Abstract
Coordinated bus timetables and vehicle scheduling can reduce bus enterprise operating costs, reduce passenger travel time, and improve passenger satisfaction. However, to the best of our knowledge, few studies have simultaneously considered parameters such as multiple depots and multiple vehicle types, time-dependent transfer rate, variable transfer time thresholds, and the importance of transfer stations in the integrated optimization of timetable coordination and vehicle scheduling for pure electric buses. Therefore, this paper first constructs a bi-objective model targeting passenger travel time and bus enterprise operating costs. The former consists of waiting and riding time, while the latter involves the costs of depreciation, recharging, and deadheading. Second, an improved non-dominated sorting genetic algorithm II (NSGA-II) is employed to obtain Pareto optimal solutions. Moreover, the optimization approach proposed in this paper is compared with the current scheme, the sequential method, and the different models. Finally, the validity is verified by Zhuhai, China. Our proposed optimization approach can reflect the actual operation of bus enterprises, and has certain advantages compared with the current scheme, the sequential method, and the models under different conditions. This study can provide a reference for bus enterprises to formulate the bus timetable and vehicle scheduling.
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