abstracts, go to this page
Session 1
Rhonda Righter (University of California, Berkeley) – Robustness in Markov Matching Models
Kuang Xu (Standford University) – Information design for load balancing
Session 2
Amy Ward (The University of Chicago) – Learning the Scheduling Policy in Time-Varying Multiclass Many Server Queues with Abandonment
Adam Wierman (California Institute of Technology) – Learning & Control in Safety-Critical Systems
Tava Olsen (University of Auckland) – Time Is Money: Leadtime Quotation and Pricing in Make-to-order Environments
Session 3
Rouba Ibrahim (University College London) – Size-based scheduling in service systems
Nicolas Gast (INRIA Grenoble) – Restless bandits, weakly coupled MDPs and LP relaxations
Caroline Jagtenberg (Vrije Universiteit Amsterdam) – Modeling Emergency Medical Service Volunteer Response
Session 4
Harsha Honnappa (Purdue University) – The Sample Complexity of Offline Reinforcement Learning
Victor Araman (American University of Beirut) – Scheduled Traffic with Application to Queues
Session 5
Petar Momcilovic (Texas A&M University) – A Probabilistic Approach to Growth Networks
Christos Zacharias (University of Miami) – Dynamic Interday and Intraday Scheduling
Michael O’Sullivan (The University of Auckland) – Modern Tools for the Management of Healthcare Systems: modelling and AI in a digital future
Session 6
Melanie Reuter-Oppermann (Technical University of Darmstadt) – Recent topics in EMS logistics
Xinyun Chen (Chinese University of Hong Kong, Shenzhen) – Online Learning and Optimization for Queues with Unknown Demand Curve and Service Distribution
Chung Piaw Teo (National University of Singapore) – Online Flow Control: Theory and Application