Solving line balancing and AGV scheduling problems for intelligent decisions using a Genetic-Artificial bee colony algorithm

J Mumtaz, KA Minhas, M Rauf, L Yue, Y Chen - Computers & Industrial …, 2024 - Elsevier
Due to the rapid advancement of technology, the demand for electronic devices in various
sectors such as consumer electronics, automotive, telecommunications, healthcare, and …

Review on ensemble meta-heuristics and reinforcement learning for manufacturing scheduling problems

Y Fu, Y Wang, K Gao, M Huang - Computers and Electrical Engineering, 2024 - Elsevier
With the development of Artificial Intelligence, Internet of Things and Big Data, intelligent
manufacturing has become a new and popular trend in manufacturing industries …

Energy-efficient motion planning of an autonomous forklift using deep neural networks and kinetic model

M Mohammadpour, S Kelouwani, MA Gaudreau… - Expert Systems with …, 2024 - Elsevier
Abstract Autonomous Forklifts (AFs) play a vital role in smart factories, particularly in the
transportation of heavy loads. However, their energy consumption poses a significant …

An efficient Q-learning integrated multi-objective hyper-heuristic approach for hybrid flow shop scheduling problems with lot streaming

Y Chen, J Du, J Mumtaz, J Zhong, M Rauf - Expert Systems with …, 2025 - Elsevier
Efficient scheduling in flow shop environments with lot streaming remains a critical
challenge in various industrial settings, necessitating innovative approaches to optimize …

A review of spider monkey optimization: modification and its biomedical application

A Agrawal, D Garg, D Popli, A Banerjee, A Raj… - International Journal on …, 2023 - Springer
In recent times, researchers have increasingly turned their attention to nature-inspired
algorithms that draw insights from the cognitive behaviors of animals, insects, and birds …

Multi-objective optimization of the mixed-flow intelligent production line for automotive MEMS pressure sensors

Q Zhang, H Li, S Shen, W Cao, J Jiang, W Tang… - Applied Intelligence, 2025 - Springer
Intelligent manufacturing can provide powerful support for the digital transformation of
manufacturing industry. Micro-electro-mechanical system (MEMS) sensors have been …

Multi-objective optimization of work package scheme problem to minimize project carbon emissions and cost

Y Zhang, X Li, Y Teng, GQP Shen, S Bai - Computers & Industrial …, 2025 - Elsevier
The construction industry accounts for around 30% of global energy consumption and 33%
of CO 2 emissions. For the carbon neutrality initiative, reducing carbon emissions from …

Batch processing machine scheduling problems using a self-adaptive approach based on dynamic programming

Y Chen, X Zhao, J Mumtaz, C Guangyuan… - Computers & Operations …, 2025 - Elsevier
With the increasing trend of smart electronic devices, interlinked industries face various
challenges in meeting market demand. The demand for customized small-batch and multi …

[HTML][HTML] A Discrete Brain Storm Optimization Algorithm for Hybrid Flowshop Scheduling Problems with Batch Production at Last Stage in the Steelmaking-Refining …

K Peng, C Zhang, W Shen, X Pang, Y Mei, X Deng - Sensors, 2024 - mdpi.com
The iron and steel industry is energy-intensive due to the large volume of steel produced
and its high-temperature and high-weight characteristics, sensors such as high-temperature …

Finite Potential Game Heuristic Algorithm for Workload Allocation in Dual-Gantry Placement Machines

Q Pi, J Yu, H Sun, X Yu, Z Li, J Qiu… - IEEE Transactions …, 2024 - ieeexplore.ieee.org
Dual-gantry surface mount optimization effectively improves the productivity of printed circuit
board assembly (PCBA), but also brings new challenges. Optimizing workload allocation to …