Heterogeneous fleet electric vehicle routing optimization for logistic distribution with time windows and simultaneous pick-up and delivery service

Abstract

Nowadays, with fierce competition of logistic industry, a large number of logistics enterprises work at cutting down cost expenses in transport activities. Besides, electric vehicles (EVs) become popular currently because of its property of environmental friendliness and cost-saving. With the EVs becoming the main means of transportation in logistics enterprises, formulating route optimization schemes that accord with the characteristics of EVs has become an urgent problem to be solved. This paper mainly studies heterogeneous fleet electric vehicle routing problem with time windows and simultaneous pickup and delivery (HFEVRPTW-PD) to improve the vehicle utilization and reduce carbon emissions, which is of great significance to protect environment and improve the quality of service. According to the actual requirements of most logistics enterprises in reality, a mixed-integer mathematical programming model is formulated with the goal of minimizing total traveling distance, in which we consider the energy consumption analysis associated with travel time and load of EVs. The variable neighborhood search (VNS) algorithm is applied to solve the proposed model, where virtual distribution centers are inserted into the traveling sequence to represent the route of multiple vehicles. Ultimately, numerical experiments and sensitivity analyses are carried out to test the performance of VNS. The experimental results show the effectiveness of the improved VNS and indicate that reasonable choice of EVs can effectively improve the economic efficiency.