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Transition to electrified transit vehicles has attracted a great public attention to achieve a greener public transport service. This work develops a methodology for multi-type electric buses (EBs) accommodating spatio-temporally imbalanced passenger demand to improve significantly the operating efficiency. However, a new complexity of this multi-type EB scheme in contrast to conventional diesel buses occurs because multi-type EBs are characterized by different capacities, limited driving ranges, decisions on recharging time and/or locations and high initial investment costs. This work proposes a new, integrated timetabling and vehicle scheduling problem with shifting departure time to attain an even-load timetable using different types of EBs at a route’s max-load stop, considering the use of fast/opportunity charging strategy. A genetic algorithm associated with right shifting of departure time has been developed to solve the resulting formulation, which is shown to be an NP-hard problem. A numerical example is used to illustrate the developed methodology, and a case study based on a scenario in the city of Dandong, China shows that the scheme of combining multiple vehicle types for a bus route not only can reduce the total cost but also bring out greater benefits than the single vehicle-type operation. From the operator viewpoint, it reduces passenger load surplus cost by approximately 11.2% for small Type A and 14.8% for large Type B. Moreover, the value of leftover pax unit cost has a significant effect on the selection of vehicle types, but has little effect on the number of trips or departures. This work shows that the higher the leftover pax unit cost is, the higher the number of large vehicle types is.

Optimal selection of vehicle types for an electric bus route with shifting departure times