Joint Optimization of Wireless Charging Station Location and Operation Scheduling for Electric Buses Under Uncertain Demand

In the context of electric bus route operations, the introduction of wireless charging facilities significantly impacts the operational scheduling of bus fleets. This study focuses on a single bus route and proposes a joint optimization model for determining departure frequencies and charging station locations under uncertain demand conditions. The model aims to minimize both user travel costs and transit operation costs by jointly optimizing departure schedules across different time periods, electric bus assignments, and wireless charging station placement. An adaptive genetic algorithm (AGA) is developed to solve the model efficiently. A case study based on a real-world bus route in China demonstrates that the proposed strategy not only improves system performance but also yields tangible benefits—reducing the required number of electric buses by 29.4%, shortening departure intervals by 12.5%, and lowering daily operational costs by 10.5%.