scholarly journals A Line Planning Approach for High-Speed Rail Networks with Time-Dependent Demand and Capacity Constraints

2019 ◽  
Vol 2019 ◽  
pp. 1-18
Author(s):  
Huanyin Su ◽  
Wencong Tao ◽  
Xinlei Hu
Keyword(s):  
High Speed ◽  
Simulated Annealing Algorithm ◽  
Capacity Constraints ◽  
Time Dependent ◽  
High Speed Rail ◽  
Line Planning ◽  
Planning Approach ◽  
Upper Level ◽  
Varying Demand ◽  
Dependent Demand

In high-speed rail networks, trains are operated with high speeds and high frequencies, which can satisfy passenger demand with different expected departure times. Given time-dependent demand, this paper proposes a line planning approach with capacity constraints for high-speed rail networks. In this paper, a bilevel optimization model is formulated and the constraints include track section capacity per unit time, train seat capacity, and the gap between the number of starting trains and that of ending trains at a station. In the upper level, the objective is to minimize train operational cost and passenger travel cost, and the decision variables include the line of each train, carriage composition of each train, train stop patterns, train start times, and train arrival and departure times at stops in the line plan. In the lower level, a schedule-based passenger assignment method, which assigns time-varying demand on trains with seat capacity constraints by simulating the ticket-booking process, is used to evaluate the line plan obtained in the upper level. A simulated annealing algorithm is developed to solve the model in which some strategies are designed to search for neighborhood solutions, including reducing train carriages, deleting trains, adding trains, increasing train carriages, and adjusting train start times. Finally, an application to the Chinese high-speed rail network is presented. The numerical results show that (i) the average time deviations between the expected departure times and the actual boarding times of passengers are within 30 min, (ii) the unserved passengers are less than 200, and (iii) the average load factors of trains are about 70%. Hence, line plan solutions meet time-dependent demand well and satisfy the capacity constraints for high-speed rail networks.

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%.

A hierarchical line planning approach for a large-scale high speed rail network: The China case

2015 ◽  
Vol 75 ◽  
pp. 61-83 ◽  
Author(s):  
Huiling Fu ◽  
Lei Nie ◽  
Lingyun Meng ◽  
Benjamin R. Sperry ◽  
Zhenhuan He
Keyword(s):  
High Speed ◽  
Large Scale ◽  
High Speed Rail ◽  
Line Planning ◽  
Rail Network ◽  
Planning Approach

A fuzzy imperfect production and repair inventory model with time dependent demand, production and repair rates under inflationary conditions

2018 ◽  
Vol 52 (1) ◽  
pp. 217-239 ◽  
Author(s):  
Shalini Jain ◽  
Sunil Tiwari ◽  
Leopoldo Eduardo Cárdenas-Barrón ◽  
Ali Akbar Shaikh ◽  
Shiv Raj Singh
Keyword(s):  
Research Work ◽  
Repair Process ◽  
Inventory Model ◽  
Time Dependent ◽  
Imperfect Production ◽  
Imperfect Items ◽  
Demand Rate ◽  
The Impact ◽  
Varying Demand ◽  
Dependent Demand

This research work derives an integrated inventory model for imperfect production/remanufacturing process with time varying demand, production and repair rates under inflationary environment. This inventory model deals with the joint manufacturing and remanufacturing options. There is a collection process devoted to collect used items with the aim to remanufacture them. Both production and repair runs generate imperfect items. The repair process remanufactures used and imperfect items. Further, it is also considered that the remanufactured item that is classified as good has exactly same quality as that of new one. Demand rate is supposed as time dependent. The production rate is assumed to be demand dependent and therefore it is also time dependent. The repair rate is supposed to be a function of time. All system costs are contemplated in uncertain environment. Therefore, the costs are considered as fuzzy nature. Theoretical results are illustrated thru a numerical example. Finally, a sensitivity analysis is performed in order to know the impact of different parameters on the optimal policy.

scholarly journals Solving High-Speed Rail Planning with the Simulated Annealing Algorithm

2013 ◽  
Vol 139 (6) ◽  
pp. 635-642 ◽  
Author(s):  
Ana Laura Costa ◽  
Maria da Conceição Cunha ◽  
Paulo A. L. F. Coelho ◽  
Herbert H. Einstein
Keyword(s):  
Simulated Annealing ◽  
High Speed ◽  
Simulated Annealing Algorithm ◽  
High Speed Rail ◽  
Annealing Algorithm

Study on Optimization of Train Line Planning for High Speed Rail Corridor Based on Analyzing Importance of Nodes

2010 ◽  
Author(s):  
Yong-Tao Niu ◽  
Bao-Ming Han ◽  
Min Liu ◽  
Qing-Lan Zhu
Keyword(s):  
High Speed ◽  
Programming Model ◽  
Planning Problem ◽  
High Speed Rail ◽  
Line Planning ◽  
Evaluation Indexes ◽  
Railway Line ◽  
Passenger Flow ◽  
Multi Objective Programming ◽  
Railway Passenger Transport

