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http://hdl.handle.net/10609/89865
Title: | Ús d'algoritmes genètics per a la gestió de la ubicació i assignació de pacients d'una unitat d'hospitalització |
Author: | Miró Pettican, Daniel |
Tutor: | Isern, David |
Others: | Ventura, Carles |
Abstract: | The management of patients in hospitalization units is one of the tasks of hospital management that, nowadays, could benefit from the use of artificial intelligence algorithms with the aim of improving their efficiency. This TFG explores the implementation and use of a genetic algorithm that, given a physical distribution of patients in a unit and the determination of their load of care tasks, suggests changes of location trying to improve patient allocation to the unit professionals. For that, it is based on the allocation suggested by another genetic algorithm, which provides patient assignments for the different professionals so that care tasks charges are balanced, trying that distances to cover to attend all the patients are as reduced as they can possibly be. The results of the application of the algorithms show that the allocation algorithm demonstrates a correct behavior when assigning patients. However, when making location changes the algorithm does not respond favorably and, therefore, its use is not feasible. In conclusion, genetic algorithms can be an useful tool when managing certain issues related to hospital management, but other options must be evaluated to find specific tools when it comes to manage certain tasks. |
Keywords: | genetic algorithms patient management nursing |
Document type: | info:eu-repo/semantics/bachelorThesis |
Issue Date: | Jan-2019 |
Publication license: | http://www.gnu.org/licenses/gpl.html |
Appears in Collections: | Bachelor thesis, research projects, etc. |
Files in This Item:
File | Description | Size | Format | |
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Presentació TFG.mp4 | 39,82 MB | MP4 | View/Open | |
Presentació TFG.pptx | 2,15 MB | Microsoft Powerpoint XML | View/Open | |
TFG.zip | Arxiu comprimit amb el codi font i els sets de proves | 24,87 kB | Unknown | View/Open |
dmiropTFG0119memoria.pdf | Memòria del TFG | 1,72 MB | Adobe PDF | View/Open |
dmiropTFG0119presentación.pdf | Presentació en PDF del TFG | 2,83 MB | Adobe PDF | View/Open |
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