Integrated optimization of train timetable, rolling stock assignment and short-turning strategy for a metro line

Jiawei Yuan, Yuan Gao, Shukai Li, Pei Liu and Lixing Yang

European Journal of Operational Research, 2022, vol. 301, issue 3, 855-874

Abstract: In many large cities, metro operations during peak hours are characterized by an overcrowded and unevenly-distributed passenger demand. This paper introduces a new integrated optimization model for the train timetable, rolling stock assignment, and short-turning strategy on a bidirectional metro line. The purpose is to increase the number of services in higher-passenger-demand segments using limited trains, thereby reducing passengers’ total waiting time on platforms. In particular, we simultaneously consider the multiple service operation zones, the train capacity, the turnaround operations, and the number of available trains. To obtain high-quality solutions, we develop a hybrid algorithm that combines a genetic algorithm with a general-purpose solver. Two sets of case studies, with a simplified metro line and the Beijing metro line 6, are implemented to verify the effectiveness and efficiency of the proposed hybrid algorithm.

Keywords: Transportation; Dynamic passenger demand; Train timetable; Rolling stock assignment; Short-turning strategy (search for similar items in EconPapers)
Date: 2022
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Citations: View citations in EconPapers (12)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:ejores:v:301:y:2022:i:3:p:855-874

DOI: 10.1016/j.ejor.2021.11.019

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