scholarly journals Using a Route-based and Vehicle Type specific Range Constraint for Improving Vehicle Routing Problems with Electric Vehicles

2021 ◽  
Vol 52 ◽  
pp. 517-524
Author(s):  
Ricardo Ewert ◽  
Kai Martins-Turner ◽  
Carina Thaller ◽  
Kai Nagel
Keyword(s):  
Vehicle Routing ◽  
Electric Vehicles ◽  
Vehicle Routing Problems ◽  
Routing Problems ◽  
Vehicle Type

scholarly journals frvcpy: An Open-Source Solver for the Fixed Route Vehicle Charging Problem

2021 ◽  
Author(s):  
Nicholas D. Kullman ◽  
Aurelien Froger ◽  
Jorge E. Mendoza ◽  
Justin C. Goodson
Keyword(s):  
Open Source ◽  
Vehicle Routing ◽  
Electric Vehicle ◽  
Electric Vehicles ◽  
Software Tool ◽  
Sustainable Transportation ◽  
Vehicle Routing Problems ◽  
Routing Problems ◽  
Vehicle Charging ◽  
Community Standard

Electric vehicles offer a pathway to more sustainable transportation, but their adoption entails new challenges not faced by their petroleum-based counterparts. A difficult task in vehicle routing problems addressing these challenges is determining how to make good charging decisions for an electric vehicle traveling a given route. This is known as the fixed route vehicle charging problem. An exact and efficient algorithm for this task exists, but its implementation is sufficiently complex to deter researchers from adopting it. In this work we introduce frvcpy, an open-source Python package implementing this algorithm. Our aim with the package is to make it easier for researchers to solve electric vehicle routing problems, facilitating the development of optimization tools that may ultimately enable the mass adoption of electric vehicles. Summary of Contribution: This work describes a novel software tool for the vehicle routing community. The tool, frvcpy, addresses one of the primary challenges faced by the vehicle routing community when considering problems involving the adoption of electric vehicles (EVs): how to make optimal charging decisions. The state-of-the-art algorithm for solving these problems is sufficiently complex to deter researchers from using it, leading them to adopt less robust methods. frvcpy offers an easy-to-use, lightweight implementation of this algorithm, providing optimal solutions in low (∼5 ms) runtime. It is designed to be easily embedded in larger solution schemes for general EV routing problems, requiring minimal input, offering compatibility with the community standard file types, and offering access both through the command line and a Python API. The tool has thus far proven adaptable, having been used by researchers studying EV routing problems with novel constraints. Our aim with frvcpy is to make it easier for researchers to solve EV routing problems, facilitating the development of optimization tools that may contribute toward the mass adoption of electric vehicles.

Reinforcement Learning With Multiple Relational Attention for Solving Vehicle Routing Problems

2021 ◽  
pp. 1-14
Author(s):  
Yunqiu Xu ◽  
Meng Fang ◽  
Ling Chen ◽  
Gangyan Xu ◽  
Yali Du ◽  
...  
Keyword(s):  
Reinforcement Learning ◽  
Vehicle Routing ◽  
Vehicle Routing Problems ◽  
Routing Problems

scholarly journals A solution approach for multi‐trip vehicle routing problems with time windows, fleet sizing, and depot location

Networks ◽  
2021 ◽  
Author(s):  
Paula Fermín Cueto ◽  
Ivona Gjeroska ◽  
Albert Solà Vilalta ◽  
Miguel F. Anjos
Keyword(s):  
Vehicle Routing ◽  
Time Windows ◽  
Vehicle Routing Problems ◽  
Routing Problems ◽  
Solution Approach ◽  
Fleet Sizing

scholarly journals A review on the electric vehicle routing problems: Variants and algorithms

2021 ◽  
Author(s):  
Hu Qin ◽  
Xinxin Su ◽  
Teng Ren ◽  
Zhixing Luo
Keyword(s):  
Vehicle Routing ◽  
Vehicle Routing Problems ◽  
Location Routing Problem ◽  
Routing Problems ◽  
Routing Problem ◽  
Delivery Problem ◽  
Pickup And Delivery Problem ◽  
The Past ◽  
Location Routing ◽  
Comprehensive Survey

AbstractOver the past decade, electric vehicles (EVs) have been considered in a growing number of models and methods for vehicle routing problems (VRPs). This study presents a comprehensive survey of EV routing problems and their many variants. We only consider the problems in which each vehicle may visit multiple vertices and be recharged during the trip. The related literature can be roughly divided into nine classes: Electric traveling salesman problem, green VRP, electric VRP, mixed electric VRP, electric location routing problem, hybrid electric VRP, electric dial-a-ride problem, electric two-echelon VRP, and electric pickup and delivery problem. For each of these nine classes, we focus on reviewing the settings of problem variants and the algorithms used to obtain their solutions.

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