报告题目：Intraday Scheduling with Patient re-entries and Variabilities in Patient Behaviours
报 告 人：周明龙
Minglong Zhou is currently a fifth year PhD candidate at the Department of Analytics and Operations at National University of Singapore (NUS) Business School. He received his Bachelor of Engineering from Singapore University of Technology and Design (SUTD) with a major in Business Analytics in 2016. His research is broadly in the area of Operations Research and Operations Management with a focus on decision making under uncertainty. His research is interdisciplinary and draws upon the fields of robust optimization, robustness optimization, data-driven optimization, and machine learning. His research has been accepted by Manufacturing & Service Operations Management.
We consider common sources of uncertainties in Orthopaedic clinics, such as patient same-day re-entry, walk-ins, no-shows, and uncertain arrival times, in an intraday scheduling problem. We use a novel construction to model the patient flow and propose a tractable robustness optimization formulation, which minimizes a risk index representing the chance of violating performance targets, such as patient waiting times. To the best of our knowledge, this is the first model that incorporates all abovementioned sources of uncertainties. Our model achieves significant reductions, in comparative studies against a sample average approximation (SAA) model, on patient waiting times while keeping server overtime constant. Our simulations further characterize the types of uncertainties under which SAA performs poorly.