A stochastic model for operating room planning with elective and emergency surgery demands, OR for Health Policy: Making better decision

This paper proposes a stochastic model for Operating Rooms (ORs) planning with two types of surgery demands: elective surgery and emergency surgery. Elective cases can be planned starting from an earliest date with a patient related cost depending on the surgery date. Emergency cases arrive randomly and have to be performed on the day of arrival. The planning problem consists of assigning elective cases to different periods over a planning horizon in order to minimize the sum of elective patients related costs and overtime costs of operating rooms. A new stochastic mathematical programming model is proposed. More specific, we propose a Monte Carlo optimisation method combining Monte Carlo simulation and Mixed Integer Programming. The solution of this method is proved to converge to a real optimum as the computation budget increases. The optimization method is implemented and numerical results are presented.

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