Optimization of High-Speed Railway Line Planning With Passenger and Freight Transport Coordination

被引:4
|
作者
Li, Shiqi [1 ,2 ]
Lang, Maoxiang [1 ,2 ]
Li, Siyu [1 ,2 ]
Chen, Xinghan [1 ,2 ]
Yu, Xueqiao [3 ]
Geng, Yixuan [1 ]
机构
[1] Beijing Jiaotong Univ, Sch Traff & Transportat, Beijing 100044, Peoples R China
[2] Beijing Jiaotong Univ, Key Lab Transport Ind Big Data Applicat Technol C, Beijing 100044, Peoples R China
[3] China Acad Railway Sci Corp Ltd, Transportat & Econ Res Inst, Beijing 100081, Peoples R China
基金
中国国家自然科学基金;
关键词
High-speed rail transportation; Freight handling; Rail transportation; Optimization; Resource management; Genetic algorithms; Heuristic algorithms; Generation algorithm; genetic algorithm; high-speed railway; passenger and freight transport coordination; the line planning; train candidate set; STOP PLAN; ALGORITHM; NETWORK; UNCERTAINTY; DESIGN; MODEL;
D O I
10.1109/ACCESS.2022.3210578
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
This paper studies the line planning optimization problem based on the coordinate mode of high-speed railway (HSR) passenger trains and freight trains. The multi objective nonlinear mixed integer programming model of HSR passenger train and freight train line planning with passengers and freight is designed on the basis of comprehensive consideration of passenger and freight transport demand. Then, in order to simultaneously determine the types, origin and destination stations, operation sections, stop schemes, operation frequencies, and demand allocation of HSR passenger trains and freight trains, the model is solved iteratively using a hybrid heuristic algorithm combining a column generation algorithm and a genetic algorithm. Finally, a numerical experiment based on the operation data of China's Dalian-Harbin HSR line is implemented to verify the effectiveness of the proposed model and algorithm, and the solution performance of the CPLEX solver and the hybrid heuristic algorithm is compared. The results show that both the CPLEX solver and the hybrid heuristic algorithm can obtain the global optimal solution set. With the expansion of the scale of the problem, the solution quality and convergence efficiency of the hybrid heuristic algorithm have significantly improved, and it can solve large-scale problems and obtain satisfactory solutions within a shorter time.
引用
收藏
页码:110217 / 110247
页数:31
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