Integrated optimization of train scheduling and maintenance planning on high-speed railway corridors

Omega ◽  
2019 ◽  
Vol 87 ◽  
pp. 86-104 ◽  
Author(s):  
Chuntian Zhang ◽  
Yuan Gao ◽  
Lixing Yang ◽  
Uday Kumar ◽  
Ziyou Gao
Author(s):  
Dian Wang ◽  
Shuguang Zhan ◽  
Qiyuan Peng ◽  
Wentao Zhou

Overnight high-speed trains are very popular and convenient for passengers in countries with a large territory like China. However, the overnight high-speed train operation inevitably conflicts with the regular evening maintenance. We focus on both overnight high-speed train scheduling and maintenance planning to eliminate the conflict. Because some of the daytime high-speed trains that run early in the morning or late in the evening also interact with overnight high-speed trains and maintenance, we also allow them to be to slightly rescheduled to improve both the quality of the overnight train timetable and the maintenance plan. Our integrated optimization problem is formulated as a mixed integer linear programming model, which can be solved efficiently by the commercial solver CPLEX. Finally, we validate our model on a large real-world case constructed based on the Beijing–Guangzhou high-speed railway line in China.


2014 ◽  
Vol 667 ◽  
pp. 81-84
Author(s):  
Mo Gao ◽  
Lei Shan Zhou ◽  
Yu Zhou

This paper analyzes the command mode of high speed railway (HSR) train dispatching based on control system CTCS-3.In order to draw up the optimum allocation plan of time and space resources for HSR, a basic concept of management and control integration was proposed in this paper, including the HSR train coordination scheduling, the structure of hardware and software, and the theory of train operation. Furthermore, the basic framework of train operation dispatching command system based on the integration of management and control was designed to optimize the HSR operation and organization.


2020 ◽  
Vol 12 (13) ◽  
pp. 5447
Author(s):  
Dezhi Zhang ◽  
Shuxin Yang ◽  
Shuangyan Li ◽  
Jiajun Fan ◽  
Bin Ji

Sustainable distribution network design for the maintenance components of electric multiple units (EMUs) is critical to reduce the problem of unreasonable resource allocation and capital occupation of high-speed railway (HSR) operations. Motivated by the above analysis, this study investigates the integrated optimization of the location and inventory of EMU maintenance component distributions. Aiming to improve the sustainable operation for high-speed railway, we proposed a corresponding nonlinear mixed-integer programming model to determine the location of the distribution center (DC) for EMU maintenance component delivery, inventory control strategy, and corresponding service level. The above optimization model is solved by an adaptive improved genetic algorithm. The proposed model and algorithm are applied to a real-world case study on China’s EMU maintenance components. The findings show that a higher service level is not better to achieve the lower total cost in the maintenance component distribution network. The ratios of transportation modes are significant to balance the service level and total cost of the EMU distribution network. Furthermore, the unit out-of-stock cost and the service level both show great impacts on the total costs of the EMU distribution system. Finally, there exists an optimal ratio of different transport modes, which ensures the least total cost of the EMU distribution system.


2018 ◽  
Vol 2018 ◽  
pp. 1-16 ◽  
Author(s):  
Chuntian Zhang ◽  
Yuan Gao ◽  
Wenjie Li ◽  
Lixing Yang ◽  
Ziyou Gao

Simultaneously considering train scheduling problem and maintenance planning problem with uncertain travel time, we propose a two-stage integrated optimization model for the sunset-departure and sunrise-arrival trains (SDSA-trains). Specifically, in the first stage, we obtain an optimal solution of the SDSA-trains under each scenario, which leads to the minimum total travel time. In the second stage, a robust SDSA-train schedule is generated based on the optimal solutions of the first stage. The key is that we consider two operation modes to solve the conflict between the SDSA-trains and the maintenances. Some state variables are used to deal with train operation mode selection. Furthermore, some linearization techniques are used to formulate a mixed-integer linear programming (MILP) model. Finally, numerical experiments are implemented to prove the effectiveness of the proposed model and optimization method.


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