Joint optimization of energy conservation and transfer passenger service quality in rail transit system

Chao Wen, Wenxin Li, Qiang Ma, Guanming Wang and Baoquan Tao

International Journal of Rail Transportation, 2024, vol. 12, issue 5, 875-908

Abstract: The complex electricity transmission process and transfer passenger demand in the rail transit system make it challenging to formulate optimal timetables and train speed profiles to meet the needs of the system. This study optimizes train timetable to meet energy conservation and passenger service quality of cross-mode rail transit system during different operation periods. Firstly, based on the spatiotemporal travel data of transfer passengers, the train-time matrix is proposed to construct a bi-objective optimization model (BOOM) that incorporates the total energy consumption optimization model (TECOM) and total waiting time optimization model of transfer passenger (TWTOM). It can better combine the passenger transport scheme and the train energy-saving operation strategy, thus improving energy-saving performance and passenger transport efficiency and simplifying the difficulty of mathematical modelling of such BOOM. Then, a method for determining the appropriate weight coefficient ratio and the improved non-dominated sorting genetic algorithm II (NSGA-II) are applied to obtain the efficient Pareto front solutions. Taking the numerical experiments as test cases, the improved NSGA-II can get a efficient solution faster than the traditional NSGA-II. Finally, two numerical experiments using real-world data are conducted to verify the practicability of the optimization model and the effectiveness of improved NSGA-II. The optimization results can reduce energy consumption by up to 11.02% and passenger waiting time by 137,320 s, respectively. This study helps to improve the energy efficiency and passenger service quality of cross-mode rail transit systems, and also provides a reference for dispatchers to optimize train timetable.

Date: 2024
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DOI: 10.1080/23248378.2023.2256731

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