Deep reinforcement learning in production systems: a systematic literature review
Shortening product development cycles and fully customisable products pose major
challenges for production systems. These not only have to cope with an increased product …
challenges for production systems. These not only have to cope with an increased product …
[HTML][HTML] A review of optimization models and applications in robotic manufacturing systems: Industry 4.0 and beyond
B Vaisi - Decision analytics journal, 2022 - Elsevier
In this review paper, recent developments in robotic problems are cited. A robotic
manufacturing system includes at least a robot-as a material handling device-, a co-worker …
manufacturing system includes at least a robot-as a material handling device-, a co-worker …
Digital twin-driven deep reinforcement learning for adaptive task allocation in robotic construction
In order to accomplish diverse tasks successfully in a dynamic (ie, changing over time)
construction environment, robots should be able to prioritize assigned tasks to optimize their …
construction environment, robots should be able to prioritize assigned tasks to optimize their …
[HTML][HTML] Self-adaptive optimized maintenance of offshore wind turbines by intelligent Petri nets
A Saleh, M Chiachío, JF Salas, A Kolios - Reliability Engineering & System …, 2023 - Elsevier
With the emerging monitoring technologies, condition-based maintenance is nowadays a
reality for the wind energy industry. This is important to avoid unnecessary maintenance …
reality for the wind energy industry. This is important to avoid unnecessary maintenance …
A reinforcement learning-artificial bee colony algorithm for flexible job-shop scheduling problem with lot streaming
Y Li, C Liao, L Wang, Y Xiao, Y Cao, S Guo - Applied Soft Computing, 2023 - Elsevier
As a typical production model in manufacturing industry, Flexible Job-shop Scheduling
Problem (FJSP) has an important impact on enhancing the productivity of enterprises …
Problem (FJSP) has an important impact on enhancing the productivity of enterprises …
A reinforcement learning-driven brain storm optimisation algorithm for multi-objective energy-efficient distributed assembly no-wait flow shop scheduling problem
F Zhao, X Hu, L Wang, T Xu, N Zhu… - International Journal of …, 2023 - Taylor & Francis
A reinforcement learning-driven brain storm optimisation idea (RLBSO) is proposed in this
paper to solve multi-objective energy-efficient distributed assembly no-wait flow shop …
paper to solve multi-objective energy-efficient distributed assembly no-wait flow shop …
Scheduling of resource allocation systems with timed Petri nets: A survey
Resource allocation systems (RASs) belong to a kind of discrete event system commonly
seen in the industry. In such systems, available resources are allocated to concurrently …
seen in the industry. In such systems, available resources are allocated to concurrently …
A novel multi-attention reinforcement learning for the scheduling of unmanned shipment vessels (USV) in automated container terminals
J Zhu, W Zhang, L Yu, X Guo - Omega, 2024 - Elsevier
To improve the operating efficiency of container terminals, we investigate a closed-loop
scheduling method in an autonomous inter-terminal system that employs unmanned …
scheduling method in an autonomous inter-terminal system that employs unmanned …
Q-learning driven multi-population memetic algorithm for distributed three-stage assembly hybrid flow shop scheduling with flexible preventive maintenance
Y Jia, Q Yan, H Wang - Expert Systems with Applications, 2023 - Elsevier
The distributed assembly flow shop scheduling (DAFS) problem has received much
attention in the last decade, and a variety of metaheuristic algorithms have been developed …
attention in the last decade, and a variety of metaheuristic algorithms have been developed …
A collaborative iterated greedy algorithm with reinforcement learning for energy-aware distributed blocking flow-shop scheduling
Energy-aware scheduling has attracted increasing attention mainly due to economic
benefits as well as reducing the carbon footprint at companies. In this paper, an energy …
benefits as well as reducing the carbon footprint at companies. In this paper, an energy …