Routing of electric vehicles for logistics industry

Abstract

Nowadays, some logistics companies like SP Express, UPS, DHL have gradually begun to deliver goods using electric vehicles (EV) to achieve carbon neutrality. As far as logistics companies' interest is concerned, an efficient and short vehicle path can reduce transportation costs and increase the processing capacity of customer nodes in each vehicle route. Compared to diesel vehicles, EVs have some battery and traffic restrictions, such as range anxiety, long charging time, and fewer charging stations. For vehicle routing planning, the logistics company should consider these restrictions. In this project, an optimization algorithm was designed to simulate an efficient transport route with EV in the logistics industry. The routing environment includes a depot node, multiple customer nodes and charging station nodes. The logistics company will arrange multiple electric vehicles to complete the delivery with less travel time and efficient node distribution. For the program design, the genetic algorithm (GA) method and Fonseca and Fleming method will optimize the transport route. Also, a battery module was adopted to monitor the charging and discharging process during EV travel. Finally, the optimized result will be drawn into a map.