2015-2019 e-VRO : Electric Vehicle Routing Optimization

Electric Vehicle Routing Optimization - e-VRO  

Electric vehicles (EVs) are one of the most promising technologies to reduce petroleum dependency and greenhouse gas emissions. The latter, is especially true when we consider the potential benefits of using EVs for freight transportation, which is believed to be responsible for as much as 30% of emissions in the European Union. Companies such as La Poste, UPS, and Coca-Cola keep have started to add EVs to their fleets, mostly to serve urban and last-mile operations. However, the massive adoption of EVs for freight transportation is still hampered by technical constraints such as low driving ranges and long battery charging times. In recent years, considerable research has been, and still is, devoted to overcome these constraints via technological advances in battery capacity, electrical efficiency, and battery charging speed. However, a considerable effort is still needed to develop fleet management tools able to cope with these restricting EV features. One of the fields in which the void is more critical is that of optimization techniques for solving electric vehicle routing problems (e-VRPs).

Vehicle routing problems are concerned with the design of efficient routes to deliver goods and services from (to) central depots to (from) customer locations satisfying specific business constraints. In the last 50 years, a vast amount of research has been devoted to solve a number of VRP variants. Unfortunately, most of the existing solution approaches are difficult, if not impossible, to use in the context in which routes are performed by EVs. Indeed, classical VRP variants consider that internal combustion engine powered vehicles perform the routes. These vehicles have a long and easy-to-restore driving range (because petrol stations are available almost everywhere and tank refueling takes a negligible time). As a result, most classical routing algorithms focus on designing only one (long) route per vehicle and do not need to care for scheduling visits to refueling stations. In contrast, due to the short driving range and long battery recharging times of EVs and the limited availability of charging infrastructure, routing algorithms for e-VRPs need to consider i) multiple routes per vehicle (with a battery recharge in between), ii) en route detours to charging stations, and iii) coordinated access of the different vehicles to the recharging infrastructure. To address these challenges, in recent years, the vehicle routing community has started to develop techniques specially tailored for e-VRPs; however, most of the underlying problems remain open or even unexplored. The main objective of this project is to contribute to this effort by designing, implementing, testing, and disseminating optimization methods for solving e-VRPs.

It is worth noting that charging infrastructure ownership impacts the definition of the operational constraints and problem parameters in e-VRPs. To cover a wide range of practical settings, the project is structured around 3 work packages (WP), each, dealing with a particular type of ownership. The first WP focuses on studying e-VRPs rising in the context of private charging infrastructure. In this context the route planner owns both the fleet of vehicles and the charging stations. The second WP studies e-VRPs in the context of public charging infrastructure. Contrary to the first scenario, in this setup the route planner owns only the fleet of vehicles and must compete with other users for access to the charging infrastructure. The third WP addresses problems that are common to both infrastructure ownership scenarios.

More Information here.