Integrated optimization of timetabling and vehicle scheduling for pure electric buses considering multiple depots and vehicle types

Reasonable bus timetabling and vehicle scheduling can not only reduce the operating costs of the enterprise, but also improve the service level and passenger satisfaction. However, few studies, to our best knowledge, have addressed time-dependent parameters, multiple depots and multiple vehicle types, the crowding degree of passengers on the bus and varying recharging prices in the integrated optimization model for timetabling and vehicle scheduling of pure electric buses over three time periods. Therefore, this paper first presents a datadriven multi-objective optimization model that considers both the passenger travel cost and the bus enterprise operating cost. Among them, the former includes the costs of waiting time, crowding on the bus, and riding time, while the latter involves the costs of vehicle depreciation, recharging, and deadheading. Second, an improved NSGA-II is used to obtain the Pareto optimal solutions. Then, compare the optimization solutions proposed in this paper with the bus enterprise schemes and the models under different conditions. Finally, bus line 18 in Zhuhai, China, is used as an example to validate the effectiveness of the proposed method. The research results indicate that the proposed method can decrease the mixed cost of both bus enterprise and passengers compared to the single depot and single vehicle type model and the bus enterprise schemes. Compared to the fixed demand model, it can approximately depict the current operational status of the bus enterprise. This study can provide a reference for bus enterprises to make bus timetabling and vehicle scheduling for a single line.