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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Bibliographic Details

Published in:	Swarm and evolutionary computation Vol. 99; p. 102200
Main Authors:	Li, Yibing, Tong, Xin, Zou, Haiqi, Guo, Jun, Wang, Lei, Tang, Hongtao, Wang, Kaipu, Li, Xinyu
Format:	Journal Article
Language:	English
Published:	Elsevier B.V 01.12.2025
Subjects:	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
Online Access:	Get full text
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