A review of the applications of multi-agent reinforcement learning in smart factories

F Bahrpeyma, D Reichelt - Frontiers in Robotics and AI, 2022 - frontiersin.org
The smart factory is at the heart of Industry 4.0 and is the new paradigm for establishing
advanced manufacturing systems and realizing modern manufacturing objectives such as …

Reinforcement learning for electric vehicle charging scheduling: A systematic review

Z Zhao, CKM Lee, X Yan, H Wang - Transportation Research Part E …, 2024 - Elsevier
As climate change and environmental concerns have become increasingly pressing issues,
electric vehicles (EVs) have emerged as a viable and environmentally-friendly alternative to …

A robust method based on reinforcement learning and differential evolution for the optimal photovoltaic parameter extraction

X Yu, J Zhou - Applied Soft Computing, 2023 - Elsevier
It is crucial to identify the optimal parameters of Photovoltaic (PV) models with the purpose of
evaluating, controlling, and improving PV systems. Lots of optimization algorithms have …

Planning approach for integrating charging stations and renewable energy sources in low-carbon logistics delivery

J Wang, Q Guo, H Sun - Applied Energy, 2024 - Elsevier
To achieve green and low-carbon development in the logistics industry, logistics operators
are promoting the electrification of logistics fleets, which imposes requirements for well …

Data-driven energy management system for flexible operation of hydrogen/ammonia-based energy hub: A deep reinforcement learning approach

D Wen, M Aziz - Energy Conversion and Management, 2023 - Elsevier
In the context of carbon neutrality, multi-energy systems are being designed to enhance the
integration of renewable energy, and the deployment of large-scale energy storage …

Model-free reinforcement learning-based energy management for plug-in electric vehicles in a cooperative multi-agent home microgrid with consideration of travel …

A Salari, M Zeinali, M Marzband - Energy, 2024 - Elsevier
The rise in popularity of plug-in electric vehicles (PEVs) and the increasing use of renewable
energy sources (RESs) have paved the way for advanced energy management systems …

A multi-agent deep reinforcement learning approach for solving the multi-depot vehicle routing problem

A Arishi, K Krishnan - Journal of Management Analytics, 2023 - Taylor & Francis
The multi-depot vehicle routing problem (MDVRP) is one of the most essential and useful
variants of the traditional vehicle routing problem (VRP) in supply chain management (SCM) …

Research on a Charging Mechanism of Electric Vehicles for Photovoltaic Nearby Consumption Strategy

Q He, M Wu, P Sun, J Guo, L Chen, L Jiang, Z Zhang - Electronics, 2022 - mdpi.com
With the promotion of the pilot development of distributed whole county roof photovoltaics in
China, problems such as power consumption, energy regional balance, and grid stability …

A multi-state model for the service quality evaluation of an electric vehicle charging network via universal generating function

Z Zhao, CKM Lee, X Yan - Computers & Industrial Engineering, 2024 - Elsevier
With the large-scale proliferation of electric vehicles (EVs), a comprehensive evaluation of
service quality for EV charging networks is crucial to develop effective policies that address …

A DQN based approach for large-scale EVs charging scheduling

Y Han, T Li, Q Wang - Complex & Intelligent Systems, 2024 - Springer
This paper addresses the challenge of large-scale electric vehicle (EV) charging scheduling
during peak demand periods, such as holidays or rush hours. The growing EV industry has …