Optimizing centralized dispatching of flexible feeder transit to provide transport and transfer services is important and theoretically challenging for real-world applications. Considering transfer coordination with regular public transit, a multiobjective optimization model that can output an operation plan containing vehicle routes and a timetable for a bus fleet is proposed. By establishing constraints for parameters such as maximum acceptable advance or delay time of transfer, rated passenger capacity, and maximum travel time of a single trip, the proposed model attempts to maximize the successful response ratio, minimize the passengers’ average time costs, and minimize the operating costs of a single passenger. A genetic algorithm was designed to solve the optimal solution, and computational experiments were conducted in a residential area in Beijing. Results reveal that the proposed model and algorithm can be applied in the operation of flexible feeder transit. Moreover, compared with the distributed dispatching method, the value of the optimal objective function in the proposed model was improved by 26%. Although the successful response ratio showed a 29.3% increase and the average passenger time cost showed a small drop, the operating costs per passenger were reduced by 30.7%. The different weight coefficients of the subobjective function and maximum acceptable advance or delay time of transfer could result in different optimal operation plans. Essentially, the optimization procedures for the successful response ratio and the operating costs are in the same direction, whereas the one for the passenger’ cost is in the opposite direction. However, operators should select appropriate values to optimize operation plans.
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