Mobile charging service optimization for electric vehicles

Mobile charging stations (MCSs) offer flexible, portable, and scalable alternatives to fixed charging stations (FCSs) for electric vehicles. To develop a cost-effective and efficient mobile charging fleet, this study proposes a bi-objective programming model to address the joint scheduling and routing problem of MCSs considering the layout of FCSs. The objectives are to minimize the total travel distance of MCSs and maximize the system coverage level. The weighted sum method and linear relaxation technique are employed to transform the proposed model into a single-objective integer linear programming model solved by the Gurobi solver. A case study in the Futian District of Shenzhen, China shows that the integration of MCSs results in a 6.7% improvement in the system coverage level. The experimental results provide quantitative insights into the impact of various MCS configurations on objectives. Additionally, the operational data of MCSs offer valuable references for the strategic planning of FCSs.