We will analyze queueing models relevant for service systems, with most of our emphasis on the many-server queue. First, we will combine asymptotic analysis methodology with statistical learning techniques to develop data-driven operational policies with provably good performance. The focus will be on handling non-exponential inter-arrival, service, and reneging distributions. Second, we will study how to incorporate human behavior in many-server queueing models by using game theory methodology. Topics covered are listed week-by-week, starting from the second page.
