Reinforcement learning for logistics and supply chain management: Methodologies, state of the art, and future opportunities
With advances in technologies, data science techniques, and computing equipment, there
has been rapidly increasing interest in the applications of reinforcement learning (RL) to …
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
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 …
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
In this paper, we investigate multi-dimensional resource management for unmanned aerial
vehicles (UAVs) assisted vehicular networks. To efficiently provide on-demand resource …
vehicles (UAVs) assisted vehicular networks. To efficiently provide on-demand resource …
Analytics and machine learning in vehicle routing research
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 …
optimisation problems for which numerous models and algorithms have been proposed. To …
Vehicle routing problem using reinforcement learning: Recent advancements
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 …
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
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 …
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 …
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
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 …
which has been a new special hot research field. Among that, how to optimize drone …
On-demand vehicular fog computing for beyond 5G networks
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 …
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
This paper proposes a reinforcement learning approach for nightly offline rebalancing
operations in free-floating electric vehicle sharing systems (FFEVSS). Due to sparse …
operations in free-floating electric vehicle sharing systems (FFEVSS). Due to sparse …