Large-scale decomposition strategies for collaborative operating room planning and scheduling


Operating rooms (ORs) play a substantial role in hospital profitability, and their optimal utilization is conducive to containing the cost of surgical service delivery, shortening surgical patient wait times, and increasing patient admissions. We extend traditional single-hospital operating room scheduling to a coalition of multiple collaborating hospitals in a strategic network. Using data from the University Health Network (UHN), in Toronto, Ontario, Canada, we propose new centralized approaches to elective and operating room scheduling when multiple collaborating hospitals are involved. We formulate the OR scheduling problem based on location-allocation problems in supply chain management. We ensure caseload balancing among collaborating hospitals in macro and micro levels. We additionally incorporate patient-to-surgeon allocation flexibilities, surgeon-to-hospital allocation flexibilities, and surgeon schedule tightness. Furthermore, we tackle single-hospital multiple specialty OR scheduling problems and single-hospital single-specialty multi-resource constrained OR scheduling problems. We develop novel logic-based Benders decomposition and branch-and-check techniques for these problems and we show that our approaches are up to two orders of magnitude faster than directly solving the mathematical models.