Distributed research and development (R&D) plays a pivotal role in high-end equipment
manufacturing enterprises, significantly impacting interdisciplinary innovation and …

We study robust single-machine batch scheduling problems under uncertain processing
times to minimize total flow time. Two types of batches are considered: serial batch (s-batch) …

We introduce a novel adversarial model for scheduling with explorable uncertainty. In this
model, the processing time of a job can potentially be reduced (by an a priori unknown …

We study single-machine scheduling of jobs, each belonging to a job type that determines
its duration distribution. We start by analyzing the scenario where the type characteristics are …

Although many firms have deployed Internet of Things (IoT)-based diagnostics to predict
equipment failures and maintenance requirements, they receive imperfect demand signals …

Simple and affordable testing tools are often not accurate enough to be operationally
relevant. For coronavirus disease 2019 (COVID-19) detection, rapid point-of-care tests are …

In service systems with heterogeneous customers, prioritization with respect to the relative
importance of customers is known to improve certain performance measures. However, in …

Motivated by diverse application areas such as healthcare, call centers, and crowdsourcing,
we consider the design and operation of service systems that process tasks with types that …

Recent work in healthcare operations provide empirical evidence for the deterioration of
service quality due to congestion. Motivated by these findings, we formulate a novel …

This paper studies a canonical general scheduling model that captures the fundamental
trade-off between processing jobs and performing diagnostics (testing). In particular, testing …