Improving the route planning of battery electric freight vehicles through speed optimization

Official URL: https://dx.doi.org/10.1109/ISAS60782.2023.10391678

The electrification of logistics vehicles has been hindered by range anxiety, even though battery technology has advanced significantly in recent years. This is especially true for battery electric freight vehicles, which may need to recharge at stations en route due to their limited driving range. To address this issue, we revisit the Electric Vehicle Routing Problem with Time Windows (EVRPTW), which aim to optimize route plans and charge schedules of electric vehicles used for last-mile deliveries. We extend this problem to the EVRPTW and Speed Optimization and present its 0-1 mixed-integer linear programming formulation. We then conduct computational tests using an off-the-shelf solver to investigate the impact of speed and cargo load on the route plans. Our findings show that optimizing the speed of the fleet can result in substantial savings.