scholarly journals An optimization model of EMU circulation problem for high-speed railway

2017 ◽  
Author(s):  
Wenjun Li ◽  
Lei Nie
Keyword(s):  
Optimization Model ◽  
High Speed ◽  
High Speed Railway ◽  
Circulation Problem

scholarly journals A Fuzzy Optimization Model for High-Speed Railway Timetable Rescheduling

2012 ◽  
Vol 2012 ◽  
pp. 1-22 ◽  
Author(s):  
Li Wang ◽  
Yong Qin ◽  
Jie Xu ◽  
Limin Jia
Keyword(s):  
Optimization Model ◽  
High Speed ◽  
Fuzzy Optimization ◽  
Soft Constraints ◽  
Accurate Approximation ◽  
Total Delay ◽  
High Speed Rail ◽  
High Speed Railway ◽  
Tolerance Approach ◽  
Rail Line

A fuzzy optimization model based on improved symmetric tolerance approach is introduced, which allows for rescheduling high-speed railway timetable under unexpected interferences. The model nests different parameters of the soft constraints with uncertainty margin to describe their importance to the optimization purpose and treats the objective in the same manner. Thus a new optimal instrument is expected to achieve a new timetable subject to little slack of constraints. The section between Nanjing and Shanghai, which is the busiest, of Beijing-Shanghai high-speed rail line in China is used as the simulated measurement. The fuzzy optimization model provides an accurate approximation on train running time and headway time, and hence the results suggest that the number of seriously impacted trains and total delay time can be reduced significantly subject to little cost and risk.

Application of Particle Swarm Algorithm in Train-Set Circulation Problem of China

2012 ◽  
Vol 253-255 ◽  
pp. 1235-1240
Author(s):  
Hua Li ◽  
Bao Ming Han ◽  
Fang Lu ◽  
Xiao Juan Li
Keyword(s):  
High Speed ◽  
Particle Swarm Optimization Algorithm ◽  
Programming Model ◽  
Real Life ◽  
Particle Swarm ◽  
Particle Swarm Algorithm ◽  
High Speed Railway ◽  
Railway Line ◽  
Circulation Problem

Train-set circulation problem is an important issue in operations of high-speed passenger trains in the world. On the basis of characteristics of the train-set circulation problem in China, an integer programming model is presented without considering distinct train-set types. With redefinitions of some basic mathematical objects and operations, an improved particle swarm optimization algorithm is proposed to solve the model. The algorithm is applied in a real-life case study based on the timetable of the Wuhan-Guangzhou High-speed Railway Line. The results show that the proposed algorithm is effective to find the optimized train-set circulation plan.

A two-layer optimization model for high-speed railway line planning

2011 ◽  
Vol 12 (12) ◽  
pp. 902-912 ◽  
Author(s):  
Li Wang ◽  
Li-min Jia ◽  
Yong Qin ◽  
Jie Xu ◽  
Wen-ting Mo
Keyword(s):  
Optimization Model ◽  
High Speed ◽  
Line Planning ◽  
High Speed Railway ◽  
Railway Line

scholarly journals Optimal Differential Pricing for Intercity High-Speed Railway Services with Time-Dependent Demand and Passenger Choice Behaviors under Capacity Constraints

2021 ◽  
Vol 2021 ◽  
pp. 1-13
Author(s):  
Huanyin Su ◽  
Shuting Peng ◽  
Lianbo Deng ◽  
Weixiang Xu ◽  
Qiongfang Zeng
Keyword(s):  
Optimization Model ◽  
High Speed ◽  
Simulated Annealing Algorithm ◽  
Solution Space ◽  
Capacity Constraints ◽  
Time Dependent ◽  
High Speed Railway ◽  
Distribution Features ◽  
Differential Pricing ◽  
Dependent Demand

Differential pricing of trains with different departure times caters to the taste heterogeneity of the time-dependent (departure time) demand and then improves the ticket revenue of railway enterprises. This paper studies optimal differential pricing for intercity high-speed railway services. The distribution features of the passenger demand regarding departure times are analyzed, and the time-dependent demand is formulated; a passenger assignment method considering departure periods and capacity constraints is constructed to evaluate the prices by simulating the ticket-booking process. Based on these, an optimization model is constructed with the aim of maximizing the ticket revenue and the decision variables for pricing train legs. A modified direct search simulated annealing algorithm is designed to solve the optimization model, and three random generation methods of new solutions are developed to search the solution space efficiently. Experimental analysis containing dozens of trains is performed on Wuhan-Shenzhen high-speed railway in China, and price solutions with different elastic demand coefficients ( ϕ ) are compared. The following results are found: (i) the optimization algorithm converges stably and efficiently and (ii) differentiation is shown in the price solutions, and the optimized ticket revenue is influenced greatly by ϕ , increasing by 7%–21%.

scholarly journals Optimization Problem of Pricing and Seat Allocation Based on Bilevel Multifollower Programming in High-Speed Railway

2021 ◽  
Vol 2021 ◽  
pp. 1-15
Author(s):  
Lianbo Deng ◽  
Jing Xu ◽  
Ningxin Zeng ◽  
Xinlei Hu
Keyword(s):  
Optimization Model ◽  
Dynamic Pricing ◽  
High Speed ◽  
Large Scale ◽  
Solution Method ◽  
Programming Model ◽  
Divide And Conquer ◽  
Small Scale ◽  
High Speed Railway ◽  
Seat Allocation

This paper studies the multistage pricing and seat allocation problems for multiple train services in a high-speed railway (HSR) with multiple origins and destinations (ODs). Taking the maximum total revenue of all trains as the objective function, a joint optimization model of multistage pricing and seat allocation is established. The actual operation constraints, including train seat capacity constraints, price time constraints in each period, and price space constraints among products, are fully considered. We reformulate the optimization model as a bilevel multifollower programming model in which the upper-level model solves the seat allocation problem for all trains serving multiple ODs in the whole booking horizon and the lower optimizes the pricing decisions for each train serving each OD in different decision periods. The upper and lower are a large-scale static seat allocation programming and many small-scale multistage dynamic pricing programming which can be solved independently, respectively. The solving difficulty can be significantly reduced by decomposing. Then, we design an effective solution method based on divide-and-conquer strategy. A real instance of the China’s Wuhan-Guangzhou high-speed railway is employed to validate the advantages of the proposed model and the solution method.

scholarly journals Sensor Networks Hierarchical Optimization Model for Security Monitoring in High-Speed Railway Transport Hub

2015 ◽  
Vol 2015 ◽  
pp. 1-9 ◽  
Author(s):  
Zhengyu Xie ◽  
Yong Qin
Keyword(s):  
Sensor Networks ◽  
Optimization Model ◽  
High Speed ◽  
Optimization Problem ◽  
Optimization Method ◽  
Hierarchical Optimization ◽  
Railway Transport ◽  
High Speed Railway ◽  
Security Monitoring

We consider the sensor networks hierarchical optimization problem in high-speed railway transport hub (HRTH). The sensor networks are optimized from three hierarchies which are key area sensors optimization, passenger line sensors optimization, and whole area sensors optimization. Case study on a specific HRTH in China showed that the hierarchical optimization method is effective to optimize the sensor networks for security monitoring in HRTH.

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