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International Journal of Production Research Volume 58, 2020 - Issue 16
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Articles

Spatial arrangement using deep reinforcement learning to minimise rearrangement in ship block stockyards

Byeongseop Kima Department of Naval Architecture and Ocean Engineering, Seoul National University;View further author information
,
Yongkuk Jeongb Department of Sustainable Production Development, KTH Royal Institute of Technology;Correspondence[email protected]
ORCID Iconhttps://orcid.org/0000-0003-1878-773XView further author information
ORCID Icon &
Jong Gye Shina Department of Naval Architecture and Ocean Engineering, Seoul National University;;c Research Institute of Marine System Engineering, Seoul National UniversityView further author information
Pages 5062-5076 | Received 03 Mar 2019, Accepted 21 Mar 2020, Published online: 20 Apr 2020

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Ana Esteso, David Peidro, Josefa Mula & Manuel Díaz-Madroñero. (2023) Reinforcement learning applied to production planning and control. International Journal of Production Research 61:16, pages 5772-5789.
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Erfaneh Nikzad & Mahdi Bashiri. (2023) A two-stage stochastic programming model for collaborative asset protection routing problem enhanced with machine learning: a learning-based matheuristic algorithm. International Journal of Production Research 61:1, pages 81-113.
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Lea Kaven, Philipp Huke, Amon Göppert & Robert H. Schmitt. (2024) Multi agent reinforcement learning for online layout planning and scheduling in flexible assembly systems. Journal of Intelligent Manufacturing.
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Shuo Gao, Tangbin Xia, Ge Hong, Ying Zhu, Zhen Chen, Ershun Pan & Lifeng Xi. (2024) An inspection network with dynamic feature extractor and task alignment head for steel surface defect. Measurement 224, pages 113957.
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Young-in Cho, Byeongseop Kim, Hee-Chang Yoon & Jong Hun Woo. (2024) Locating algorithm of steel stock area with asynchronous advantage actor-critic reinforcement learning. Journal of Computational Design and Engineering 11:1, pages 230-246.
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Teng Wang, Xuandong Mo, Mingzhi Chen & Xiaofeng Hu. (2023) An Improved Spatial Scheduling Algorithm for Sub-Assembly in Shipbuilding. An Improved Spatial Scheduling Algorithm for Sub-Assembly in Shipbuilding.
Xiaoli Cao, Xiang Chen, Lu Huang, Lijie Deng, Yijie Cai & Hang Ren. (2023) Detecting technological recombination using semantic analysis and dynamic network analysis. Scientometrics.
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Chengxi Li, Pai Zheng, Yue Yin, Baicun Wang & Lihui Wang. (2023) Deep reinforcement learning in smart manufacturing: A review and prospects. CIRP Journal of Manufacturing Science and Technology 40, pages 75-101.
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Saumyaranjan Sahoo, Satish Kumar, Mohammad Zoynul Abedin, Weng Marc Lim & Suresh Kumar Jakhar. (2022) Deep learning applications in manufacturing operations: a review of trends and ways forward. Journal of Enterprise Information Management 36:1, pages 221-251.
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Steffen Klink, Florian Beuss, Jan Sender & Wilko Fluegge. (2023) Time-based occupancy planning method for assembly areas at production site of large structures. Procedia CIRP 118, pages 946-951.
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Constantin Waubert de Puiseau, Dimitri Tegomo Nanfack, Hasan Tercan, Johannes Löbbert-Plattfaut & Tobias Meisen. (2022) Dynamic Storage Location Assignment in Warehouses Using Deep Reinforcement Learning. Technologies 10:6, pages 129.
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Sirui Wang, Yanlu Sun, Qifan Luo, Zhaocheng Li & Aimin Wang. (2022) A spatial scheduling strategy based on evaluation of the remaining usable area for shipbuilding. A spatial scheduling strategy based on evaluation of the remaining usable area for shipbuilding.
Yimo Yan, Andy H.F. Chow, Chin Pang Ho, Yong-Hong Kuo, Qihao Wu & Chengshuo Ying. (2022) Reinforcement learning for logistics and supply chain management: Methodologies, state of the art, and future opportunities. Transportation Research Part E: Logistics and Transportation Review 162, pages 102712.
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Violetta Giada Cannas & Jonathan Gosling. (2021) A decade of engineering-to-order (2010–2020): Progress and emerging themes. International Journal of Production Economics 241, pages 108274.
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Yongkuk Jeong, Tarun Kumar Agrawal, Erik Flores-García & Magnus Wiktorsson. (2021) A reinforcement learning model for material handling task assignment and route planning in dynamic production logistics environment. Procedia CIRP 104, pages 1807-1812.
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Chong Wang, Kang Wang, Jiabin Tao & Yongqing Zhou. (2020) Research on Real-Time Optimal Path Planning Model and Algorithm for Ship Block Transportation in Shipyard. Journal of Marine Science and Engineering 8:12, pages 991.
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Yimo Yan, Andy H.F. Chow, Chin Pang Ho, Yong-Hong Kuo, Qihao Wu & Chengshuo Ying. (2021) Reinforcement Learning for Logistics and Supply Chain Management: Methodologies, State of the Art, and Future Opportunities. SSRN Electronic Journal.
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