IE SEMINAR: Maintaining Fairness in Stochastic Chemotherapy Scheduling

Guest: Dr. Serhat Gül

Title: Maintaining Fairness in Stochastic Chemotherapy Scheduling

Date:  January 17, 2024@10:00AM 

Location: FENS G032 (physical only)

Abstract: Chemotherapy scheduling is hard to manage under uncertainty in infusion durations, and focusing on  expected performance measure values may lead to unfavorable outcomes for some patients. In this  study, we aim to design daily patient appointment schedules considering a fair environment regarding  patient waiting times. We propose using a metric that encourages fairness and efficiency in waiting time  allocations. To optimize this metric, we formulate a two-stage stochastic mixed-integer nonlinear  programming model. We employ a binary search algorithm to identify the optimal schedule, and then  propose a modified binary search algorithm (MBSA) to enhance computational capability. Moreover, to  address stochastic feasibility problems at each MBSA iteration, we introduce a novel reduce-and  augment algorithm that utilizes scenario set reduction and augmentation methods. We use real data  from a major oncology hospital to show the efficacy of MBSA. We compare the schedules identified by  MBSA with both the baseline schedules from the oncology hospital and those generated by commonly  employed scheduling heuristics. Finally, we highlight the significance of considering uncertainty in  infusion durations to maintain fairness while creating appointment schedules. 

Bio: Serhat Gul completed his B.Sc. in Industrial Engineering at Sabanci University in 2006, and his M.Sc. and  PhD in Industrial Engineering at Arizona State University in 2007 and 2010, respectively. He is currently a  visiting assistant professor at the Operations & Information Management Department in the Isenberg  School of Management at the UMass Amherst. Previously, he worked as an assistant professor at the  Department of Industrial Engineering at TED University, a visiting faculty in Industrial Engineering at  Sabancı University, a postdoctoral research fellow at the Healthcare Systems Engineering Institute at  Northeastern University, and a National Institute of Health Postdoctoral Fellow at the School of  Industrial and Systems Engineering at Georgia Tech.  

Dr Gul's primary research interests include stochastic optimization and its applications to health care  delivery systems and public health planning. His articles appeared in journals including INFORMS Journal  on Computing, POM, NRL, EJOR, OMEGA, Service Science, and Flexible Services and Manufacturing  Journal. 

He taught courses at several universities including UMass Amherst, Georgia Tech, Northeastern