Simulation Optimisation for Operating Room Scheduling

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dc.contributor.authorBaesler, Felipe
dc.contributor.authorGatica Fuentes, J.
dc.contributor.authorCorrea, Rodrigo
dc.date.accessioned2016-08-10T21:27:51Z
dc.date.available2016-08-10T21:27:51Z
dc.date.issued2015
dc.description.abstractThis paper presents a case study on operating room scheduling in a small hospital in Chile. Patient flow was represented using a discrete-event simulation model that considered the randomness associated with the primary activities of the entire process, which includes Pre- and post-hospitalisation, surgery, surgery setup and recovery. A simulated annealing algorithm was implemented and connected to the simulation model to search for better patient schedules. Additionally, three dispatching rules, Shortest Processing Time (SPT), Longest Processing Time (LPT) and First-In, First-Out (FIFO) were used. The results showed that the simulated annealing approach, based on the Cmax objective function, obtained schedules that were 18 % better than the hospital's scheduling practices. The utilisation of dispatching rules also has a significant effect in the Cmax indicator. The SPT rule performed better than the hospital schedule in two of the three experiments considered in the study.
dc.identifier.citationBaesler, Felipe & Gatica, J. & Correa, Rodrigo. (2015). Simulation Optimisation for Operating Room Scheduling. International Journal of Simulation Modelling. 14. 215-226. 10.2507/IJSIMM14(2)3.287.
dc.identifier.urihttp://hdl.handle.net/11447/726
dc.identifier.urihttp://dx.doi.org/10.2507/IJSIMM14(2)3.287
dc.language.isoen_US
dc.subjectSimulation Optimisation
dc.subjectSimulated Annealing
dc.subjectOperating Room
dc.subjectScheduling
dc.subjectSystem
dc.subjectTimes
dc.titleSimulation Optimisation for Operating Room Scheduling
dc.typeArtículo

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