Electric vehicle routing problem considering energy differences of charging stations

Abstract

In order to promote green and sustainable development of the transportation industry, an increasing number of logistics companies are deploying Electric Vehicles (EVs) to provide logistics distribution services. However, whether EVs are truly low-carbon remains to be evaluated. Therefore, this paper studies an Electric Vehicle Routing Problem Considering Energy Differences of Charging Stations (EVRPEDCS) and constructs a Mixed Integer Programming (MIP) model based on the calculation formula of EV energy consumption and carbon emissions. With the goal of minimizing the economic and environmental costs of logistics distribution enterprises, an Improved Ant Colony Algorithm (IACA) is designed to conduct comprehensive numerical experiments and verify the efficacy of the suggested model and method. The test results demonstrate that IACA performs well and can provide high-quality solutions. Moreover, the experiment tests the carbon emission difference of EV transportation under energy differences of charging stations, finding that EVRPEDCS can help logistics companies reduce carbon emissions by up to 89.69% on average and decrease charging costs by 41.26% on average, which significantly improves EV distribution's environmental and economic benefits. This work can provide helpful advice for the future growth of the transportation sector.