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DKUM
EPF - Faculty of Business and Economics
FE - Faculty of Energy Technology
FERI - Faculty of Electrical Engineering and Computer Science
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Faculty of Business and Economic, Maribor
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Faculty of Logistics, Celje, Krško
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Title:
Evaluation of Machine Learning Algorithms for Predicting the Processing Time of Order Picking in a Warehouse
Authors:
ID
Škrinjar, Tilen
(
Author
)
ID
Strnad, Damjan
(
Mentor
)
More about this mentor...
ID
Lengheimer, Mario
(
Comentor
)
Files:
MAG_Skrinjar_Tilen_2019.pdf
(3,28 MB)
MD5: 17B32DF8D48CA9BDEB49D864096A72A2
PID:
20.500.12556/dkum/5940b27b-e891-481f-9ff9-81abbf5c6d3e
Language:
English
Work type:
Master's thesis/paper
Typology:
2.09 - Master's Thesis
Organization:
FERI - Faculty of Electrical Engineering and Computer Science
Abstract:
Optimization of warehouse processes increases efficiency and lowers the cost of managing a warehouse. The most expensive and time-consuming activity is picking. Knowing picking process time is an important factor for proper organization of material and information flow. Orders delivered to a packing station too early or too late can cause delays in a warehouse. The purpose of this study is to evaluate machine learning pipeline for processing time prediction of order picking. This includes data gathering, data preprocessing and the evaluation of machine learning algorithms, which are the most important aspects of this research.
Keywords:
warehouse
,
order picking
,
machine learning
,
regression analysis
Place of publishing:
[Maribor
Publisher:
T. Škrinjar
Year of publishing:
2019
PID:
20.500.12556/DKUM-73067
UDC:
004.85.021(043.2)
COBISS.SI-ID:
22167830
NUK URN:
URN:SI:UM:DK:LCAOQ9KN
Publication date in DKUM:
25.02.2019
Views:
2251
Downloads:
87
Metadata:
Categories:
KTFMB - FERI
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Licences
License:
CC BY-NC-ND 4.0, Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International
Link:
http://creativecommons.org/licenses/by-nc-nd/4.0/
Description:
The most restrictive Creative Commons license. This only allows people to download and share the work for no commercial gain and for no other purposes.
Licensing start date:
30.01.2019
Secondary language
Language:
Slovenian
Title:
Ovrednotenje algoritmov strojnega učenja za napovedovanje časa komisioniranja v skladišču
Abstract:
Optimizacija procesov v skladišču povečuje učinkovitost delovanja in zmanjša stroške pri upravljanju skladišča. Časovno najzahtevnejši proces je komisioniranje. To je proces zbiranja blaga v skladišču in dostave na prostor za pakiranje. Čas komisioniranja je pomemben pri optimalnem prehodu blaga v skladišču. Naročila, ki so na pakirno mesto dostavljena prezgodaj ali prepozno, lahko povzročijo zamude v skladišču. Namen magistrske naloge je ovrednotiti proces strojnega učenja za napovedovanja časa komisioniranja. To vključuje zbiranje podatkov, predhodno obdelavo podatkov in ovrednotenje algoritmov strojnega učenja, ki predstavljajo najbolj pomemben del raziskave.
Keywords:
skladišče. komisioniranje
,
strojno učenje
,
regresijska analiza
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