Metro train delay-recovery strategy considering passenger waiting time and energy consumption: a real-world case study

Wenxin Li, Qingwei Zhong, Qiyuan Peng, Jing Liu and Chao Ma

International Journal of Rail Transportation, 2024, vol. 12, issue 1, 76-101

Abstract: Based on actual delay-recovery strategies (ADRS) on site only considers reducing the delays and ignores the operation cost of the enterprise. This study proposes optimized delay-recovery strategies (ODRS) to reduce the impact of delay on passengers and increase energy efficiency simultaneously. A bi-objective optimization model is used to deal with different initial delay scenarios and minimize the additional waiting time of passengers (AWTP) and total energy consumption (TEC). In the solving process, the non-dominated sorting genetic algorithm-II (NSGA-II) is used to solve the models, which can get the effective Pareto frontier solutions. Finally, Chengdu Metro is taken as the numerical experiments to verify the performance of the models. The results show that the ODRS can effectively reduce the AWTP and TEC than the ADRS. Furthermore, with the increase of initial delay time, the optimization effect of ODRS will be more obvious.

Date: 2024
References: Add references at CitEc
Citations:

Downloads: (external link)
http://hdl.handle.net/10.1080/23248378.2022.2143918 (text/html)
Access to full text is restricted to subscribers.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:taf:tjrtxx:v:12:y:2024:i:1:p:76-101

Ordering information: This journal article can be ordered from
http://www.tandfonline.com/pricing/journal/tjrt20

DOI: 10.1080/23248378.2022.2143918

Access Statistics for this article

International Journal of Rail Transportation is currently edited by Wanming Zhai and Kelvin C. P. Wang

More articles in International Journal of Rail Transportation from Taylor & Francis Journals
Bibliographic data for series maintained by Chris Longhurst ().