This paper aims to optimize demand-oriented train timetables under overtaking operations for a high-speed rail corridor. With the application of the constructed space-time network representation, the timetabling and skip-stopping decisions in response to passenger demand for heterogeneous train traffic are formulated into an integer linear programming model. Specifically, we carefully assign the hour-dependent origin-to-destination demand to the skip-stop-flexible timetable by using a group of tailored constraints that bind the origin station and destination station together. While solving the proposed model under the column-generation-based framework, the biggest barrier is that the pricing subproblem cannot be successfully solved through the standard dynamic programming algorithm, because the dual price from the demand constraint is dependent upon two coupled stations. To dynamically eliminate the indivisibility attached to the demand-oriented timetabling problem, we propose a novel approach to replace the two-station-dependent dual variable with its single-station-dependent surrogate counterpart. A branch-and-price-and-cut procedure is also conducted to achieve the corresponding integer solutions, where specific families of valid inequalities are selected to narrow the feasible solutions in the restricted master problem. Finally, numerical experiments are implemented to demonstrate the efficiency and effectiveness of the proposed method.

本文旨在优化高铁走廊超车操作下以需求为导向的火车时刻表。借助构建的时空网络表示，将响应旅客对异类火车交通需求的时间表和停站决策制定为整数线性规划模型。具体来说，我们通过使用一组将始发站和目标站绑定在一起的定制约束，将与小时相关的始发地到目的地的需求小心地分配给灵活的跳停时间表。在基于列生成的框架下解决建议的模型时，最大的障碍是无法通过标准动态规划算法成功解决定价子问题，因为来自需求约束的双重价格取决于两个耦合站。为了动态消除依附于面向需求的时间表问题的不可分割性，我们提出了一种新颖的方法，以其依赖于单工位的替代物替换具有两工位的对偶变量。还进行了分支和降价和割价的程序来获得相应的整数解，其中选择有效不等式的特定族来缩小受限主问题中的可行解。最后，通过数值实验证明了该方法的有效性和有效性。我们提出了一种新颖的方法，用其依赖于单工位的替代物替代依赖于两工位的对偶变量。还进行了分支和降价和割价的程序来获得相应的整数解，其中选择有效不等式的特定族来缩小受限主问题中的可行解。最后，通过数值实验证明了该方法的有效性和有效性。我们提出了一种新颖的方法，用其依赖于单工位的替代物替代依赖于两工位的对偶变量。还进行了分支和降价和割价的程序来获得相应的整数解，其中选择有效不等式的特定族来缩小受限主问题中的可行解。最后，通过数值实验证明了该方法的有效性和有效性。