Deep reinforcement learning in smart manufacturing: A review and prospects
To facilitate the personalized smart manufacturing paradigm with cognitive automation
capabilities, Deep Reinforcement Learning (DRL) has attracted ever-increasing attention by …
capabilities, Deep Reinforcement Learning (DRL) has attracted ever-increasing attention by …
Survey of integrated flexible job shop scheduling problems
The flexible job shop scheduling problems (FJSP) has been studied for many years, and
many different mathematical models and solution approaches have been developed. With …
many different mathematical models and solution approaches have been developed. With …
Knowledge-driven two-stage memetic algorithm for energy-efficient flexible job shop scheduling with machine breakdowns
This paper focuses on the multi-objective energy-efficient flexible job shop scheduling
problem with machine breakdowns. To mitigate the impact of machine breakdowns, a …
problem with machine breakdowns. To mitigate the impact of machine breakdowns, a …
[HTML][HTML] Edge computing-based real-time scheduling for digital twin flexible job shop with variable time window
Production scheduling is the central link between enterprise production and operation
management and is also the key to realising efficient, high-quality and sustainable …
management and is also the key to realising efficient, high-quality and sustainable …
Large-scale dynamic scheduling for flexible job-shop with random arrivals of new jobs by hierarchical reinforcement learning
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 …
decision-making framework for handling the uncertainty and complexity of production line …
Flexible job shop scheduling via dual attention network-based reinforcement learning
Flexible manufacturing has given rise to complex scheduling problems such as the flexible
job shop scheduling problem (FJSP). In FJSP, operations can be processed on multiple …
job shop scheduling problem (FJSP). In FJSP, operations can be processed on multiple …
A deep reinforcement learning based algorithm for a distributed precast concrete production scheduling
Y Du, J Li - International Journal of Production Economics, 2024 - Elsevier
The environmental-friendly production demands higher manufacturing efficiency and lower
energy cost; therefore, time-of-use electricity price constraint and distributed production have …
energy cost; therefore, time-of-use electricity price constraint and distributed production have …
An end-to-end deep reinforcement learning method based on graph neural network for distributed job-shop scheduling problem
Abstract Distributed Job-shop Scheduling Problem (DJSP) is a hotspot in industrial and
academic fields due to its valuable application in the real-life productions. For DJSP, the …
academic fields due to its valuable application in the real-life productions. For DJSP, the …
Multi-agent reinforcement learning for real-time dynamic production scheduling in a robot assembly cell
As industry rapidly shifts towards mass personalisation, the need for a decentralised multi-
agent system capable of dynamic flexible job shop scheduling (FJSP) is evident. Traditional …
agent system capable of dynamic flexible job shop scheduling (FJSP) is evident. Traditional …
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 …