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Naslov:A new solution to distributed permutation flow shop scheduling problem based on NASH Q-Learning
Avtorji:ID Ren, J. F. (Avtor)
ID Ye, C. M. (Avtor)
ID Li, Y. (Avtor)
Datoteke:.pdf APEM16-3_269-284.pdf (784,23 KB)
MD5: 0BDA68EC782622F0B61A2F38F178CF66
 
URL https://apem-journal.org/Archives/2021/APEM16-3_269-284.pdf
 
Jezik:Angleški jezik
Vrsta gradiva:Članek v reviji
Tipologija:1.01 - Izvirni znanstveni članek
Organizacija:FS - Fakulteta za strojništvo
Opis:Aiming at Distributed Permutation Flow-shop Scheduling Problems (DPFSPs), this study took the minimization of the maximum completion time of the workpieces to be processed in all production tasks as the goal, and took the multi-agent Reinforcement Learning (RL) method as the main frame of the solution model, then, combining with the NASH equilibrium theory and the RL method, it proposed a NASH Q-Learning algorithm for Distributed Flow-shop Scheduling Problem (DFSP) based on Mean Field (MF). In the RL part, this study designed a two-layer online learning mode in which the sample collection and the training improvement proceed alternately, the outer layer collects samples, when the collected samples meet the requirement of batch size, it enters to the inner layer loop, which uses the Q-learning model-free batch processing mode to proceed, and adopts neural network to approximate the value function to adapt to large-scale problems. By comparing the Average Relative Percentage Deviation (ARPD) index of the benchmark test questions, the calculation results of the proposed algorithm outperformed other similar algorithms, which proved the feasibility and efficiency of the proposed algorithm.
Ključne besede:flow shop scheduling, distributed scheduling, permutation flow shop, NASH Q-learning, mean field (MF)
Status publikacije:Objavljeno
Verzija publikacije:Objavljena publikacija
Poslano v recenzijo:29.07.2021
Datum sprejetja članka:26.09.2021
Datum objave:31.10.2021
Založnik:Chair of Production Engineering (CPE), University of Maribor Faculty of Mechanical Engineering
Leto izida:2021
Št. strani:str. 269-284
Številčenje:Vol. 16, no. 3
PID:20.500.12556/DKUM-97384 Novo okno
UDK:331.103:678.02
COBISS.SI-ID:270030595 Novo okno
DOI:10.14743/apem2021.3.399 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:03.03.2026
Število ogledov:151
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

Gradivo je financirano iz projekta

Financer:Shanghai Science and Technology Commission, China
Program financ.:Key Soft Science Project
Številka projekta:20692104300
Naslov:Science and Technology Innovation Action Plan

Financer:National Natural Science Foundation, China
Številka projekta:71840003

Financer:University of Shanghai for Science and Technology, China
Številka projekta:2018KJFZ043
Naslov:the Technology Development Project

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:razporejanje pretoka dela v delavnici, porazdeljeno razporejanje, trgovina s permutacijskim tokom, NASH Q-učenje, povprečno polje


Zbirka

To gradivo je del naslednjih zbirk del:
  1. Advances in production engineering & management

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