[HTML][HTML] Energy-efficient scheduling in job shop manufacturing systems: a literature review

JMRC Fernandes, SM Homayouni, DBMM Fontes - Sustainability, 2022 - mdpi.com
Energy efficiency has become a major concern for manufacturing companies not only due to
environmental concerns and stringent regulations, but also due to large and incremental …

A machine learning approach for energy-efficient intelligent transportation scheduling problem in a real-world dynamic circumstances

J Mou, K Gao, P Duan, J Li, A Garg… - IEEE transactions on …, 2022 - ieeexplore.ieee.org
This paper provides a novel intelligent scheduling strategy for a real-world transportation
dynamic scheduling case from an engine workshop of general motor company (GMEW) …

Knowledge-based reinforcement learning and estimation of distribution algorithm for flexible job shop scheduling problem

Y Du, J Li, X Chen, P Duan… - IEEE Transactions on …, 2022 - ieeexplore.ieee.org
Inthis study, a flexible job shop scheduling problem with time-of-use electricity price
constraint is considered. The problem includes machine processing speed, setup time, idle …

Precast production scheduling in off-site construction: Mainstream contents and optimization perspective

L Wang, Y Zhao, X Yin - Journal of Cleaner Production, 2023 - Elsevier
Precast production scheduling (PPS) is a key factor that enables efficient off-site construction
(OSC) and has received considerable attention from researchers. However, there is still a …

A reinforcement learning approach for flexible job shop scheduling problem with crane transportation and setup times

Y Du, J Li, C Li, P Duan - IEEE Transactions on Neural …, 2022 - ieeexplore.ieee.org
Flexible job shop scheduling problem (FJSP) has attracted research interests as it can
significantly improve the energy, cost, and time efficiency of production. As one type of …

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 …

QMOEA: A Q-learning-based multiobjective evolutionary algorithm for solving time-dependent green vehicle routing problems with time windows

R Qi, J Li, J Wang, H Jin, Y Han - Information Sciences, 2022 - Elsevier
The vehicle routing problem with time windows (VRPTW) is critical in the fields of operations
research and combinatorial optimization. To promote research on the multiobjective …

A Q-learning-based hyper-heuristic evolutionary algorithm for the distributed flexible job-shop scheduling problem with crane transportation

ZQ Zhang, FC Wu, B Qian, R Hu, L Wang… - Expert Systems with …, 2023 - Elsevier
With the globalization and sustainable development of the modern manufacturing industry,
distributed manufacturing and scheduling systems that consider environmental effects have …

Historical information based iterated greedy algorithm for distributed flowshop group scheduling problem with sequence-dependent setup times

X He, QK Pan, L Gao, JS Neufeld, JND Gupta - Omega, 2024 - Elsevier
Distributed flowshop group scheduling problem (DFGSP) is commonly seen in modern
industry. However, research works on DFGSP with total flow time criterion are rarely …

A hybrid estimation of distribution algorithm for distributed flexible job shop scheduling with crane transportations

Y Du, J Li, C Luo, L Meng - Swarm and Evolutionary Computation, 2021 - Elsevier
Distributed flexible job shop scheduling has attracted research interest due to the
development of global manufacturing. However, constraints including crane transportation …