Speaker: Serhat Gül (TED University)
Title: Scheduling surgery requests from outdoctors and indoctors under uncertainty
Date: 20 February 2026, Friday
Time: 13:30-14:30
Place: EA409
Abstract: Hospitals increasingly allow surgeons who are not full-time employees (outdoctors) to rent operating rooms (ORs) to generate revenue. However, to have their surgeries scheduled, outdoctors need to compete with the full-time hospital-employed surgeons of the hospital (indoctors) for limited resources. Balancing the needs of both surgeon types while accounting for uncertainty in surgery durations creates a challenging surgery planning problem. To address this problem, we formulate a stochastic mixed-integer programming model to select outdoctor surgery requests and schedule both indoctor and selected outdoctor surgeries across ORs and days within a finite planning horizon. Key performance measures include revenue from accepted outdoctor requests, and cost of patient waiting times, and that of expected OR overtime and idle time. To solve the model, we propose a problem-based scenario reduction algorithm based on loss function minimization (LFM). We solve the LFM problem using both a mixed-integer second-order cone programming model and a sub-gradient-based heuristic. As the heuristic provides near-optimal solutions within reasonable time, we adopt it for further experiments using real surgery duration data. We compare our scenario reduction algorithm against three alternatives from the literature. Additionally, we provide insights into the benefits of incorporating outdoctor surgeries into hospital surgery planning and exploring different levels of flexibility in handling these requests. Finally, we perform sensitivity analyses on various model parameters and estimate the value of the stochastic solution.
Bio: Dr. Serhat Gül is an Associate Professor of Industrial Engineering at TED University. He received his Ph.D. and M.Sc. degrees in Industrial Engineering from Arizona State University in 2010 and 2007, respectively, and his B.Sc. from Sabancı University in 2006. He worked as a postdoctoral research fellow at Georgia Institute of Technology and Northeastern University before joining TED University. Recently, he was a visiting professor at the Isenberg School of Management, University of Massachusetts Amherst, during 2023–2024. Dr. Gül’s primary research interests include stochastic optimization and its applications in health care delivery systems. He recently published a book on chemotherapy appointment scheduling with Springer Nature. His articles appeared in journals including INFORMS Journal on Computing, Production and Operations Management, Naval Research Logistics, European Journal of Operational Research, Omega, Service Science, and others.