Two-Stage Robust Optimization with Applications in Health Care and Combinatorial Optimization

Abstract

The development of new robust optimization models is motivated by the need for risk-based decision making in health care operations. Surgery scheduling has attracted a great deal of attention due to its importance in health care outcomes and costs. We apply robust optimization theory to the surgery scheduling problem and downstream capacity planning problem to address important questions regarding the impact of uncertainty in surgery duration and length-of-stay (LOS) in the surgical intensive care units on hospital resource planning and scheduling operations.