An improved MOEA/D with reinforcement learning for flexible job shops incorporating manual operations and fatigue effects

Evidence shows that the manufacturing industry is transitioning towards “automation” at the present stage, workpieces will be processed by machines automatically, and workers only need to complete the “pre-processing” and “post-processing” tasks. In the meantime, worker fatigue also needs to be take...

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Vydáno v:	Swarm and evolutionary computation Ročník 99; s. 102200
Hlavní autoři:	Li, Yibing, Tong, Xin, Zou, Haiqi, Guo, Jun, Wang, Lei, Tang, Hongtao, Wang, Kaipu, Li, Xinyu
Médium:	Journal Article
Jazyk:	angličtina
Vydáno:	Elsevier B.V 01.12.2025
Témata:	Flexible job-shop scheduling Manual task Multi-objective evolutionary algorithm based on decomposition (MOEA/D) Reinforcement learning Worker fatigue Manual task Flexible job-shop scheduling Multi-objective evolutionary algorithm based on decomposition (MOEA/D) Worker fatigue Reinforcement learning
ISSN:	2210-6502
On-line přístup:	Získat plný text
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