Integrated operating room planning and scheduling problem with assistant surgeon dependent surgery durations
There is evidence in the literature that most surgeries in hospitals are performed by a team composed of two surgeons, and that their experience largely influences the surgery duration. However, to the best our knowledge, only one contribution has addressed the operating room planning and scheduling...
| Autores: | , , |
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| Tipo de recurso: | artículo |
| Estado: | Versión aceptada para publicación |
| Fecha de publicación: | 2015 |
| País: | España |
| Institución: | Universidad de Sevilla (US) |
| Repositorio: | idUS. Depósito de Investigación de la Universidad de Sevilla |
| OAI Identifier: | oai:idus.us.es:11441/166922 |
| Acceso en línea: | https://hdl.handle.net/11441/166922 https://doi.org/10.1016/j.cie.2015.01.006 |
| Access Level: | acceso abierto |
| Palabra clave: | Operations research in health services Operating room planning and scheduling Assistant surgeon dependent surgery duration Approximate methods |
| Sumario: | There is evidence in the literature that most surgeries in hospitals are performed by a team composed of two surgeons, and that their experience largely influences the surgery duration. However, to the best our knowledge, only one contribution has addressed the operating room planning and scheduling problem with surgical teams, but in such case surgery durations did not depend on the experience of surgeons. In this paper we address an integrated operating room planning and scheduling problem with surgical teams composed by one or two surgeons where surgery durations depend on their experience and skills. We propose a mixed integer linear programming (MILP) model to optimally solve this problem. Given the high computation requirements of our MILP model, we also propose an iterative constructive method. In order to evaluate the performance of both exact and approximate methods, an extensive test bed is generated. The computational experience shows that the proposed algorithm is able to find feasible solution for all problems requiring shorter CPU time and average relative percentage deviation than the MILP model. Finally, the robustness of the so-obtained surgical schedules is analyzed using simulation. |
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