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Naslov:Real-time scheduling for dynamic workshops with random new job insertions by using deep reinforcement learning
Avtorji:ID Sun, Z. Y. (Avtor)
ID Han, W. M. (Avtor)
ID Gao, L. L. (Avtor)
Datoteke:.pdf APEM18-2_137-151.pdf (1,78 MB)
MD5: 69F2274AC3C2AB253B699FDEE617E60B
 
URL https://apem-journal.org/Archives/2023/Abstract-APEM18-2_137-151.html
 
Jezik:Angleški jezik
Vrsta gradiva:Članek v reviji
Tipologija:1.01 - Izvirni znanstveni članek
Organizacija:FS - Fakulteta za strojništvo
Opis:Dynamic real-time workshop scheduling on job arrival is critical for effective production. This study proposed a dynamic shop scheduling method integrating deep reinforcement learning and convolutional neural network (CNN). In this method, the spatial pyramid pooling layer was added to the CNN to achieve effective dynamic scheduling. A five-channel, two-dimensional matrix that expressed the state characteristics of the production system was used to capture the state of the real-time production of the workshop. Adaptive scheduling was achieved by using a reward function that corresponds to the minimum total tardiness, and the common production dispatching rules were used as the action space. The experimental results revealed that the proposed algorithm achieved superior optimization capabilities with lower time cost than that of the genetic algorithm and could adaptively select appropriate dispatching rules based on the state features of the production system.
Ključne besede:real-time scheduling, machine learning, deep reinforcement learning, DRL, spatial pyramid pooling layer, artificial neural networks, ANN, convolutional neural networks, CNN
Status publikacije:Objavljeno
Verzija publikacije:Objavljena publikacija
Poslano v recenzijo:07.12.2022
Datum sprejetja članka:25.06.2023
Datum objave:21.07.2023
Založnik:Chair of Production Engineering (CPE), University of Maribor Faculty of Mechanical Engineering
Leto izida:2023
Št. strani:str. 137-151
Številčenje:Vol. 18, no. 2
PID:20.500.12556/DKUM-97033 Novo okno
UDK:004.8
COBISS.SI-ID:268213507 Novo okno
DOI:10.14743/apem2023.2.462 Novo okno
ISSN pri članku:1854-6250
Avtorske pravice:Content from this work may be used under the terms of the Creative Commons Attribution 4.0 International Licence (CC BY 4.0). Any further distribution of this work must maintain attribution to the author(s) and the title of the work, journal citation and DOI.
Datum objave v DKUM:12.02.2026
Število ogledov:170
Število prenosov:4
Metapodatki:XML DC-XML DC-RDF
Področja:Ostalo
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Gradivo je del revije

Naslov:Advances in production engineering & management
Skrajšan naslov:Adv produc engineer manag
Založnik:Fakulteta za strojništvo, Inštitut za proizvodno strojništvo
ISSN:1854-6250
COBISS.SI-ID:229859072 Novo okno

Licence

Licenca:CC BY 4.0, Creative Commons Priznanje avtorstva 4.0 Mednarodna
Povezava:http://creativecommons.org/licenses/by/4.0/deed.sl
Opis:To je standardna licenca Creative Commons, ki daje uporabnikom največ možnosti za nadaljnjo uporabo dela, pri čemer morajo navesti avtorja.

Sekundarni jezik

Jezik:Slovenski jezik
Ključne besede:konvolucijske nevronske mreže, umetne nevronske mreže, globoko učenje


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  1. Advances in production engineering & management

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