Logic-Based Benders Decomposition and Binary Decision Diagram Based Approaches for Stochastic Distributed Operating Room Scheduling

The distributed operating room (OR) scheduling problem aims to find an assignment of surgeries ORs across collaborating hospitals that share their waiting lists and ORs. We propose a stochastic extension this where surgery durations are considered be uncertain. In order obtain solutions for the challenging model, we use sample average approximation develop two enhanced decomposition frameworks logic-based Benders (LBBD) optimality cuts binary decision diagram based cuts. Specifically, best our knowledge, deriving LBBD in programming context is new literature. Our computational experiments on hospital data set illustrate formulation generates robust schedules algorithms improve efficiency. Summary Contribution: model important healthcare scheduling, namely, which inspired by current practice Toronto, Ontario, Canada. methods computationally faster than solving directly via state-of-the-art solver. present both some theoretical results numerical evaluation algorithms. Compared with its deterministic counterpart literature, shows improvement relevant metrics underlying problem. addition, exploit structure solvability. Those also have potential used tackle other planning problems similar structure.