Optimizacija in digitalizacija procesov Luke Koper

diplomsko delo

Kristjan Jekovec (Author), Tomaž Hočevar (Mentor)

Abstract

Vsak dan skozi Luko Koper preide veliko število kontejnerjev, ki so nato iz luke odpremljeni z različnimi prevoznimi sredstvi, kot so vlaki, tovornjaki ali ladje. Ker ob prihodu ladje še ni natančno znano, kako bodo posamezni kontejnerji odpremljeni, sem razvil napovedni model, ki omogoča predvidevanje načina prevoza kontejnerjev iz luke. Takšna napoved je ključnega pomena, saj omogoča optimalno razporeditev kontejnerjev že ob prihodu v luko, kar povečuje učinkovitost dostopa do nadaljnjega transporta z vlakom ali tovornjakom. Posledično se zmanjša število nepotrebnih premikov kontejnerjev med skladiščenjem, kar pripomore k skrajšanju časa, potrebnega za dostavo vsebine kontejnerjev do končnega naročnika. Cilj naloge je bil razviti model z vsaj 70% natančnostjo, kar nam je uspelo preseči, saj smo z uporabo vseh razpoložljivih podatkov dosegli natančnost približno 80%.

Keywords

optimizacija procesov;digitalizacija procesov;Luka Koper;simulacija;računalništvo;matematika;interdisciplinarni študij;univerzitetni študij;diplomske naloge;

Data

Language:	Slovenian
Year of publishing:	2024
Typology:	2.11 - Undergraduate Thesis
Organization:	UL FRI - Faculty of Computer and Information Science
Publisher:	[K. Jekovec]
UDC:	004.85:331.103:627.21(043.2)
COBISS:	212258819
Views:	130
Downloads:	29
Average score:	0 (0 votes)
Metadata:

Other data

Secondary language:	English
Secondary title:	Optimization and Digitalization of Processes at the Port of Koper
Secondary abstract:	Every day, a large number of containers pass through the Port of Koper, where they are dispatched via various modes of transportation, such as trains, trucks, or ships. Since the exact mode of transportation for each container is unknown upon the ship’s arrival, I developed a predictive model that forecasts how containers will be transported out of the port. This prediction is crucial as it allows for the optimal allocation of containers upon their arrival at the port, thereby increasing the efficiency of access to subsequent transportation by train or truck. Consequently, this reduces the number of unnecessary container movements during storage and shortens the time required to deliver the container’s contents to the final customer. The goal of the thesis was to develop a model with at least 70% accuracy, which we successfully exceeded, achieving an accuracy of approximately 80%.
Secondary keywords:	machine learning;data analysis;data mining;simulation;computer science;computer and information science;computer science and mathematics;interdisciplinary studies;diploma;Strojno učenje;Digitalizacija;Pristanišča;Organizacija dela;Računalništvo;Univerzitetna in visokošolska dela;
Type (COBISS):	Bachelor thesis/paper
Study programme:	1000407
Embargo end date (OpenAIRE):	1970-01-01
Thesis comment:	Univ. v Ljubljani, Fak. za računalništvo in informatiko
Pages:	1 spletni vir (1 datoteka PDF (64 str.))
ID:	25001755