Multi-vehicle routing problems with soft time windows: A multi-agent reinforcement learning approach
Multi-vehicle routing problem with soft time windows (MVRPSTW) is an indispensable
constituent in urban logistics distribution systems. Over the past decade, numerous methods …
constituent in urban logistics distribution systems. Over the past decade, numerous methods …
Real-time deep reinforcement learning based vehicle navigation
Traffic congestion has become one of the most serious contemporary city issues as it leads
to unnecessary high energy consumption, air pollution and extra traveling time. During the …
to unnecessary high energy consumption, air pollution and extra traveling time. During the …
The vehicle routing problem: State of the art classification and review
K Braekers, K Ramaekers… - Computers & industrial …, 2016 - Elsevier
Over the past decades, the Vehicle Routing Problem (VRP) and its variants have grown ever
more popular in the academic literature. Yet, the problem characteristics and assumptions …
more popular in the academic literature. Yet, the problem characteristics and assumptions …
Deep reinforcement learning approach to solve dynamic vehicle routing problem with stochastic customers
In real-world urban logistics operations, changes to the routes and tasks occur in response
to dynamic events. To ensure customers' demands are met, planners need to make these …
to dynamic events. To ensure customers' demands are met, planners need to make these …
Rbg: Hierarchically solving large-scale routing problems in logistic systems via reinforcement learning
The large-scale vehicle routing problems (VRPs) are defined based on the classical VRPs
with thousands of customers. It is an important optimization problem in modern logistic …
with thousands of customers. It is an important optimization problem in modern logistic …
Learning collaborative policies to solve np-hard routing problems
Recently, deep reinforcement learning (DRL) frameworks have shown potential for solving
NP-hard routing problems such as the traveling salesman problem (TSP) without problem …
NP-hard routing problems such as the traveling salesman problem (TSP) without problem …
Deep reinforcement learning for the electric vehicle routing problem with time windows
The past decade has seen a rapid penetration of electric vehicles (EVs) as more and more
logistics and transportation companies start to deploy electric vehicles (EVs) for service …
logistics and transportation companies start to deploy electric vehicles (EVs) for service …
Deep reinforcement learning for transportation network combinatorial optimization: A survey
Q Wang, C Tang - Knowledge-Based Systems, 2021 - Elsevier
Traveling salesman and vehicle routing problems with their variants, as classic
combinatorial optimization problems, have attracted considerable attention for decades of …
combinatorial optimization problems, have attracted considerable attention for decades of …
The vehicle routing problem: State-of-the-art classification and review
SY Tan, WC Yeh - Applied Sciences, 2021 - mdpi.com
Transportation planning has been established as a key topic in the literature and social
production practices. An increasing number of researchers are studying vehicle routing …
production practices. An increasing number of researchers are studying vehicle routing …
Hybrid adaptive large neighborhood search for vehicle routing problems with depot location decisions
This article considers three variants of the vehicle routing problem (VRP). These variants
determine the respective depot locations from which customers are supplied, ie, the two …
determine the respective depot locations from which customers are supplied, ie, the two …