14th International Conference on Industrial Engineering and Operations Management

Electric vehicle routing problem with an on-demand mobile charging system

İhsan Sadati & Bülent Çatay
Publisher: IEOM Society International
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Track: Logistics
Abstract

Many logistics operators predominantly rely on diesel-powered vehicles for their delivery services. However, the adverse external effects of internal combustion engine vehicles have led governments and city authorities to enact more stringent regulations governing freight transportation within urban areas. These initiatives promote the transition to alternative fuel vehicles, with a primary focus on electric vehicles (EVs). Consequently, it is anticipated that EVs will make up a substantial portion of logistics operators' vehicle fleets. Inadequate charging infrastructure has been a significant impediment to the widespread adoption of EVs. Charging at the depot is a practical solution in real-world logistics operations due to limited recharging infrastructure in many regions and the uncertainty surrounding charger availability. While there may be numerous public recharging stations in the area, not all are suitable for commercial vehicles, especially trucks. Furthermore, some companies prefer charging their EVs at their depots due to factors like high energy costs at public stations. Nevertheless, this approach can result in operational inefficiencies, especially for deliveries in peri-urban and rural areas. To address this, offering charging services for EVs, such as deploying mobile chargers (MCs), can enhance the efficiency of EV usage. In other words, a flexible recharging system with an on-demand mobile charging approach can be recommended. We introduce the Electric Vehicle Routing Problem with On-Demand Charging System to tackle these challenges. MCs recharge EV batteries at customer locations along their routes when necessary. We have developed a matheuristic algorithm that combines the variable neighborhood search (VNS) and an exact method.

Published in: 14th International Conference on Industrial Engineering and Operations Management, Dubai, UAE

Publisher: IEOM Society International
Date of Conference: February 12-14, 2024

ISBN: 979-8-3507-1734-1
ISSN/E-ISSN: 2169-8767