Deep reinforcement learning for dynamic scheduling of a flexible job shop
The ability to handle unpredictable dynamic events is becoming more important in pursuing
agile and flexible production scheduling. At the same time, the cyber-physical convergence …
agile and flexible production scheduling. At the same time, the cyber-physical convergence …
Surrogate-assisted evolutionary multitask genetic programming for dynamic flexible job shop scheduling
Dynamic flexible job shop scheduling (JSS) is an important combinatorial optimization
problem with complex routing and sequencing decisions under dynamic environments …
problem with complex routing and sequencing decisions under dynamic environments …
Evolving scheduling heuristics via genetic programming with feature selection in dynamic flexible job-shop scheduling
Dynamic flexible job-shop scheduling (DFJSS) is a challenging combinational optimization
problem that takes the dynamic environment into account. Genetic programming …
problem that takes the dynamic environment into account. Genetic programming …
[HTML][HTML] Designing and developing smart production planning and control systems in the industry 4.0 era: a methodology and case study
In furtherance of emerging research within smart production planning and control (PPC), this
paper prescribes a methodology for the design and development of a smart PPC system. A …
paper prescribes a methodology for the design and development of a smart PPC system. A …
Scheduling under uncertainty for Industry 4.0 and 5.0
This article provides a review about how uncertainties in increasingly complex production
and supply chains should be addressed in scheduling tasks. Uncertainty management will …
and supply chains should be addressed in scheduling tasks. Uncertainty management will …
Scheduling in Industrial environment toward future: insights from Jean-Marie Proth
According to [Dolgui, Alexandre, and Jean Marie Proth. 2010. Supply Chain Engineering:
Useful Methods and Techniques. Vol. 539. Springer.], advancing tactical levels in production …
Useful Methods and Techniques. Vol. 539. Springer.], advancing tactical levels in production …
Survey on genetic programming and machine learning techniques for heuristic design in job shop scheduling
Job shop scheduling (JSS) is a process of optimizing the use of limited resources to improve
the production efficiency. JSS has a wide range of applications, such as order picking in the …
the production efficiency. JSS has a wide range of applications, such as order picking in the …
Heuristic and metaheuristic methods for the parallel unrelated machines scheduling problem: a survey
M Ɖurasević, D Jakobović - Artificial Intelligence Review, 2023 - Springer
Scheduling has an immense effect on various areas of human lives, be it though its
application in manufacturing and production industry, transportation, workforce allocation, or …
application in manufacturing and production industry, transportation, workforce allocation, or …
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 …
boosted customized requirements, has dramatically increased the difficulties of Dynamic …
[HTML][HTML] Machine learning and optimization for production rescheduling in Industry 4.0
Along with the fourth industrial revolution, different tools coming from optimization, Internet of
Things, data science, and artificial intelligence fields are creating new opportunities in …
Things, data science, and artificial intelligence fields are creating new opportunities in …