Daily Operating Rooms Scheduling under Uncertainty using Simulation based Optimization Approach

Operating room scheduling has an important role in increasing the productivity of operating rooms and reducing the hospital costs. Due to uncertainties in operating room activities, this problem can be very challenging. In this article, scheduling of daily surgical cases in 3 stages of operation, preparation, surgery and recovery, considering real constraints of teaching hospitals is investigated. This problem, determines the surgeries sequence and start times and resource allocated to each stage of surgeries by the objectives of minimizing the cost of operating rooms’ over time and idle time under uncertainty in surgeries’ durations. Considering the inefficiency of exact methods in solving large stochastic problems, in this article a simulation based optimization approach is proposed to tackle uncertainty. A two stage ant colony optimization algorithm is combined with a simulation. The proposed algorithm is evaluated through solving several real problems from Hashemi Nejad hospital, a teaching hospital in Tehran, using a set of randomly generated scenarios. The results show the efficiency of the proposed algorithm in solving real life problems.