Journal
TRANSPORTATION RESEARCH PART C-EMERGING TECHNOLOGIES
Volume 63, Issue -, Pages 126-146Publisher
PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.trc.2015.12.007
Keywords
Train scheduling; Railway service plan; Train stopping pattern; Column generation
Categories
Funding
- Fundamental Research Funds for the Central Universities [2014JBZ008]
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High-speed railway (HSR) systems have been developing rapidly in China and various other countries throughout the past decade; as a result, the question of how to efficiently operate such large-scale systems is posing a new challenge to the railway industry. A high-quality train timetable should take full advantage of the system's capacity to meet transportation demands. This paper presents a mathematical model for optimizing a train timetable for an HSR system. We propose an innovative methodology using a column-generation-based heuristic algorithm to simultaneously account for both passenger service demands and train scheduling. First, we transform a mathematical model into a simple linear programming problem using a Lagrangian relaxation method. Second, we search for the optimal solution by updating the restricted master problem (RMP) and the sub-problems in an iterative process using the column-generation-based algorithm. Finally, we consider the Beijing-Shanghai HSR line as a real-world application of the methodology; the results show that the optimization model and algorithm can improve the defined profit function by approximately 30% and increase the line capacity by approximately 27%. This methodology has the potential to improve the service level and capacity of HSR lines with no additional high-cost capital investment (e.g., the addition of new tracks, bridges and tunnels on the mainline and/or at stations). (C) 2015 Elsevier Ltd. All rights reserved.
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