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A review on learning to solve combinatorial optimisation problems in manufacturing
An efficient manufacturing system is key to maintaining a healthy economy today. With the
rapid development of science and technology and the progress of human society, the …
rapid development of science and technology and the progress of human society, the …
[HTML][HTML] Graph neural networks for job shop scheduling problems: A survey
Job shop scheduling problems (JSSPs) represent a critical and challenging class of
combinatorial optimization problems. Recent years have witnessed a rapid increase in the …
combinatorial optimization problems. Recent years have witnessed a rapid increase in the …
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 …
Solving flexible job shop scheduling problems via deep reinforcement learning
Flexible job shop scheduling problem (FJSSP), as a variant of the job shop scheduling
problem, has a larger solution space. Researchers are always looking for good methods to …
problem, has a larger solution space. Researchers are always looking for good methods to …
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 …
Manufacturing in the age of human-centric and sustainable industry 5.0: application to holonic, flexible, reconfigurable and smart manufacturing systems
This paper provides a classification of manufacturing types in terms of new technological
tools provided in the Industry 5.0 framework. The manufacturing types agile, holonic, flexible …
tools provided in the Industry 5.0 framework. The manufacturing types agile, holonic, flexible …
Dynamic scheduling for flexible job shop with insufficient transportation resources via graph neural network and deep reinforcement learning
M Zhang, L Wang, F Qiu, X Liu - Computers & Industrial Engineering, 2023 - Elsevier
The smart workshop is a powerful tool for manufacturing companies to reduce waste and
improve production efficiency through real-time data analysis for self-organized production …
improve production efficiency through real-time data analysis for self-organized production …
Deep reinforcement learning-based memetic algorithm for energy-aware flexible job shop scheduling with multi-AGV
The integration of manufacturing and logistics scheduling issues in shop operations has
garnered considerable attention. Concurrently, escalating concerns about global warming …
garnered considerable attention. Concurrently, escalating concerns about global warming …
A deep reinforcement learning model for dynamic job-shop scheduling problem with uncertain processing time
The dynamic job-shop scheduling problem (DJSP) is a type of scheduling tasks where
rescheduling is performed when encountering the uncertainties such as the uncertain …
rescheduling is performed when encountering the uncertainties such as the uncertain …
[HTML][HTML] Job shop smart manufacturing scheduling by deep reinforcement learning
Smart manufacturing scheduling (SMS) requires a high degree of flexibility to successfully
cope with changes in operational decision level planning processes in today's production …
cope with changes in operational decision level planning processes in today's production …