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undergraduate thesis
Učinkovito raspoređivanje pacijenata na bolničke preglede
2024. urn:nbn:hr:200:180167
Šobačić, Lea
Josip Juraj Strossmayer University of Osijek
Faculty of Electrical Engineering, Computer Science and Information Technology Osijek
Department of Software Engineering
Chair of Visual Computing

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Šobačić, L. (2024). Učinkovito raspoređivanje pacijenata na bolničke preglede (Undergraduate thesis). Osijek: Josip Juraj Strossmayer University of Osijek, Faculty of Electrical Engineering, Computer Science and Information Technology Osijek. Retrieved from https://urn.nsk.hr/urn:nbn:hr:200:180167

Šobačić, Lea. "Učinkovito raspoređivanje pacijenata na bolničke preglede." Undergraduate thesis, Josip Juraj Strossmayer University of Osijek, Faculty of Electrical Engineering, Computer Science and Information Technology Osijek, 2024. https://urn.nsk.hr/urn:nbn:hr:200:180167

Šobačić, Lea. "Učinkovito raspoređivanje pacijenata na bolničke preglede." Undergraduate thesis, Josip Juraj Strossmayer University of Osijek, Faculty of Electrical Engineering, Computer Science and Information Technology Osijek, 2024. https://urn.nsk.hr/urn:nbn:hr:200:180167

Šobačić, L. (2024). 'Učinkovito raspoređivanje pacijenata na bolničke preglede', Undergraduate thesis, Josip Juraj Strossmayer University of Osijek, Faculty of Electrical Engineering, Computer Science and Information Technology Osijek, accessed 04 January 2025, https://urn.nsk.hr/urn:nbn:hr:200:180167

Šobačić L. Učinkovito raspoređivanje pacijenata na bolničke preglede [Undergraduate thesis]. Osijek: Josip Juraj Strossmayer University of Osijek, Faculty of Electrical Engineering, Computer Science and Information Technology Osijek; 2024 [cited 2025 January 04] Available at: https://urn.nsk.hr/urn:nbn:hr:200:180167

L. Šobačić, "Učinkovito raspoređivanje pacijenata na bolničke preglede", Undergraduate thesis, Josip Juraj Strossmayer University of Osijek, Faculty of Electrical Engineering, Computer Science and Information Technology Osijek, Osijek, 2024. Available at: https://urn.nsk.hr/urn:nbn:hr:200:180167

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Metadata
TitleUčinkovito raspoređivanje pacijenata na bolničke preglede
Title (english)Hospital Examination Patient Scheduling Efficiency
AuthorLea Šobačić
MentorJosip Job (mentor)
Committee memberIvica Lukić (predsjednik povjerenstva)
GranterJosip Juraj Strossmayer University of Osijek
Faculty of Electrical Engineering, Computer Science and Information Technology Osijek
(Department of Software Engineering)
(Chair of Visual Computing)
Osijek
Defense date and country2024-09-30, Croatia
Scientific / art field,
discipline and subdiscipline		TECHNICAL SCIENCES
Computing
Information Systems
Abstract
Ovaj rad bavi se učinkovitim raspoređivanjem pacijenata na bolničke preglede koristeći tri različita algoritma: First-Come First-Served, Priority Scheduling i cjelobrojno linearno programiranje. Cilj istraživanja bio je smanjiti vrijeme čekanja pacijenata i poboljšati učinkovitost korištenja zdravstvenih resursa. Rezultati su pokazali da je ILP algoritam ostvario najbolje performanse, smanjivši vrijeme čekanja za 60,46%, dok su FCFS i PS algoritmi postigli smanjenje od 55,66% i 11,92%. U istraživanju smo koristili tehnologije poput programskog jezika Python i biblioteka kao što su Pandas za manipulaciju podacima te PuLP za rješavanje problema linearnog programiranja. Ovi alati omogućili su nam učinkovito modeliranje i analizu problema raspodjele pacijenata, naglašavajući važnost naprednih algoritama u optimizaciji zdravstvenih sustava.
Abstract (english)
This paper addresses the efficient scheduling of patients for hospital examinations using three different algorithms: First-Come First-Served, Priority Scheduling, and Integer Linear Programming. The aim of the research was to reduce patient waiting times and improve the efficiency of healthcare resource utilization. The results showed that the ILP algorithm achieved the best performance, reducing waiting time by 60.46%, while the FCFS and PS algorithms achieved reductions of 55.66% and 11.92%. In this research, we utilized technologies such as the Python programming language and libraries like Pandas for data manipulation and PuLP for solving linear programming problems. These tools allowed us to effectively model and analyze the patient scheduling problem, highlighting the importance of advanced algorithms in optimizing healthcare systems.
Keywords
Keywords (english)
Languagecroatian
URN:NBNurn:nbn:hr:200:180167
Study programmeTitle: Undergraduate University Study Programme in Computer Engineering
Study programme type: university
Study level: undergraduate
Academic / professional title: sveučilišni/sveučilišna provostupnik/prvostupnica (baccalaureus/baccalaurea) inženjerka računarstva (sveučilišni/sveučilišna provostupnik/prvostupnica (baccalaureus/baccalaurea) inženjerka računarstva)
Type of resourceText
File originBorn digital
Access conditionsOpen access
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Created on2024-10-25 11:58:21