Real-time scheduling for dynamic partial-no-wait multiobjective flexible job shop by deep reinforcement learning

S Luo, L Zhang, Y Fan - IEEE Transactions on Automation …, 2021 - ieeexplore.ieee.org
In modern discrete flexible manufacturing systems, dynamic disturbances frequently occur in
real time and each job may contain several special operations in partial-no-wait constraint …

Dynamic multi-objective scheduling for flexible job shop by deep reinforcement learning

S Luo, L Zhang, Y Fan - Computers & Industrial Engineering, 2021 - Elsevier
In modern volatile and complex manufacturing environment, dynamic events such as new
job insertions and machine breakdowns may randomly occur at any time and different …

Multi-objective reinforcement learning framework for dynamic flexible job shop scheduling problem with uncertain events

H Wang, J Cheng, C Liu, Y Zhang, S Hu, L Chen - Applied Soft Computing, 2022 - Elsevier
The economic benefits for manufacturing companies will be influenced by how it handles
potential dynamic events and performs multi-objective real-time scheduling for existing …

Dynamic scheduling for flexible job shop with new job insertions by deep reinforcement learning

S Luo - Applied Soft Computing, 2020 - Elsevier
In modern manufacturing industry, dynamic scheduling methods are urgently needed with
the sharp increase of uncertainty and complexity in production process. To this end, this …

Dynamic scheduling for flexible job shop using a deep reinforcement learning approach

Y Gui, D Tang, H Zhu, Y Zhang, Z Zhang - Computers & Industrial …, 2023 - Elsevier
Due to the influence of dynamic changes in the manufacturing environment, a single
dispatching rule (SDR) cannot consistently attain better results than other rules for dynamic …

Deep reinforcement learning for dynamic flexible job shop scheduling problem considering variable processing times

L Zhang, Y Feng, Q Xiao, Y Xu, D Li, D Yang… - Journal of Manufacturing …, 2023 - Elsevier
In recent years, the uncertainties and complexity in the production process, due to the
boosted customized requirements, has dramatically increased the difficulties of Dynamic …

Real-time data-driven dynamic scheduling for flexible job shop with insufficient transportation resources using hybrid deep Q network

Y Li, W Gu, M Yuan, Y Tang - Robotics and Computer-Integrated …, 2022 - Elsevier
With the extensive application of automated guided vehicles in manufacturing system,
production scheduling considering limited transportation resources becomes a difficult …

Dynamic scheduling method for job-shop manufacturing systems by deep reinforcement learning with proximal policy optimization

M Zhang, Y Lu, Y Hu, N Amaitik, Y Xu - sustainability, 2022 - mdpi.com
With the rapid development of Industrial 4.0, the modern manufacturing system has been
experiencing profoundly digital transformation. The development of new technologies helps …

Deep reinforcement learning for dynamic flexible job shop scheduling with random job arrival

J Chang, D Yu, Y Hu, W He, H Yu - Processes, 2022 - mdpi.com
The production process of a smart factory is complex and dynamic. As the core of
manufacturing management, the research into the flexible job shop scheduling problem …

Large-scale dynamic scheduling for flexible job-shop with random arrivals of new jobs by hierarchical reinforcement learning

K Lei, P Guo, Y Wang, J Zhang… - IEEE Transactions on …, 2023 - ieeexplore.ieee.org
As the intelligent manufacturing paradigm evolves, it is urgent to design a near real-time
decision-making framework for handling the uncertainty and complexity of production line …