WANG Xiaochao, ZHU Changfeng, SUN Yuanguang, et al. Optimization study on train service frequency of intercity railways under bus-style operation modeJ. Urban Mass Transit, 2026, 29(2): 167-173. DOI: 10.16037/j.1007-869x.20240037
Citation: WANG Xiaochao, ZHU Changfeng, SUN Yuanguang, et al. Optimization study on train service frequency of intercity railways under bus-style operation modeJ. Urban Mass Transit, 2026, 29(2): 167-173. DOI: 10.16037/j.1007-869x.20240037

Optimization Study on Train Service Frequency of Intercity Railways under Bus-style Operation Mode

  • Objective The bus-style operation of intercity railways is an important measure to support and guide the development of urban agglomerations and metropolitan areas. Reasonably optimizing station stop schemes and service frequency is an effective way to meet travel demand within the region, enhance the efficiency of railway transportation enterprises, and promote the integration of urban agglomerations and metropolitan areas. Therefore, it is necessary to conduct an optimization study on the train service frequency of intercity railways under the bus-style operation mode.
    Method Based on the characteristics of the bus-style operation of intercity railways, an alternative set of train stop schemes is proposed. Passenger travel and enterprise operation costs are analyzed, and a bi-objective optimization model is constructed with the two mentioned costs as objectives, train service frequency as the decision variable, and taking into account the constraints such as section capacity, passenger flow delivery volume, and station capacity. The NSGA-Ⅱ (Non-dominated Sorting Genetic Algorithm Ⅱ) algorithm is adopted to solve the proposed optimization model. Considering the interests of both passengers and enterprises, fuzzy logic compromise is applied to screen the solution set of the Pareto optimal frontier. Taking the bus-style operation of the Changsha-Zhuzhou-Xiangtan Intercity Railway as a case study, the obtained peak-hour intercity travel passenger flow is preprocessed, the optimization results and model-related parameters are discussed and analyzed.
    Result & Conclusion  After optimization, six train station stop schemes (stop at every station, non-stop service and selective stop), and corresponding service frequencies (4 trains, 5 trains, or 6 trains) under Pareto non-dominated solutions are obtained. According to the screening results, four trains should be in operation during the peak hours, among which the service frequencies for the stop-at-every-station, non-stop service, and selective stop schemes are 1 train, 1 train, and 2 trains respectively. When the station stop cost fluctuates within the interval of 500-800 CNY, most of the compromise solutions are distributed along three optimal compromise distribution lines. Under such circumstances, within the acceptable range of different passenger travel costs, the uncertainty in train stop costs has the least impact on the enterprise operating costs.
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