This study proposes a model and method for solving the transit timetabling problem with consideration of passenger path choices within a congested and schedule-based transit network. The model has two submodels: transit timetabling and passenger-equilibrium assignment. The transit timetabling submodel generates timetables to improve passengers’ journey experience based on the results of passenger-equilibrium assignment, whereas the passenger-equilibrium assignment loads passengers on transit vehicles based on a fixed vehicle capacity and timetable output from the transit timetabling. An iterative method is developed to connect these two submodels and efficiently determine an optimal solution. The iterative method includes an equilibrium assignment method to simulate passenger loading and suggests a decomposition approach for transit timetabling. The decomposition approach has a significant computational advantage when handling transit systems that involve hundreds of transit vehicles because the algorithm generates a timetable for one transit line in each step rather than for all transit lines. The decomposition approach can therefore handle relatively large problems with more transit lines. The suggested algorithms are analyzed with a hypothetical example and with the practically sized example of South China’s high-speed railway in terms of efficiency, optimality, and applicability.

这项研究提出了一种模型和方法，用于在拥挤且基于时间表的公交网络中考虑乘客路径选择来解决公交时间表问题。该模型有两个子模型：过境时间表和旅客平衡分配。过境时间表子模型基于乘客平衡分配的结果生成时间表，以改善乘客的旅行体验，而乘客平衡分配则基于固定车辆容量和过境时间表输出的时间表，为过境车辆加载乘客。开发了一种迭代方法来连接这两个子模型并有效地确定最佳解决方案。迭代方法包括一个平衡分配方法，以模拟乘客的载运量，并提出一种分解方法，以用于公交时间表。当处理涉及数百辆运输车辆的运输系统时，分解方法具有显着的计算优势，因为该算法在每个步骤中为一条运输线而不是所有运输线生成时间表。因此，分解方法可以通过更多的运输线处理相对较大的问题。本文从效率，最优性和适用性方面，以一个假设的例子和一个华南高速铁路的实际规模例子对建议的算法进行了分析。因此，分解方法可以通过更多的运输线处理相对较大的问题。本文从效率，最优性和适用性方面，以一个假设的例子和一个华南高速铁路的实际规模例子对建议的算法进行了分析。因此，分解方法可以通过更多的运输线处理相对较大的问题。本文从效率，最优性和适用性方面，以一个假设的例子和一个华南高速铁路的实际规模例子对建议的算法进行了分析。