A Multiobjective Integer Linear Programming Model for the Cross-Track Line Planning Problem in the Chinese High-Speed Railway Network

Han, Peiwen; Nie, Lei; Fu, Huiling; Gong, Yantao; Wang, Gang

doi:10.3390/sym11050670

Cited by 8 publications

(5 citation statements)

References 27 publications

(29 reference statements)

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“…Fu et al [4] introduced a two-stage approach for train stop scheduling with a goal of efficiently organizing passenger traffic. Han et al [5] developed a multi-objective integer programming model to produce a balanced cross-track line plan by combining individual-track high-speed trains into cross-track high-speed trains.…”

Section: Literature Review 21 Railway Train Operation Planmentioning

confidence: 99%

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A Multi-Objective Optimization Model for the Intercity Railway Train Operation Plan: The Case of Beijing-Xiong’an ICR

et al. 2022

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For intercity railway transportation enterprises, a reasonable intercity train operation plan is not only the foundation of the intercity railway operation organization, but also the key to the sustainable development of the intercity railway (ICR). In this paper, taking into account the economic benefits of railway transportation enterprises and the social benefits of passenger travel, an optimization model is established with the intercity railway train operation plan as the research object. The model aims to minimize the operating cost of railway transportation enterprises and minimize the travel time of passengers, and considers constraints such as passenger seat utilization, passenger flow, train frequency, and stops. It is a multi-objective optimization model that accumulates two objectives by introducing the passenger time value coefficient. According to the characteristics of the model, a genetic algorithm is designed to solve the model. Taking the Beijing-Xiong’an Intercity Railway (BXICR) as an example, the “smart business card” of China’s high-speed railway, two scenarios of passenger time value are designed, and the optimized train operation plan is obtained according to the existing OD passenger flow data, which verifies the effectiveness of the model and algorithm. The results show that compared with the original train operation plan, the number of stops per train of the optimized train operation plan under the two passenger time value scenarios decreased by 8.8% and 14.9%, the operating cost of the enterprise decreased by 7.7% and 1.6%, the travel time of passengers decreased by 0.7% and 1.5%, respectively. Under the condition of meeting the demand of passenger flow, the optimized train operation plan can effectively reduce the operating cost of enterprises and save the travel time of passengers, which is conducive to the sustainable development of intercity railways.

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Section: Literature Review 21 Railway Train Operation Planmentioning

confidence: 99%

“…The time consumption of passengers due to the trains stopping at the intermediate station C 3 can be expressed as Equation (5).…”

Section: Decision Variables Definitionmentioning

confidence: 99%

A Multi-Objective Optimization Model for the Intercity Railway Train Operation Plan: The Case of Beijing-Xiong’an ICR

et al. 2022

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“…Hetrakul and Cirillo [27,28] first formulated latent class and mixed logit models by internet booking data to analyze railway passenger choice behavior, then proposed a joint optimization model for pricing and seat allocation with the assumption of deterministic demand. All studies of railway revenue management are based on prepared line planning [29], train diagrams [30], and timetables [31]. However, group reservations were not considered in the above literature.…”

Section: Literature Reviewmentioning

confidence: 99%

Joint Decision Model of Group Ticket Booking Limits and Individual Passenger Dynamic Pricing for the High-Speed Railway

Yan

Zhang

et al. 2019

Symmetry

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Rail operators in many countries discount group tickets to improve revenue by increasing price-driven demand. For individual passengers, dynamic pricing is beneficial for maximizing revenue based on the price discrimination principle. Usually, group fares are cheaper than individual fares. If too many group tickets are sold, there will not be enough tickets available to meet high-priced individual demand; by contrast, if not enough group tickets are sold and there is insufficient individual demand, the unsold seats will not have value once the train departs. Therefore, for railway operators, it is worth looking for a balance between group discounts and dynamic pricing to maximize benefits. Essentially, rail operators need to find the symmetry point of the expected revenue between accepting group bookings and reserving tickets for individuals when making decisions. In this study, we formulated a joint decision model of group ticket booking control and dynamic pricing and investigated the effect of the joint decision. The results of numerical experiments showed that incorporating group discounts into dynamic pricing can improve expected revenue when passenger demand is weak, and compared to setting fixed quantities for group tickets, dynamically controlling the limit of group bookings can effectively increase expected revenue. Further analysis of the impacts of time, number of tickets sold, and group demand was helpful to implement the proposed joint policy.

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“…The increasing passenger travel demands have brought great pressure to the whole public transit systems. The proper management and better performance of public transit systems are effective ways to solve this problem [1][2][3][4][5][6][7]. As a low-carbon and environment-friendly public transit mode, high-speed railway (HSR) has developed rapidly in recent years, and its high speed and high density have made it the first choice for more and more passengers traveling between cities.…”

Section: Introductionmentioning

confidence: 99%

Column Generation Accelerated Algorithm and Optimisation for a High-Speed Railway Train Timetabling Problem

2019

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With the rapid development of high-speed railway (HSR) systems, the increasing demand for passenger traffic has put forward higher requirements for HSR train timetabling problems (HSRTTPs). This paper establishes two mathematical optimisation models with different optimisation objectives for an HSRTTP and solves these models through a column generation-based algorithm. However, the column generation-based algorithm has the disadvantage of a slow convergence rate, thus we put forward corresponding acceleration strategies for five stages of the algorithm: preprocessing, restricted master problem, pricing problem, branch-and-bound and postprocessing from a symmetry point between the computation efficiency and the accuracy. The effectiveness of the acceleration strategies was validated by a case study of the Beijing–Shanghai HSR. The results show that the proposed optimal acceleration strategies can increase the computation efficiency of the algorithm by 11.8× on average while ensuring the accuracy.

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A Multiobjective Integer Linear Programming Model for the Cross-Track Line Planning Problem in the Chinese High-Speed Railway Network

Cited by 8 publications

References 27 publications

A Multi-Objective Optimization Model for the Intercity Railway Train Operation Plan: The Case of Beijing-Xiong’an ICR

A Multi-Objective Optimization Model for the Intercity Railway Train Operation Plan: The Case of Beijing-Xiong’an ICR

Joint Decision Model of Group Ticket Booking Limits and Individual Passenger Dynamic Pricing for the High-Speed Railway

Column Generation Accelerated Algorithm and Optimisation for a High-Speed Railway Train Timetabling Problem

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