Big data analytics for intelligent manufacturing systems: A review

J Wang, C Xu, J Zhang, R Zhong - Journal of Manufacturing Systems, 2022‏ - Elsevier
With the development of Internet of Things (IoT), 5 G, and cloud computing technologies, the
amount of data from manufacturing systems has been increasing rapidly. With massive …

A review on learning to solve combinatorial optimisation problems in manufacturing

C Zhang, Y Wu, Y Ma, W Song, Z Le… - IET Collaborative …, 2023‏ - Wiley Online Library
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 …

Deep reinforcement learning for dynamic scheduling of a flexible job shop

R Liu, R Piplani, C Toro - International Journal of Production …, 2022‏ - Taylor & Francis
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 …

Survey on genetic programming and machine learning techniques for heuristic design in job shop scheduling

F Zhang, Y Mei, S Nguyen… - IEEE Transactions on …, 2023‏ - ieeexplore.ieee.org
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 …

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 …

A deep multi-agent reinforcement learning approach to solve dynamic job shop scheduling problem

R Liu, R Piplani, C Toro - Computers & Operations Research, 2023‏ - Elsevier
Manufacturing industry is experiencing a revolution in the creation and utilization of data, the
abundance of industrial data creates a need for data-driven techniques to implement real …

A hybrid artificial bee colony algorithm for flexible job shop scheduling with worker flexibility

G Gong, R Chiong, Q Deng, X Gong - International journal of …, 2020‏ - Taylor & Francis
The traditional flexible job shop scheduling problem (FJSP) considers machine flexibility but
not worker flexibility. Given the influence and potential of human factors in improving …

[HTML][HTML] Industrial-size job shop scheduling with constraint programming

G Da Col, EC Teppan - Operations Research Perspectives, 2022‏ - Elsevier
The job shop scheduling problem is one of the most studied optimization problems to this
day and it becomes more and more important in the light of the fourth industrial revolution …

An improved African vulture optimization algorithm for dual-resource constrained multi-objective flexible job shop scheduling problems

Z He, B Tang, F Luan - Sensors, 2022‏ - mdpi.com
According to the characteristics of flexible job shop scheduling problems, a dual-resource
constrained flexible job shop scheduling problem (DRCFJSP) model with machine and …

Makespan estimation in a flexible job-shop scheduling environment using machine learning

D Tremblet, S Thevenin, A Dolgui - International Journal of …, 2024‏ - Taylor & Francis
ABSTRACT A production plan gives the quantity of products to release on the shop floor in
each period, where a period may represent a week or a month. The plan is the basis for …