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) …

A new AGV scheduling algorithm based on harmony search for material transfer in a real-world manufacturing system

G Li, B Zeng, W Liao, X Li… - Advances in Mechanical …, 2018 - journals.sagepub.com
With the development of advanced manufacturing technology, more and more enterprises
utilize automated guided vehicles to transfer materials for computer numerical control …

Evolutionary algorithm incorporating reinforcement learning for energy-conscious flexible job-shop scheduling problem with transportation and setup times

G Zhang, S Yan, X Song, D Zhang, S Guo - Engineering Applications of …, 2024 - Elsevier
Flexible job-shop scheduling is considerably important in the modern intelligent
manufacturing factory. In a real job shop, transportation and setup times account for a large …

An effective hybrid collaborative algorithm for energy-efficient distributed permutation flow-shop inverse scheduling

J Mou, P Duan, L Gao, X Liu, J Li - Future Generation Computer Systems, 2022 - Elsevier
Distributed scheduling problem, a novel model of intelligent manufacturing, urgently needs
new scheduling methods to meet the dynamic market demand. The inverse scheduling in a …

Multi-objective green scheduling of integrated flexible job shop and automated guided vehicles

G Xu, Q Bao, H Zhang - Engineering Applications of Artificial Intelligence, 2023 - Elsevier
The traditional flexible job shop scheduling problem (FJSP) ignores transportation issues or
merely introduces a time lag for transportation tasks while assuming an infinite number of …

A review of reinforcement learning based intelligent optimization for manufacturing scheduling

L Wang, Z Pan, J Wang - Complex System Modeling and …, 2021 - ieeexplore.ieee.org
As the critical component of manufacturing systems, production scheduling aims to optimize
objectives in terms of profit, efficiency, and energy consumption by reasonably determining …

Research on flexible job-shop scheduling problem in green sustainable manufacturing based on learning effect

Z Peng, H Zhang, H Tang, Y Feng, W Yin - Journal of Intelligent …, 2022 - Springer
As one of the manufacturing industries with high energy consumption and high pollution,
sand casting is facing major challenges in green manufacturing. In order to balance …

Intelligent scheduling and reconfiguration via deep reinforcement learning in smart manufacturing

S Yang, Z Xu - International Journal of Production Research, 2022 - Taylor & Francis
To realise the intelligent decision-making of dynamic scheduling and reconfiguration, we
studied the intelligent scheduling and reconfiguration with dynamic job arrival for a …

Efficient multiobjective optimization for an AGV energy-efficient scheduling problem with release time

WQ Zou, QK Pan, L Wang, ZH Miao, C Peng - Knowledge-Based Systems, 2022 - Elsevier
In recent years, green manufacturing has attracted wide attention from researchers.
However, the energy efficiency problem in matrix manufacturing workshops is still a blank …

Optimization of waiting time for electric vehicles using a fuzzy inference system

S Hussain, YS Kim, S Thakur… - IEEE Transactions on …, 2022 - ieeexplore.ieee.org
Electric vehicles (EVs) need to be recharged at intermediate locations, such as shopping
malls, restaurants, and parking lots, to meet the daily commute requirements of their users …