Demand-driven integrated train timetabling and rolling stock scheduling on urban rail transit line

Abstract

This paper aims to simultaneously optimise train timetabling and rolling stock scheduling in a bidirectional urban rail transit line. A novel variable train composition strategy is adopted to respond to time-dependent passenger demand by allowing modular train units to split and couple with each other at depots. We mathematically model this problem in an arrival time revision framework, simplifying the problem structure and rendering the model solved by a commercial solver. In particular, the proposed model considers two realistic first-in-first-out rules to capture passenger transportation accurately in the oversaturated urban rail transit system. The efficiency of the proposed strategy and model is validated on an illustrative example and a real-world instance in the Yizhuang Line of Beijing Subway. Results show that adopting the variable train composition strategy can save 63.6% and 44.6% of total passenger waiting time compared to the current fixed train composition strategy with eight and six units.

KEYWORDS:

• Urban rail transit
• variable train compositions
• timetabling
• rolling stock scheduling
• oversaturated passenger demand

Disclosure statement

No potential conflict of interest was reported by the author(s).

Additional information

Funding

This study was supported by the National Natural Science Foundation of China (grant numbers 72001020, 72074215, and 52002017), Beijing Natural Science Foundation (grant number L201016), and Joint Funds of the National Natural Science Foundation of China (grant number U2034208).