Abstract

Motivated by mass emergencies such as pandemics and earthquakes that result in a large number of patients requiring critical services, we study a feature-based scheduling problem with N patients waiting to be served by a decision maker. The decision maker knows each patient's features and waiting cost, but does not know how the expected service time depends on the patient features. After a patient is served, the decision maker observes the realized service time and determines which patient to serve next. We prove that the decision maker's expected regret, i.e., the difference between the expected total waiting cost of the decision maker and that of a clairvoyant who knows the patients' expected service times, is at least of order N^{3/2}. We then design a learn-then-commit policy and an uncertainty ellipsoid policy to dynamically learn the expected service times, and prove that the expected regrets of these two policies are of order N^{5/3} log^{1/2} N and N^{3/2} log^{3/2} N, respectively. Finally, we conduct simulation experiments and a case study based on real-world data from Duke University Hospital to demonstrate the practical value of our policies relative to commonly used approaches. (Paper available at SSRN: https://ssrn.com/abstract=4852356)

Speaker's Bio

Bora Keskin is an Associate Professor of Operations Management at Duke University’s Fuqua School of Business. His research focuses on data-driven decision making under uncertainty, with applications in dynamic pricing, revenue management, platform operations, and supply chain innovation. His recent work explores how emerging technologies—such as blockchain, IoT, and AI—are reshaping the future of operations. Bora received his Ph.D. from Stanford University. His work has been recognized with several awards, including the Lanchester Prize (2019) and the MSOM Young Scholar Prize (2024). Prior to joining Duke in 2015, he worked as a consultant at McKinsey & Company and served on the faculty of the University of Chicago Booth School of Business. At Fuqua, Bora teaches the MBA elective Value Chain Innovation in Business Processes, which emphasizes technological change and data-driven practices. He also teaches a Ph.D. course on revenue management and pricing. Outside Duke, he serves as an Associate Editor for Management Science and Operations Research, and as a Senior Editor for Production and Operations Management.