Zhang, Shuai (Beijing Jiaotong University), Wang, Yihui (Beijing Jiaotong University), Zhou, Yicheng (Beijing Jiaotong University)

A Two-Stage Ant Colony Algorithm for Rolling Stock Circulation Planning for Railway Lines

Scheduled for presentation during the Regular Session "Transport planning" (FrAT9), Friday, September 27, 2024, 11:50−12:10, Salon 17

2024 IEEE 27th International Conference on Intelligent Transportation Systems (ITSC), September 24- 27, 2024, Edmonton, Canada

This information is tentative and subject to change. Compiled on December 26, 2024

Abstract

This paper focuses on addressing rolling stock planning (RSP) for short-turning strategy operation in railway lines. Building upon predefined operation schemes, a modelling methodology is proposed from the perspective of train operations, substituting train service connection (TSC) for RSP. Through the adoption of an alternative set strategy, the problem is transformed into a multi-paths traveling salesman problem (MTSP), incorporating constraints such as depot capacity and safety connections. The objective is to minimize the total rolling stock planning time and resources, while employing a two-stage ant colony algorithm designed on heuristic information. Using the Beijing Subway Line 15 as a case study, the proposed algorithms are utilized to solve the RSP for trains operating on short-turning strategy routes. Results demonstrate that the proposed algorithms can rapidly and effectively solve the problem. Finally, the completed train operation diagram is presented, and the reliability of the solution is validated.