Abstract
A time-space network based optimization method is designed for high-speed rail train timetabling problem to improve the service level of the high-speed rail. The general time-space path cost is presented which considers both the train travel time and the high-speed rail operation requirements: (1) service frequency requirement; (2) stopping plan adjustment; and (3) priority of train types. Train timetabling problem based on time-space path aims to minimize the total general time-space path cost of all trains. An improved branch-and-price algorithm is applied to solve the large scale integer programming problem. When dealing with the algorithm, a rapid branching and node selection for branch-and-price tree and a heuristic train time-space path generation for column generation are adopted to speed up the algorithm computation time. The computational results of a set of experiments on China’s high-speed rail system are presented with the discussions about the model validation, the effectiveness of the general time-space path cost, and the improved branch-and-price algorithm.
Highlights
The train timetabling problem (TTP) plays a critical role in the organization and operation of the railway system
TTP for the high-speed rail (HSR), which is different from conventional lines on operational requirements, brings a tremendous challenge for the operation company
TTP schedules the movement of trains on tracks in the railway system, and our research focuses on the offline timetable optimization problem
Summary
The train timetabling problem (TTP) plays a critical role in the organization and operation of the railway system. As the off-line timetabling problem is less sensitive to the time requirement, integer programming based formulations are a more popular approach for nonperiodic train timetabling These approaches usually adopted the time-space network or the likely network to describe the trains’ movement on the tracks, and designed an exact algorithm to obtain a more optimal solution. Caprara et al proposed a linear integer programming model based on a graph theoretic representation of the TTP, considering the track capacity and operational constraints Their model aimed to maximize the total train profit and the profit determined by the (nonnegative) difference between the running times in the actual and ideal timetables. Note that minimizing the total train travel time and maximizing the total train profits are the commonly used objective functions in the previous train timetabling researches It cannot handle the HSR requirements like the service frequency in different hours, stopping plan adjustment, and train priority.
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