Joint optimization of electric bus scheduling and fast charging infrastructure location planning

Transit authorities are transitioning from conventional buses to electric buses (EBs) due to growing concerns about air quality and greenhouse gas emissions. Many mathematical optimization models have been developed for scheduling conventional buses. However, such models would not fit EBs due to their limited travelling range and long charging time. Such operational differences have prompted new research into the literature on the charging station location problem. This study combines EB scheduling with fast-charging infrastructure location planning to minimize total scheduling and charger installation costs. We propose an Integer Linear Programming (ILP) formulation for a path-based model, solved using four developed branch-and-price algorithms, and test their performance across various instances. Our computational experiments show which branching strategy is computationally efficient in terms of execution time and optimality gap. Finally, we conduct a real case study and perform a sensitivity analysis to identify the most cost-effective type of electric bus, considering the specific characteristics of different EB types.