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International Journal of Production Research Volume 60, 2022 - Issue 15
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Research Article

A decision-making method for assembly sequence planning with dynamic resources

Wenbo WuSchool of Mechanical Science and Engineering, Huazhong University of Science and Technology, People’s Republic of ChinaView further author information
,
Zhengdong HuangSchool of Mechanical Science and Engineering, Huazhong University of Science and Technology, People’s Republic of ChinaCorrespondence[email protected]
View further author information
,
Jiani ZengSchool of Mechanical Science and Engineering, Huazhong University of Science and Technology, People’s Republic of ChinaView further author information
&
Kuan FanSchool of Mechanical Science and Engineering, Huazhong University of Science and Technology, People’s Republic of ChinaView further author information
Pages 4797-4816 | Received 16 Jul 2020, Accepted 06 Feb 2021, Published online: 14 Jun 2021

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Stephanie Beyer Díaz, Kristof Coussement, Arno De Caigny, Luis Fernando Pérez & Stefan Creemers. (2024) Do the US president's tweets better predict oil prices? An empirical examination using long short-term memory networks. International Journal of Production Research 62:6, pages 2158-2175.
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Yosra Mezghani, S. Ehsan Hashemi-Petroodi, Simon Thevenin & Alexandre Dolgui. Robust design and reconfiguration planning of mixed-model assembly lines under uncertain evolutions of product family. International Journal of Production Research 0:0, pages 1-23.
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Articles from other publishers (6)

Hang Zhang, Wenhu Wang, Shusheng Zhang, Yajun Zhang, Jingtao Zhou, Zhen Wang, Bo Huang & Rui Huang. (2024) A novel method based on deep reinforcement learning for machining process route planning. Robotics and Computer-Integrated Manufacturing 86, pages 102688.
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Xin Wan, Kun Liu, Weijian Qiu & Zhenhang Kang. (2024) An Assembly Sequence Planning Method Based on Multiple Optimal Solutions Genetic Algorithm. Mathematics 12:4, pages 574.
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Kai Guo, Rui Liu, Guijiang Duan, Jiajun Liu & Pengyong Cao. (2023) Research on dynamic decision-making for product assembly sequence based on Connector-Linked Model and deep reinforcement learning. Journal of Manufacturing Systems 71, pages 451-473.
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Xiaolin Shi, Xitian Tian, Jianguo Gu, Gangfeng Wang, Dongping Zhao & Liping Ma. (2023) A hybrid approach of case- and rule-based reasoning to assembly sequence planning. The International Journal of Advanced Manufacturing Technology 127:1-2, pages 221-236.
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Xiaojun Zhu, Zhigang Xu, Junyi Wang, Xiao Yang & Linlin Fan. (2023) Graph-based assembly sequence planning algorithm with feedback weights. The International Journal of Advanced Manufacturing Technology 125:7-8, pages 3607-3617.
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Marcin Suszyński & Katarzyna Peta. (2021) Assembly Sequence Planning Using Artificial Neural Networks for Mechanical Parts Based on Selected Criteria. Applied Sciences 11:21, pages 10414.
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