Improve the Operating Room Schedule to Reduce the Number of Required Beds
After surgery most of the surgical patients have to be admitted and treated at one of the wards in the hospital. Due to financial and other reasons, it is important to reduce the number of required beds as much as possible. Each feasible operating room schedule leads to a number of required beds at the ward. Due to the stochastic nature of the length of stay of patients, the analytical calculation of this number results in a complex formulation which involves convolutions of discrete distributions. I will present two different approaches to deal with this complexity. The first approach is based on a local search heuristic which takes into account the detailed formulation of the objective. The second approach reduces the complexity by simplifying the objective function. This allows modeling and solving the resulting problem as an ILP. The computational results show that the second approach provides better solutions to the original problem for instances based on a Dutch hospital. By using this approach, the number of required beds for this hospital can be reduced by almost 20%.
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