In order to meet the demand of passengers for travelling and make their travelling more convenient, the railway operator must ascertain the operational train number, section, classes, stop stations and appropriate departure and arrival stations for passenger trains. The nodes of railway passenger transport are the generation and attraction points of passenger flow in the railway transport network. Starting from the analysis of the economic and social attributes as well as railway resource allocation of the Passenger Dedicated Railway Line (PDRL) covered nodes, this paper introduces the concept of the importance of nodes. On the basis of analytical hierarchy process (AHP), the paper studies the quantitative index of the nodes transport distribution capacity in the PDRL network and calculates the evaluation indexes of importance of those city nodes. Thus, in the light of the assessment results, the paper sets up the three-level hierarchy in the importance of city nodes covered by the PDRL. Based on that, the paper proposes that the first-level nodes serve as the departure and arrival stations, the second-level nodes adopt the fluid and alternate stop stations, and the tertiary-level nodes take the form of “all-stop” for low-class trains so as to build a multi-objective programming model for the PDRL train line planning. With the lingo 8.0 program, the train line planning optimizes the calculation of stop stations. This method has been applied in the PDRL train line planning of Wuhan-GuangZhou High-Speed Railway Line and proved to be effective in reducing the complexity of the train line planning problem according to different modes of passenger flow.

scholarly journals Estimation of Time-Varying Passenger Demand for High Speed Rail System

Complexity ◽  
2019 ◽  
Vol 2019 ◽  
pp. 1-24
Author(s):  
Tangjian Wei ◽  
Feng Shi ◽  
Guangming Xu
Keyword(s):  
High Speed ◽  
Case Analysis ◽  
Error Rates ◽  
Time Varying ◽  
High Speed Rail ◽  
Passenger Demand ◽  
The Times ◽  
Railway Operation ◽  
Varying Demand ◽  
Estimation Of Time

Passenger demand plays an important role in railway operation and organization, and this paper aims to estimate passenger time-varying demand by simulating the ticket-booking process for High Speed Rail (HSR) system. The ticket-booking process of each OD pair can be partition into discrete booking phases by the times when the tickets of any itinerary had sold out. The ticket booking volume of each itinerary is reversely assigned to its corresponding expected departure intervals to obtain the time-varying demand in each booking phase using the rooftop model, and the total time-varying demand are estimated by summing the time-varying demand distributions in all booking phases. Only with the data about the itinerary flow, the precedence relationship is introduced to constrain the ticket sold-out order of all itineraries for each OD pair. Based on the precedence relationships of itineraries, two typical situations are proposed, in which the Single Booking Phase Reverse Assignment (SBPRA) algorithm and the Multiple Booking Phases Reverse Assignment (MBPRA) algorithm are proposed to estimate the time-varying demand respectively. Case analysis on OD pair Beijing-Shanghai are presented, and the validity analysis demonstrates that the error rates of SBPRA algorithm and MBPRA algorithm are 8.64% and 6.37%, respectively.

scholarly journals An Integrated Model for Demand Forecasting and Train Stop Planning for High-Speed Rail

Symmetry ◽  
2019 ◽  
Vol 11 (5) ◽  
pp. 720 ◽  
Author(s):  
Guowei Jin ◽  
Shiwei He ◽  
Jiabin Li ◽  
Yubin Li ◽  
Xiaole Guo ◽  
...  
Keyword(s):  
High Speed ◽  
Travel Demand ◽  
Demand Forecasting ◽  
Planning Problem ◽  
High Speed Rail ◽  
Line Planning ◽  
Modal Choice ◽  
The Sustainable Development ◽  
Mode Share ◽  
The Impact

Studying the interaction between demand forecasting and train stop planning is important, as it ensures the sustainable development of high-speed rail (HSR). Forecasting the demand for high-speed rail (HSR), which refers to modal choice or modal split in this paper, is the first step in high-speed rail (HSR) planning. Given the travel demand and the number of train trips on each route, the train stop planning problem (TSPP) of line planning involves determining the stations at which each train trip stops, i.e., the stop-schedule of each train trip, so that the demand can be satisfied. To integrate and formulate the two problems, i.e., the modal choice problem (MCP) and train stop planning problem (TSPP), a nonlinear model is presented with the objective of maximizing the total demand captured by a high-speed rail system. To solve the model, a heuristic iterative algorithm is developed. To study the relationship between the demand and the service, the Beijing–Shanghai high-speed rail (HSR) corridor in China is selected. The empirical analysis indicates that combining modal choice and train stop planning should be considered for the sustainable design of high-speed rail (HSR) train services. Furthermore, the model simulates the impact of the number of stops on its mode share by reflecting changes in travelers’ behaviors according to HSR train stop planning, and it also provides a theoretical basis for the evaluation of the adaptability of the service network to travel demand.

Research on Prediction of High-Speed Rail Trains Delay Time

CICTP 2020 ◽  
2020 ◽  
Author(s):  
Jing Shi ◽  
Qiyuan Peng ◽  
Ling Liu
Keyword(s):  
Delay Time ◽  
High Speed ◽  
High Speed Rail
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