<b>Rolling Stock Scheduling Algorithm for Temporary Timetable After Natural Disaster</b>

This paper focuses on rolling stock scheduling after a large-scale natural disaster. In general, a temporary timetable is generated when sections of a line are partially disrupted by damage caused by the natural disaster. The next step is to generate a rolling stock schedule that is as close as possible to the original schedule at the time of timetable revision. We propose a two-phase rolling stock scheduling algorithm based on a mathematical programming method to cope with the temporary timetable. In addition, we confirm that the proposed algorithm can produce a practical rolling stock schedule in terms of evaluation criteria and computational time.

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Publication Details

Journal
Quarterly Report of RTRI
Published
2024-08-01
DOI
https://doi.org/10.2219/rtriqr.65.3_182
Citations
1
Primary Topic
Advanced Manufacturing and Logistics Optimization
Type
article
Field-Weighted Citation Impact
0.35
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article

Rolling Stock Scheduling Algorithm for Temporary Timetable After Natural Disaster

Satoshi Kato, Jun Imaizumi, Taichi Nakahigashi, Tatsuya Kokubo
1 citations
Quarterly Report of RTRI
Advanced Manufacturing and Logistics Optimization
0.35
article

Rolling Stock Scheduling Algorithm for Temporary Timetable After Natural Disaster

Satoshi Kato, Jun Imaizumi, Taichi Nakahigashi, Tatsuya Kokubo
article en
1 citations

Abstract

This paper focuses on rolling stock scheduling after a large-scale natural disaster. In general, a temporary timetable is generated when sections of a line are partially disrupted by damage caused by the natural disaster. The next step is to generate a rolling stock schedule that is as close as possible to the original schedule at the time of timetable revision. We propose a two-phase rolling stock scheduling algorithm based on a mathematical programming method to cope with the temporary timetable. In addition, we confirm that the proposed algorithm can produce a practical rolling stock schedule in terms of evaluation criteria and computational time.

Quarterly Report of RTRIVol. 65(3)
Toyo University (JP), Systems Technology (United States) (US)
Climate action
Openalex Percentile: Top 37%
Advanced Manufacturing and Logistics Optimization
0.35
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