Rješavanje problema raspoređivanja medicinskih sestara u smjene korištenjem algoritama evolucijskog računanja

master's thesis

• Title (english): Solving the nurse scheduling problem using evolutionary computation algorithms
• Author: Katarina Jurič
• Mentor: Alan Jović (mentor)
• Committee member: Alan Jović (predsjednik povjerenstva)
• Committee member: Nikolina Frid (član povjerenstva)
• Committee member: Jan Šnajder (član povjerenstva)
• Granter: University of Zagreb; Faculty of Electrical Engineering and Computing; Zagreb
• Defense date and country: 2024-07-08, Croatia

Abstract

U ovom radu predstavljen je diskretni binarni problem raspoređivanja medicinskih sestara u
smjene. Problem uključuje izradu rasporeda smjena koji zadovoljava tvrda i meka ograničenja.
Ulazni podaci uzeti su iz NSPLiba, a rješenja problema dobivena su pomoću implementacije
triju metaheuristika – genetskog algoritma, tabu-pretrage i optimizacije roja čestica. Najbolji
rezultati ostvareni su genetskim algoritmom i tabu-pretragom koji se i inače koriste za
logističke probleme. Algoritam roja čestica nije se pokazao prikladnim za ovu vrstu problema
s obzirom na to da se češće koristi nad kontinuiranim optimizacijskim problemima.

Abstract (english)

This paper presents a discrete binary nurse scheduling problem. The problem involves creating
a shift schedule that satisfies hard and soft constraints. The input data is taken from NSPLib
and the problem solutions are obtained using the implementation of three metaheuristics –
genetic algorithm, tabu search, and particle swarm optimization. The best results were achieved
using the genetic algorithm and tabu search, which are commonly used for logistic problems.
The particle swarm optimization algorithm did not prove suitable for this type of problem, as
it is more frequently used for continuous optimization problems.

• Keywords: problem raspoređivanja medicinskih sestara u smjene; genetski algoritam; algoritam optimizacije rojem čestica; tabu-pretraga; diskretni optimizacijski problemi
• Keywords (english): nurse scheduling problem; genetic algorithm; particle swarm optimization; tabu search; discrete optimization problems
• Language: croatian
• URN:NBN: urn:nbn:hr:168:867323
• Study programme: Title: Computing; Study programme type: university; Study level: graduate; Academic / professional title: magistar/magistra inženjer/inženjerka računarstva (magistar/magistra inženjer/inženjerka računarstva)
• Type of resource: Text
• File origin: Born digital
• Access conditions: Closed access
• Created on: 2024-10-12 20:59:23