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Naslov:Genetic algorithm-based approach for makespan minimization in a flow shop with queue time limits and skip-ping jobs
Avtorji:ID Han, J. H. (Avtor)
ID Lee, J. Y. (Avtor)
Datoteke:.pdf APEM18-2_152-162.pdf (670,82 KB)
MD5: 775340C25ADDD23AD67F8548A909412C
 
URL https://apem-journal.org/Archives/2023/Abstract-APEM18-2_152-162.html
 
Jezik:Angleški jezik
Vrsta gradiva:Članek v reviji
Tipologija:1.01 - Izvirni znanstveni članek
Organizacija:FS - Fakulteta za strojništvo
Opis:This study investigates a flow shop scheduling problem with queue time limits and skipping jobs, which are common scheduling requirements for semiconductor and printed circuit board manufacturing systems. These manufacturing systems involve the most complex processes, which are strictly controlled and constrained to manufacture high-quality products and satisfy dynamic customer orders. Further, queue times between consecutive stages are limited. Given that the queue times are limited, jobs must begin the next step within the maximum queue time after the jobs in the previous step are completed. In the considered flow shop, several jobs can skip the first step, referred to as skipping jobs. Skipping jobs exist because of multiple types of products processed in the same flow shop. For the considered flow shop, this paper proposes a mathematical programming formulation and a genetic algorithm to minimize the makespan. The GA demonstrated its strengths through comprehensive computational experiments, demonstrating its effectiveness and efficiency. As the problem size increased, the GA's performance improved noticeably, while maintaining acceptable computation times for real-world fab facilities. We also validated its performance in various scenarios involving queue time limits and skipping jobs, to further emphasize its capabilities.
Ključne besede:scheduling, flow shop, makespan, queue time limits, skipping jobs, optimization, modelling, genetic algorithm
Status publikacije:Objavljeno
Verzija publikacije:Objavljena publikacija
Poslano v recenzijo:09.10.2022
Datum sprejetja članka:06.07.2023
Datum objave:23.07.2023
Založnik:Chair of Production Engineering (CPE), University of Maribor Faculty of Mechanical Engineering
Leto izida:2023
Št. strani:str. 152-162
Številčenje:Vol. 18, no. 2
PID:20.500.12556/DKUM-97040 Novo okno
UDK:004.8
COBISS.SI-ID:268223747 Novo okno
DOI:10.14743/apem2023.2.463 Novo okno
ISSN pri članku:1854-6250
Avtorske pravice:Content form 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:13.02.2026
Število ogledov:155
Število prenosov:1
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:the Ministry of SMEs and Startups (MSS, Korea)
Program financ.:the Technology Development Program
Številka projekta:RS-2022-00140527

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:genetski algoritmi, modeliranje, optimizacija


Zbirka

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

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