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dc.contributor.author
Pulido, Raul  
dc.contributor.author
Aguirre, Adrian Marcelo  
dc.contributor.author
Ibañez Herrero, Natalia  
dc.contributor.author
Ortega Mier, Miguel  
dc.contributor.author
García Sanchez, Alvaro  
dc.contributor.author
Mendez, Carlos Alberto  
dc.date.available
2016-12-16T17:33:33Z  
dc.date.issued
2014-09  
dc.identifier.citation
Pulido, Raul; Aguirre, Adrian Marcelo; Ibañez Herrero, Natalia; Ortega Mier, Miguel; García Sanchez, Alvaro; et al.; Optimization methods for the operation room management under uncertainty: Stochastic programming vs. Decomposition approach; Tadbir Operational Research Group; Journal of Applied Operational Research; 6; 9-2014; 145-157  
dc.identifier.issn
1735-8523  
dc.identifier.uri
http://hdl.handle.net/11336/9580  
dc.description.abstract
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.  
dc.format
application/pdf  
dc.language.iso
eng  
dc.publisher
Tadbir Operational Research Group  
dc.rights
info:eu-repo/semantics/openAccess  
dc.rights.uri
https://creativecommons.org/licenses/by-nc-sa/2.5/ar/  
dc.subject
Stochastic Optimization  
dc.subject
Decomposition Approach  
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Scheduling  
dc.subject.classification
Ingeniería de Procesos Químicos  
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Ingeniería Química  
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INGENIERÍAS Y TECNOLOGÍAS  
dc.title
Optimization methods for the operation room management under uncertainty: Stochastic programming vs. Decomposition approach  
dc.type
info:eu-repo/semantics/article  
dc.type
info:ar-repo/semantics/artículo  
dc.type
info:eu-repo/semantics/publishedVersion  
dc.date.updated
2016-12-12T13:44:03Z  
dc.journal.volume
6  
dc.journal.pagination
145-157  
dc.journal.pais
Canadá  
dc.journal.ciudad
Toronto  
dc.description.fil
Fil: Pulido, Raul. Escuela Técnica Superior de Ingenieros Industriales; España  
dc.description.fil
Fil: Aguirre, Adrian Marcelo. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Santa Fe. Instituto de Desarrollo Tecnológico Para la Industria Química (i); Argentina  
dc.description.fil
Fil: Ibañez Herrero, Natalia. Escuela Técnica Superior de Ingenieros Industriales; España  
dc.description.fil
Fil: Ortega Mier, Miguel. Escuela Técnica Superior de Ingenieros Industriales; España  
dc.description.fil
Fil: García Sanchez, Alvaro. Escuela Técnica Superior de Ingenieros Industriales; España  
dc.description.fil
Fil: Mendez, Carlos Alberto. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Santa Fe. Instituto de Desarrollo Tecnológico Para la Industria Química (i); Argentina  
dc.journal.title
Journal of Applied Operational Research  
dc.relation.alternativeid
info:eu-repo/semantics/altIdentifier/url/http://orlabanalytics.ca/jaor/archive/v6n3.htm