Urban Rail Transit Rolling Stock Scheduling Optimization with Shared Depot

Jia Feng (), Guowei Li, Yuxin Shi, Zhengzhong Li and Shanshan Liu
Additional contact information
Jia Feng: Key Laboratory of Transport Industry of Big Data Application Technologies for Comprehensive Transport, Beijing Jiaotong University, Beijing 100044, China
Guowei Li: Key Laboratory of Transport Industry of Big Data Application Technologies for Comprehensive Transport, Beijing Jiaotong University, Beijing 100044, China
Yuxin Shi: Key Laboratory of Transport Industry of Big Data Application Technologies for Comprehensive Transport, Beijing Jiaotong University, Beijing 100044, China
Zhengzhong Li: Tianjin Transportation Research Institute, Tianjin 300074, China
Shanshan Liu: Yunnan Jingjian Rail Transit Investment and Construction Co., Ltd., Kunming 650500, China

Sustainability, 2022, vol. 14, issue 22, 1-16

Abstract: This paper presents a coordinated model to optimize the rolling stock scheduling of two urban rail transit lines with a shared train depot. The proposed integrated and extended integrated optimization problems are transformed into mixed integer linear programming (MILP) problems, which can be efficiently solved by an ant colony optimization algorithm. Numerical examples based on the Beijing Subway System are implemented to demonstrate the performance of the proposed models and solution approach.

Keywords: urban rail transit; rolling stock scheduling; network operation; shared train depot; MILP (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2022
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

Downloads: (external link)
https://www.mdpi.com/2071-1050/14/22/15075/pdf (application/pdf)
https://www.mdpi.com/2071-1050/14/22/15075/ (text/html)

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:gam:jsusta:v:14:y:2022:i:22:p:15075-:d:972487

Access Statistics for this article

Sustainability is currently edited by Ms. Alexandra Wu

More articles in Sustainability from MDPI
Bibliographic data for series maintained by MDPI Indexing Manager ().