AbstractWith the development of new energy technologies, dual-source trolleybuses are widely used in public transportation systems. A synergistic schedule can further improve the service quality of vehicles and optimize the passenger travel experience. This study investigated the synchronized scheduling of dual-source trolleybus networks to reduce the transfer time of passengers and the fleet size problem to reduce the operating cost of enterprises. A bi-objective mixed-integer linear programming model was developed to maximize the total synchronizations and minimize the total fleet size of dual-source trolleybus lines. A two-stage algorithm was designed to obtain multiple sets of Pareto effective solutions. Meanwhile, to demonstrate the effectiveness of the proposed method, the results of numerical examples solved by the two-stage algorithm were compared with those of a genetic algorithm (GA) and a nondominated sorting genetic algorithm (NSGA-II). A real-world case study based on the Beijing dual-source trolleybus network was studied to validate the proposed model. The results show that the model can obtain synchronized schedules. The optimization of the number of synchronizations and fleet size is obvious. The model and algorithm can be applied to a large dual-source trolleybus network.

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