Reinforcement learning for logistics and supply chain management: Methodologies, state of the art, and future opportunities

Y Yan, AHF Chow, CP Ho, YH Kuo, Q Wu… - … Research Part E …, 2022 - Elsevier
With advances in technologies, data science techniques, and computing equipment, there
has been rapidly increasing interest in the applications of reinforcement learning (RL) to …

An overview and experimental study of learning-based optimization algorithms for the vehicle routing problem

B Li, G Wu, Y He, M Fan… - IEEE/CAA Journal of …, 2022 - ieeexplore.ieee.org
The vehicle routing problem (VRP) is a typical discrete combinatorial optimization problem,
and many models and algorithms have been proposed to solve the VRP and its variants …

Multi-agent reinforcement learning based resource management in MEC-and UAV-assisted vehicular networks

H Peng, X Shen - IEEE Journal on Selected Areas in …, 2020 - ieeexplore.ieee.org
In this paper, we investigate multi-dimensional resource management for unmanned aerial
vehicles (UAVs) assisted vehicular networks. To efficiently provide on-demand resource …

Analytics and machine learning in vehicle routing research

R Bai, X Chen, ZL Chen, T Cui, S Gong… - … Journal of Production …, 2023 - Taylor & Francis
The Vehicle Routing Problem (VRP) is one of the most intensively studied combinatorial
optimisation problems for which numerous models and algorithms have been proposed. To …

Vehicle routing problem using reinforcement learning: Recent advancements

SM Raza, M Sajid, J Singh - Advanced machine intelligence and signal …, 2022 - Springer
In the realization of smart cities, the most important component is the smart logistics in which
the vehicle routing problem (VRP) plays a significant role. The VRP has been proven to be …

Reinforcement learning-based routing protocols for vehicular ad hoc networks: A comparative survey

RA Nazib, S Moh - IEEE Access, 2021 - ieeexplore.ieee.org
Vehicular-ad hoc networks (VANETs) hold great importance because of their potentials in
road safety improvement, traffic monitoring, and in-vehicle infotainment services. Due to high …

Reinforcement learning-based routing protocols in vehicular ad hoc networks for intelligent transport system (its): A survey

J Lansky, AM Rahmani, M Hosseinzadeh - Mathematics, 2022 - mdpi.com
Today, the use of safety solutions in Intelligent Transportation Systems (ITS) is a serious
challenge because of novel progress in wireless technologies and the high number of road …

Trajectory optimization for drone logistics delivery via attention-based pointer network

F Kong, J Li, B Jiang, H Wang… - IEEE Transactions on …, 2022 - ieeexplore.ieee.org
Drone logistics delivery is a potential booster to redefine the logistics system efficiency,
which has been a new special hot research field. Among that, how to optimize drone …

On-demand vehicular fog computing for beyond 5G networks

W Mao, OU Akgul, B Cho, Y Xiao… - IEEE Transactions on …, 2023 - ieeexplore.ieee.org
Emerging compute-intensive and latency-sensitive vehicular applications are expected to be
deployed at the edge instead of the cloud to shorten the network latency. Mobile fog nodes …

A reinforcement learning approach for rebalancing electric vehicle sharing systems

A Bogyrbayeva, S Jang, A Shah… - IEEE Transactions on …, 2021 - ieeexplore.ieee.org
This paper proposes a reinforcement learning approach for nightly offline rebalancing
operations in free-floating electric vehicle sharing systems (FFEVSS). Due to sparse …