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Speaker Series Dr. Theresia van Essen


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%.

About the Speaker

Theresia van Essen graduated in 2009 at Delft University of Technology with a cum laude Master’s of Science degree in Applied Mathematics with a thesis on the hub location problem. After finishing her master studies, Theresia joined the department Applied Mathematics of the University of Twente for a Ph.D. program with the Discrete Mathematics and Mathematical Programming group. Additionally, she conducted research at HagaZiekenhuis in The Hague. In 2013, she successfully defended her Phd thesis on health care logistics at the University of Twente. Since then, she has been working as a lecturer at the Applied Mathematics department of Delft University of Technology and as a postdoc in the Stochastics group at the Centre for Mathematics and Informatics (CWI). Currently, her research focuses mainly on ambulance planning.