The planning of the operating rooms (ORs) is a difficult process due to the different
stakeholders involved. The real complexity, however, results from various sources of …

The restless multi-armed bandit problem is a paradigmatic modeling framework for optimal
dynamic priority allocation in stochastic models of wide-ranging applications that has been …

A new generation of healthcare operations management (HOM) scholars is studying timely
healthcare topics (eg, organization design, design of delivery, and organ transplantation) …

Secure messaging, or “e-visits,” between patients and providers has sharply increased in
recent years, and many hope they will help improve healthcare quality, while increasing …

We consider the multi-armed restless bandit problem (RMABP) with an infinite horizon
average cost objective. Each arm of the RMABP is associated with a Markov process that …

There has been a significant increase in the scale and scope of humanitarian efforts over the
last decade. Humanitarian operations need to be—rapid, impactful, sustained, and efficient …

We consider the online restless bandits with average-reward and multiple actions, where the
state of each arm evolves according to a Markov decision process (MDP), and the reward of …

This paper seeks an efficient way to screen a population of patients at risk for hepatocellular
carcinoma when (1) each patient's disease evolves stochastically and (2) there are limited …

Many settings involve sequential decision making where a set of actions can be chosen at
each time step, each action provides a stochastic reward, and the distribution for the reward …

We study a finite-horizon restless multi-armed bandit problem with multiple actions, dubbed
as R (MA)^ 2B. The state of each arm evolves according to a controlled Markov decision …