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A Formulation of MIP Train Rescheduling at Terminals in Bidirectional Double-Track Lines with a Moving Block and ATO

Authors Kosuke Kawazoe, Takuto Yamauchi, Kenji Tei



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Author Details

Kosuke Kawazoe
  • Faculty of Science and Engineering, Waseda University, Shinjuku, Tokyo, Japan
Takuto Yamauchi
  • Faculty of Science and Engineering, Waseda University, Shinjuku, Tokyo, Japan
Kenji Tei
  • Faculty of Science and Engineering, Waseda University, Shinjuku, Tokyo, Japan

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Kosuke Kawazoe, Takuto Yamauchi, and Kenji Tei. A Formulation of MIP Train Rescheduling at Terminals in Bidirectional Double-Track Lines with a Moving Block and ATO. In 22nd Symposium on Algorithmic Approaches for Transportation Modelling, Optimization, and Systems (ATMOS 2022). Open Access Series in Informatics (OASIcs), Volume 106, pp. 10:1-10:18, Schloss Dagstuhl - Leibniz-Zentrum für Informatik (2022)
https://doi.org/10.4230/OASIcs.ATMOS.2022.10

Abstract

When delays in trains occur, train schedules are rescheduled to reduce the impact. Despite many existing studies of automated train rescheduling, this study focuses on automated rescheduling considering a moving block and Automatic Train Operation (ATO). This study enables such automated rescheduling by formalizing this problem as a mixed integer programming (MIP) model. In previous work, the formulation was achieved for unidirectional single-track railway lines. In this paper, we aim to achieve the formulation for bidirectional double-track lines. Specifically, we propose a formulation of constraints about trains’ running terminal stations. To evaluate our automated rescheduling approach, we implemented an MIP model consisting of a combination of the new constraints with the previous MIP model. We demonstrated the feasibility of our approach by applying it to a bidirectional double-track line with eight delay scenarios. We also evaluate the delay reduction and computation overhead of our approach by comparing it with a baseline with these eight scenarios. The results show that the total delay of all trains from our approach reduced from 20% to 30% than one from the baseline. On the other hand, the computation time increased from less than 1 second to a minimum of about 20 seconds and a maximum of about 1600 seconds.

Subject Classification

ACM Subject Classification
  • Applied computing → Transportation
Keywords
  • Train rescheduling
  • Mixed integer programming
  • ATO
  • Moving block

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