Scheduling elective surgery patients considering time-dependent health urgency: Modeling and solution approaches

Abstract This paper describes an operating room planning problem in which patients have different severity levels when they are diagnosed, and patient health condition deteriorates with the increase of waiting time. In addition, uncertainty in surgery durations is incorporated in this problem. A stochastic mixed integer program is proposed to optimize the assignment of surgeries considering the worst patient health condition among all patients waiting for surgeries and total overtime that exceeds the available time durations allotted for surgeries. This paper presents three solution approaches: the sample average approximation method, a fastest ascent local search, and a tabu search. These three solution approaches are evaluated in the computational study and the results show that the tabu search provides effective solutions within reasonable computation times.