A Line Planning Approach for High-speed Railway Network with Time-varying Demand

2021 ◽  
pp. 107547
Author(s):  
Shuo Zhao ◽  
Runfa Wu ◽  
Feng Shi
2019 ◽  
Vol 2019 ◽  
pp. 1-18
Author(s):  
Huanyin Su ◽  
Wencong Tao ◽  
Xinlei Hu

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.


2020 ◽  
Vol 2020 ◽  
pp. 1-18
Author(s):  
Di Liu ◽  
Javier Durán Micco ◽  
Gongyuan Lu ◽  
Qiyuan Peng ◽  
Jia Ning ◽  
...  

In this paper, a matheuristic iterative approach (MHIA) is proposed to solve the line planning problem, also called network design problem, and frequency setting on the Chinese high-speed railway network. Our optimization model integrates the cost-oriented and passenger-oriented objectives into a profit-oriented objective. Therefore, the passenger travel time is incorporated in the ticket price using a travel time value. As a result, transfers and detours will result in lower ticket prices and thus lower revenues for the operator. When evaluating the performance of a given line plan, the way in which passengers will travel through the network needs to be modelled. This passenger assignment is typically a time-consuming calculation. The proposed line planning approach iteratively improves the line plan using easy-to-determine indicators. During the process, a mixed integer linear programming model addresses the passenger assignment and optimizes the frequency setting in order to maximise the operational profit. Extensive computational experiments are executed to show the effectiveness of the proposed approach to deal with the real-world railway network line planning problem. Through extensive computational experiments on the small example network and real-world-based instances, the results show that the proposed model can improve the profits by 22.4% on average comparing to their initial solutions. When comparing to an alternative iterative approach, our proposed method has advantage of obtaining high quality of solutions by improving the profit 10.8% on average. For small, medium, and large size networks, the obtained results are close to the optimal solutions, when available.


2013 ◽  
Vol 30 (04) ◽  
pp. 1350006 ◽  
Author(s):  
BUM HWAN PARK ◽  
YONG-IL SEO ◽  
SUNG-PIL HONG ◽  
HAG-LAE RHO

This study investigated railway line planning optimization models that determine the frequency of trains on each line to satisfy passenger origin–destination demands while minimizing related costs. Most line planning models assume that all trains on the same route run with the same halting pattern. However, to minimize passenger travel time and to provide a train service with faster travel times to as many stations as possible, we must consider various halting patterns; these patterns can be provided in advance or are required to be formulated. Our study addresses two line planning problems that consider halting patterns, describes the computational complexities of each problem, and presents the column generation approach for one model. We also present experimental results obtained for the Korean high-speed railway network.


Energies ◽  
2021 ◽  
Vol 14 (15) ◽  
pp. 4648
Author(s):  
Zhipeng Tang ◽  
Ziao Mei ◽  
Jialing Zou

The carbon intensity of China’s resource-based cities (RBCs) is much higher than the national average due to their relatively intensive mode of development. Low carbon transformation of RBCs is an important way to achieve the goal of reaching the carbon emissions peak in 2030. Based on the panel data from 116 RBCs in China from 2003 to 2018, this study takes the opening of high-speed railway (HSR) lines as a quasi-experiment, using a time-varying difference-in-difference (DID) model to empirically evaluate the impact of an HSR line on reducing the carbon intensity of RBCs. The results show that the opening of an HSR line can reduce the carbon intensity of RBCs, and this was still true after considering the possibility of problems with endogenous selection bias and after applying the relevant robustness tests. The opening of an HSR line is found to have a significant reducing effect on the carbon intensity of different types of RBC, and the decline in the carbon intensity of coal-based cities is found to be the greatest. Promoting migration of RBCs with HSR lines is found to be an effective intermediary way of reducing their carbon intensity.


ICTE 2015 ◽  
2015 ◽  
Author(s):  
Qiangfeng Zhang ◽  
Haifeng Yan ◽  
Shaoquan Ni ◽  
Wenting Zhang

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