Energy-Efficient Optimization Method for Timetable Adjusting in Urban Rail Transit

Lianbo Deng (), Shiyu Tang, Ming Chen, Ying Zhang, Yuanyuan Tian and Qun Chen
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Lianbo Deng: Rail Data Research and Application Key Laboratory of Hunan Province, School of Traffic and Transportation Engineering, Central South University, Changsha 410075, China
Shiyu Tang: Rail Data Research and Application Key Laboratory of Hunan Province, School of Traffic and Transportation Engineering, Central South University, Changsha 410075, China
Ming Chen: Rail Data Research and Application Key Laboratory of Hunan Province, School of Traffic and Transportation Engineering, Central South University, Changsha 410075, China
Ying Zhang: Rail Data Research and Application Key Laboratory of Hunan Province, School of Traffic and Transportation Engineering, Central South University, Changsha 410075, China
Yuanyuan Tian: Guangzhou Metro Group Co., Ltd., Guangzhou 510030, China
Qun Chen: Rail Data Research and Application Key Laboratory of Hunan Province, School of Traffic and Transportation Engineering, Central South University, Changsha 410075, China

Mathematics, 2025, vol. 13, issue 13, 1-24

Abstract: For a given timetable in urban rail transit systems, this paper presents a practical energy efficiency optimization problem that carries out adjustments to the timetable, with the goal of energy saving. We propose two strategies to address this challenge, including adjusting the section running time by selecting a speed profile and improving the utilization of regenerative braking energy by adjusting the trains’ departure time. Constraints on the range of adjustment for energy-efficient time elements are constructed for maintaining the stability of elements of the given timetable. An energy efficiency optimization model is then established to minimize the total net energy consumption of the timetable, and a solution algorithm based on a genetic algorithm is proposed. We make small-scale adjustments to trains’ running trajectories to optimize the overlap time of braking and traction conditions among multiple trains. The case of the Guangzhou Metro Line 8 in China is presented to verify the effectiveness and practicality of our method. The results show that the consumption of traction energy is reduced by 0.95% and the use of regenerative braking energy is increased by 8.18%, with an improvement in energy efficiency of 6.78%. This method can achieve relatively significant energy efficiency results while ensuring the stable service quality of the train timetable and can provide support for an energy-efficient train timetable for urban rail transit operation enterprises.

Keywords: urban rail transit; energy-efficient train timetable; section running time adjustment; regenerative braking energy utilization; genetic algorithm (search for similar items in EconPapers)
JEL-codes: C (search for similar items in EconPapers)
Date: 2025
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