Automatic Generation Method for Crew Scheduling After a Large-scale Natural Disaster

When railway line sections are partially disrupted due to damage from large-scale natural disasters, it is necessary to prepare crew schedule plans for temporary timetables. In such a case, a crew schedule plan ensures that duties once assigned to crew members are not changed. As this task is time-consuming for schedule planners, an automatic crew scheduling method for supporting planners is desired. In this paper, we focus on crew scheduling following a large-scale natural disaster. The proposed algorithm is based on mathematical programming and column generation. In addition, we show the results of computational experiments based on a real disaster case, which indicate that the proposed algorithm can generate an efficient schedule plan in a short time.

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Publication Details

Journal
IEEJ Transactions on Industry Applications
Published
2025-05-01
DOI
https://doi.org/10.1541/ieejias.145.343
Primary Topic
Scheduling and Timetabling Solutions
Type
article
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article

Automatic Generation Method for Crew Scheduling After a Large-scale Natural Disaster

Satoshi Kato, Jun Imaizumi, Taichi Nakahigashi
IEEJ Transactions on Industry Applications
Scheduling and Timetabling Solutions
article

Automatic Generation Method for Crew Scheduling After a Large-scale Natural Disaster

Satoshi Kato, Jun Imaizumi, Taichi Nakahigashi
article en

Abstract

When railway line sections are partially disrupted due to damage from large-scale natural disasters, it is necessary to prepare crew schedule plans for temporary timetables. In such a case, a crew schedule plan ensures that duties once assigned to crew members are not changed. As this task is time-consuming for schedule planners, an automatic crew scheduling method for supporting planners is desired. In this paper, we focus on crew scheduling following a large-scale natural disaster. The proposed algorithm is based on mathematical programming and column generation. In addition, we show the results of computational experiments based on a real disaster case, which indicate that the proposed algorithm can generate an efficient schedule plan in a short time.

IEEJ Transactions on Industry ApplicationsVol. 145(5)
Railway Technical Research Institute (JP), Toyo University (JP)
Climate action
Openalex Percentile: Top 90%
Scheduling and Timetabling Solutions
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Automatic Generation Method for Crew Scheduling After a Large-scale Natural Disaster — Satoshi Kato, Jun Imaizumi, et al. · IEEJ Transactions on Industry Applications (2025) | TGRS Research Map | TGRS