Optimization methods for the operation room management under uncertainty: Stochastic programming vs. Decomposition approach

Article

Authorship

Pulido, Raul ; Aguirre, Adrian Marcelo ; Ibañez Herrero, Natalia ; Ortega Mier, Miguel ; García Sanchez, Alvaro ; MENDEZ, CARLOS ALBERTO

Date

2014

Publishing House and Editing Place

Tadbir Operational Research Group

Magazine

Journal of Applied Operational Research, vol. 6 (pp. 145-157) - ISSN 1735-8523
Tadbir Operational Research Group

ISSN

1735-8523

Summary Information provided by the agent in SIGEVA

The operating theatres are the engine of the hospitals; proper management of the operating rooms and its staff represents a great challenge for managers and its results impact directly in the budget of the hospital. This work presents a MILP model for the efficient schedule of multiple surgeries in Operating Rooms (ORs) during a working day. This model considers multiple surgeons and ORs and different types of surgeries. Stochastic strategies are also implemented for taking into account the unc... The operating theatres are the engine of the hospitals; proper management of the operating rooms and its staff represents a great challenge for managers and its results impact directly in the budget of the hospital. This work presents a MILP model for the efficient schedule of multiple surgeries in Operating Rooms (ORs) during a working day. This model considers multiple surgeons and ORs and different types of surgeries. Stochastic strategies are also implemented for taking into account the uncertain in surgery durations (pre-incision, incision, post-incision times). In addition, a heuristic-based methods and a MILP decomposition approach is proposed for solving large-scale ORs scheduling problems in computational efficient way. All these computer-aided strategies has been implemented in AIMMS, as an advanced modeling and optimization software, developing a user friendly solution tool for the operating room management under uncertainty.