326
Views
1
CrossRef citations to date
0
Altmetric
Research Article

Intelligent scheduling of double-deck traversable cranes based on deep reinforcement learning

ORCID Icon, , &
Pages 2034-2050 | Received 16 Feb 2022, Accepted 27 Jun 2022, Published online: 15 Nov 2022

References

  • Afsar, H. M., P. Lacomme, L. Ren, C. Prodhon, and D. Vigo. 2016. “Resolution of a Job-Shop Problem with Transportation Constraints: A Master/Slave Approach.” IFAC-PapersOnLine, 8th IFAC Conference on Manufacturing Modelling, Management and Control MIM 49 (12): 898–903. doi:10.1016/j.ifacol.2016.07.889.
  • Dai, Min, Dunbing Tang, Adriana Giret, and Miguel A. Salido. 2019. “Multi-objective Optimization for Energy-Efficient Flexible Job Shop Scheduling Problem with Transportation Constraints.” Robotics & Computer-Integrated Manufacturing 59 (October): 143–157. doi:10.1016/j.rcim.2019.04.006.
  • Du, Yu, Jun-qing Li, Chao Luo, and Lei-lei Meng. 2021. “A Hybrid Estimation of Distribution Algorithm for Distributed Flexible Job Shop Scheduling with Crane Transportations.” Swarm & Evolutionary Computation 62 (April): 100861. doi:10.1016/j.swevo.2021.100861.
  • Han, Bao-An, and Jian-Jun Yang. 2020. “Research on Adaptive Job Shop Scheduling Problems Based on Dueling Double DQN.” IEEE Access 8: 186474–186495. doi:10.1109/ACCESS.2020.3029868.
  • Hasselt, Arthur Guez van Hado, and David Silver. 2015. “Deep Reinforcement Learning with Double Q-Learning.” Arxiv:1509.06461 [Cs]. http://arxiv.org/abs/1509.06461, December.
  • Heshmati, Sam, Túlio A. M. Toffolo, Wim Vancroonenburg, and Greet Vanden Berghe. 2019. “Crane-Operated Warehouses: Integrating Location Assignment and Crane Scheduling.” Computers & Industrial Engineering 129 (March): 274–295. doi:10.1016/j.cie.2019.01.039.
  • Horng, Shih-Cheng, and Shieh-Shing Lin. 2022. “Apply Ordinal Optimization to Optimize the Job-Shop Scheduling Under Uncertain Processing Times.” Arabian Journal for Science & Engineering 47: 9659–9671. doi:10.1007/s13369-021-06317-9.
  • Hu, Hao, Xiaoliang Jia, Qixuan He, Shifeng Fu, and Kuo Liu. 2020. “Deep Reinforcement Learning Based AGVs Real-Time Scheduling with Mixed Rule for Flexible Shop Floor in Industry 4.0.” Computers & Industrial Engineering 149 (November): 106749. doi:10.1016/j.cie.2020.106749.
  • Lei, Chuanjin, Ning Zhao, Song Ye, and Xiuli Wu. 2020. “Memetic Algorithm for Solving Flexible Flow-Shop Scheduling Problems with Dynamic Transport Waiting Times.” Computers & Industrial Engineering 139 (January): 105984. doi:10.1016/j.cie.2019.07.041.
  • Li, Zhipeng, Xiumei Wei, Xuesong Jiang, and Yewen Pang. 2021. “A Kind of Reinforcement Learning to Improve Genetic Algorithm for Multiagent Task Scheduling.” Mathematical Problems in Engineering 2021 (January): e1796296. doi:10.1155/2021/1796296.
  • Liu, Zhengchao, Shunsheng Guo, and Lei Wang. 2019. “Integrated Green Scheduling Optimization of Flexible Job Shop and Crane Transportation Considering Comprehensive Energy Consumption.” Journal of Cleaner Production 211 (February): 765–786. doi:10.1016/j.jclepro.2018.11.231.
  • Luo, Shu. 2020. “Dynamic Scheduling for Flexible Job Shop with New Job Insertions by Deep Reinforcement Learning.” Applied Soft Computing 91: 106208. doi:10.1016/j.asoc.2020.106208.
  • Mnih, Volodymyr, Koray Kavukcuoglu, David Silver, Andrei A. Rusu, Joel Veness, Marc G. Bellemare, Alex Graves, et al. 2015. “Human-Level Control Through Deep Reinforcement Learning.” Nature 518 (7540): 529–533. doi:10.1038/nature14236.
  • Ou, Xinyan, Qing Chang, Jorge Arinez, and Jing Zou. 2018. “Gantry Work Cell Scheduling Through Reinforcement Learning with Knowledge-Guided Reward Setting.” IEEE Access 6: 14699–14709. doi:10.1109/ACCESS.2018.2800641.
  • Shi, Daming, Wenhui Fan, Yingying Xiao, Tingyu Lin, and Chi Xing. 2020. “Intelligent Scheduling of Discrete Automated Production Line via Deep Reinforcement Learning.” International Journal of Production Research 58 (11): 3362–3380. doi:10.1080/00207543.2020.1717008.
  • Shiue, Y., Ken-Chuan Lee Lee, and Chao-Ton Su. 2018. “Real-Time Scheduling for a Smart Factory Using a Reinforcement Learning Approach.” Computers & Industrial Engineering 125 (November): 604–614. doi:10.1016/j.cie.2018.03.039.
  • Sun, Jinghe, Guohui Zhang, Jiao Lu, and Wenqiang Zhang. 2021. “A Hybrid Many-Objective Evolutionary Algorithm for Flexible Job-Shop Scheduling Problem with Transportation and Setup Times.” Computers & Operations Research 132 (August): 105263. doi:10.1016/j.cor.2021.105263.
  • Tang, Lixin, Xie Xie, and Jiyin Liu. 2009. “Scheduling of a Single Crane in Batch Annealing Process.” Computers & Operations Research 36 (10): 2853–2865. doi:10.1016/j.cor.2008.12.014.
  • Wang, Libing, Xin Hu, Yin Wang, Sujie Xu, Shijun Ma, Kexin Yang, Zhijun Liu, and Weidong Wang. 2021. “Dynamic Job-Shop Scheduling in Smart Manufacturing Using Deep Reinforcement Learning.” Computer Networks 190 (May): 107969. doi:10.1016/j.comnet.2021.107969.
  • Zhang, Zhicong, Weiping Wang, Shouyan Zhong, and Kaishun Hu. 2013. “Flow Shop Scheduling with Reinforcement Learning.” Asia-Pacific Journal of Operational Research 30 (5): 1350014. doi:10.1142/S0217595913500140.
  • Zhou, Binghai, and Xiumei Liao. 2020. “Particle Filter and Levy Flight-Based Decomposed Multi-objective Evolution Hybridized Particle Swarm for Flexible Job Shop Greening Scheduling with Crane Transportation.” Applied Soft Computing 91 (June): 106217. doi:10.1016/j.asoc.2020.106217.

Reprints and Corporate Permissions

Please note: Selecting permissions does not provide access to the full text of the article, please see our help page How do I view content?

To request a reprint or corporate permissions for this article, please click on the relevant link below:

Academic Permissions

Please note: Selecting permissions does not provide access to the full text of the article, please see our help page How do I view content?

Obtain permissions instantly via Rightslink by clicking on the button below:

If you are unable to obtain permissions via Rightslink, please complete and submit this Permissions form. For more information, please visit our Permissions help page.