A new model for operating room scheduling with elective patient strategy. Issue 2 (3rd May 2021)

• Record Type: Journal Article
• Authors: Kayvanfar, Vahid; Akbari Jokar, Mohammad R.; Rafiee, Majid; Sheikh, Shaya; Iranzad, Reza
• Is Part Of: Infor. Volume 59:Issue 2(2021)
• Page Start: 309
• Page End: 332
• Publication Date: 2021-05-03
• Subjects: Scheduling operating rooms -- integer programming -- open scheduling -- Lagrangian relaxation -- sub-gradient; Operations research -- Periodicals; Electronic data processing -- Periodicals; Systems engineering -- Periodicals; Systems engineering; Electronic data processing; Periodicals; 003.05
• DOI: 10.1080/03155986.2021.1881359
• Languages: English
• ISSNs: 0315-5986

Abstract

Abstract: Hospitals are dealing with the daunting task of scheduling patients in operating rooms under a limited budget, time, and staff. This article finds the optimal schedule of surgeries by minimizing operating rooms' idle times while maximizing the number of scheduled surgeries during the most effective and desirable time windows. Surgeries during ideal time windows are encouraged by assigning bonus weights in the objective function. Stated and implied benefits of this strategy include mitigating financial loss, complications, and death rate due to a reduction in surgery delays. We introduce a binary programming model for scheduling operating rooms and a mixed integer binary program for planning and scheduling both operating and recovery rooms for elected patients under deterministic conditions. We apply an open scheduling strategy for assigning operating rooms to surgeons and a Lagrangian relaxation method for finding promising solutions. We move hard constraints to the objective to reduce the complexity of the proposed NP-hard model. We incorporate a sub-gradient method that selects the best penalty vector. Finally, we benchmark the results to evaluate the efficiency of the proposed solutions.