A Q-learning-based multi-population algorithm for multi-objective distributed heterogeneous assembly no-idle flowshop scheduling with batch delivery

Distributed heterogeneous factory environments have become the mainstream in real-world manufacturing enterprises. Scheduling the assembly no-idle flowshops in such distributed heterogeneous environments is significant for practitioners. This problem takes into account the heterogeneity between diff...

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Bibliographic Details

Published in:	Expert systems with applications Vol. 263; p. 125690
Main Authors:	Zhang, Zikai, Tang, Qiuhua, Zhang, Liping, Li, Zixiang, Cheng, Lixin
Format:	Journal Article
Language:	English
Published:	Elsevier Ltd 05.03.2025
Subjects:	Assembly flowshop Distributed heterogeneous scheduling Multi-objective optimization Q-learning Distributed heterogeneous scheduling Q-learning Multi-objective optimization Assembly flowshop
ISSN:	0957-4174
Online Access:	Get full text
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