Search Results - "Deep reinforcement learning"

A scalable Deep Q-Learning approach for hot stamping process under dynamic control environment.

Nievas, Nuria^1,2 (AUTHOR) nuria.nievas@eurecat.org, Pagès-Bernaus, Adela² (AUTHOR), Abio, Albert¹ (AUTHOR), Lange, Danillo¹ (AUTHOR), Garcia-Llamas, Eduard³ (AUTHOR), Grané, Marc³ (AUTHOR), Pujante, Jaume³ (AUTHOR), Echeverria, Lluís¹ (AUTHOR), Bonada, Francesc¹ (AUTHOR)

Deep reinforcement learning for solving car resequencing with selectivity banks in automotive assembly shops.

Huang, Yuzhe¹ (AUTHOR), Fu, Gaocai¹ (AUTHOR) fgc1989@whut.edu.cn, Sheng, Buyun^1,2 (AUTHOR), Lu, Yingkang¹ (AUTHOR), Yu, Junpeng¹ (AUTHOR), Yin, Xiyan² (AUTHOR)

Improving efficiency of steel converter facility: a digital twin and reinforcement learning approach.

Kumar, Amit¹ (AUTHOR), Kumar, Ramesh¹ (AUTHOR) rameshkr8190@gmail.com

A dual-critic DQN architecture for lifter assignment in multi-floor semiconductor FAB.

Kim, Jiwon¹ (AUTHOR), Mo, Jeonghoon¹ (AUTHOR) j.mo@yonsei.ac.kr

Integrated scheduling of multi-objective lot-streaming hybrid flowshop with AGV based on deep reinforcement learning.

Tang, Hongtao¹ (AUTHOR) tanght@zjut.edu.cn, Huang, Jiawei¹ (AUTHOR), Ren, Chenhao¹ (AUTHOR), Shao, Yiping¹ (AUTHOR), Lu, Jiansha¹ (AUTHOR)

Real-time stochastic flexible flow shop scheduling in a credit factory with model-based reinforcement learning.

Chen, Liao^1,2 (AUTHOR), Liu, Hongjia^1,2 (AUTHOR), Jia, Ning^1,2 (AUTHOR) jia_ning@tju.edu.cn, Ren, Nianlu^1,2 (AUTHOR), Cui, Runbang³ (AUTHOR), Wei, Wei³ (AUTHOR)

Deep reinforcement learning approach for dynamic capacity planning in decentralised regenerative medicine supply chains.

Tseng, Chin-Yuan^1,2 (AUTHOR) ctseng40@gatech.edu, Li, Junxuan³ (AUTHOR), Lin, Li-Hsiang⁴ (AUTHOR), Wang, Kan² (AUTHOR), White III, Chelsea C.¹ (AUTHOR), Wang, Ben¹ (AUTHOR)

Towards Industry 5.0: digital twin-enhanced approach for dynamic supply chain rescheduling with real-time order arrival and acceptance.

Zhu, Xing¹ (AUTHOR), Liao, Baoyu² (AUTHOR) baoyu_liao@163.com, Shen, Yexing³ (AUTHOR), Kong, Min³ (AUTHOR)

The beer game bullwhip effect mitigation: a deep reinforcement learning approach.

Rozhkov, Maxim¹ (AUTHOR) maksim.rozhkov@hse.ru, Alyamovskaya, Nataliya¹ (AUTHOR), Zakhodiakin, Gleb¹ (AUTHOR)

Cost-effective dynamic sampling in high dimensional online monitoring with advantage actor-critic.

Li, Haoqian¹ (AUTHOR), Chen, Yudong¹ (AUTHOR), Liu, Kaibo¹ (AUTHOR) kliu8@wisc.edu

An efficient and adaptive design of reinforcement learning environment to solve job shop scheduling problem with soft actor-critic algorithm.

Si, Jinghua¹ (AUTHOR), Li, Xinyu¹ (AUTHOR) lixinyu@mail.hust.edu.cn, Gao, Liang¹ (AUTHOR), Li, Peigen¹ (AUTHOR)

Federated deep reinforcement learning for dynamic job scheduling in cloud-edge collaborative manufacturing systems.

Wang, Xiaohan^1,2 (AUTHOR), Zhang, Lin^1,3 (AUTHOR) zhanglin@buaa.edu.cn, Wang, Lihui² (AUTHOR), Vincent Wang, Xi² (AUTHOR), Liu, Yongkui⁴ (AUTHOR)

Real-time AGV scheduling optimisation method with deep reinforcement learning for energy-efficiency in the container terminal yard.

Gong, Lin^1,2 (AUTHOR), Huang, Zijie¹ (AUTHOR), Xiang, Xi¹ (AUTHOR), Liu, Xin^1,2 (AUTHOR) xliu826@bit.edu.cn

Deep reinforcement learning on variable stiffness compliant control for programming-free robotic assembly in smart manufacturing.

Ji, Zhenrui^1,2 (AUTHOR), Liu, Gang^1,2 (AUTHOR), Xu, Wenjun^1,2 (AUTHOR) xuwenjun@whut.edu.cn, Yao, Bitao³ (AUTHOR), Liu, Xuedong^1,2 (AUTHOR), Zhou, Zude¹ (AUTHOR)

A cognitive computing approach for product configuration design based on associative rule mining and deep reinforcement learning.

Wu, Xuanyu^1,2 (AUTHOR), Feng, Yixiong^1,2 (AUTHOR) yxfeng@gzu.edu.cn, Lou, Shanhe³ (AUTHOR), Li, Zhiwu⁴ (AUTHOR), Hong, Zhaoxi² (AUTHOR), Zhang, Ansi¹ (AUTHOR), Jin, Kebing¹ (AUTHOR), Si, Hengyuan⁵ (AUTHOR), Tan, Jianrong² (AUTHOR)

Production optimisation in carbon reduction engineering management.

Wei, Yi-Ming¹ (AUTHOR), Huang, Zhimin² (AUTHOR), Coffman Dalton, D'Maris³ (AUTHOR), Liao, Hua¹ (AUTHOR), Wang, Ke¹ (AUTHOR) wangke03@yeah.net

A novel carbon reduction engineering method-based deep Q-learning algorithm for energy-efficient scheduling on a single batch-processing machine in semiconductor manufacturing.

Kong, Min^1,2 (AUTHOR), Wang, Weizhong¹ (AUTHOR), Deveci, Muhammet^3,4 (AUTHOR) muhammetdeveci@gmail.com, Zhang, Yajing¹ (AUTHOR), Wu, Xuzhong¹ (AUTHOR) xmuwxz@163.com, Coffman, D'Maris³ (AUTHOR)

Performance of deep reinforcement learning algorithms in two-echelon inventory control systems.

Stranieri, Francesco^1,2 (AUTHOR) francesco.stranieri@polito.it, Stella, Fabio¹ (AUTHOR), Kouki, Chaaben³ (AUTHOR)

An improved deep reinforcement learning-based scheduling approach for dynamic task scheduling in cloud manufacturing.

Xiaohan Wang¹, Lin Zhang^1,2 zhanglin@buaa.edu.cn, Yongkui Liu³, Yuanjun Laili^1,4

Digital-twin deep dynamic camera position optimisation for the V-STARS photogrammetry system based on 3D reconstruction.

Likun Wang¹, Zi Wang¹ Sara.Wang@nottingham.ac.uk, Kendall, Peter¹, Gumma, Kevin¹, Turner, Alison¹, Ratchev, Svetan¹