Demand-Driven Train Schedule Synchronization for High-Speed Rail Lines

Niu, Huimin; Tian, Xiaopeng; Zhou, Xuesong

doi:10.1109/tits.2015.2415513

Cited by 63 publications

(30 citation statements)

References 17 publications

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“…Going through the research results [104][105][106][107][108][109][110], we can figure out that there have been some achievements in the risk measurement of hazardous materials transportation, transportation route optimization, and transport fleet scheduling, including at least the following six aspects:…”

Section: Problems In Current Researchmentioning

confidence: 99%

Fleet Scheduling Optimization of Hazardous Materials Transportation: A Literature Review

Zhou

et al. 2020

Journal of Advanced Transportation

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To comprehensively understand the research progress of the fleet scheduling for hazardous materials, the study has summarized the corresponding research results from three aspects (a) hazardous materials transportation risk, (b) route optimization, and (c) fleet scheduling, and then pointed out potential problems from six aspects: (a) the coupling risk of the transport fleet; (b) the screening of time and space for the transport of hazardous materials; (c) the scheduling optimization for transport fleets; (d) taking insufficient account of transport risks fairness; (e) insufficient robustness of scheduling schemes; and (f) lacking of research results on fleet scheduling of transport in the context of antiterrorism. After that, by considering the existing shortcomings of the current research, five research directions are presented that should be further explored in the future. Subsequently, both rough set and association rule theory is applied to explore the cause chain of transportation accidents for hazardous materials, and analyze the mechanism of transport accident for hazardous materials. Next, the Bayesian network is presented to predict the accident rate of hazardous materials transportation under different temporal and spatial conditions, and the dynamic rolling scheduling method of hazardous materials transport fleet is constructed under normal and antiterrorism background.

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Section: Problems In Current Researchmentioning

confidence: 99%

Fleet Scheduling Optimization of Hazardous Materials Transportation: A Literature Review

Zhou

et al. 2020

Journal of Advanced Transportation

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“…Shafahi and Khani 8 established a mixed integer programming model to minimize the waiting time considering the extra stopping time of vehicles at transfer stations. Niu et al 9 proposed a non-linear optimization model to minimize passenger waiting time at station and crowding disutility in the trains when passengers have a transfer between two interconnected high-speed rail lines. Tian and Niu 10 proposed a bi-objective integer programming model integrated with irregular headways to optimize the train timetables for transfer synchronization, in order to minimize the total waiting time and maximize the number of connections.…”

Section: Literature Reviewmentioning

confidence: 99%

Scheduling overnight trains for improving both last and first train services in an urban subway network

Wang

Wei

Zhang

et al. 2019

Advances in Mechanical Engineering

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In most urban subway networks, passengers may make a transfer at night or in the early morning to arrive at their destinations. Given that passengers may confronted with transfer failure at night or long waiting in the morning, scheduling overnight trains is beneficial to both the last and first train services in the urban metro network, in particular, to minimize the number of failed transfer passengers in the last train service and the transfer waiting time for the first train service. Then, we formulate the overnight train scheduling problem as a mixed integer linear programming model based on a well-designed time-discretized space-time network. To handle large-scale applications, we decompose the proposed model into two space-time path-searching sub-problems and a semi-assignment problem through Lagrangian relaxationbased decomposition and solution framework. Finally, we adopt Beijing Subway Network as a practical case study. The results show that both the number of failed transfer passengers for last train service and the passenger transfer waiting time for first train service decrease significantly if the operators can schedule the overnight trains in Beijing Subway Network according to the optimization results of the proposed model.

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“…[1][2][3] In contrast, other studies have straightforward viewed the departure and arrival times as the decision variables. [4][5][6][7][8][9][10] The primary reason leading to this distinction is that the assumption conditions of these studies (i.e. deterministic and probabilistic conditions) are different.…”

Section: Introductionmentioning

confidence: 99%

“…Hsu 15 formulated a continuous model to calculate the mean passenger transfer waiting time. Recently, Niu et al 10 calculated the exact total transfer waiting time under the condition of timevarying demand. Furthermore, some papers calculated the approximate passenger transfer waiting time.…”

Section: Introductionmentioning

confidence: 99%

“…7 In addition, because connection optimization is a complex task, the synchronizing train timetables in different networks are optimized using special models and algorithms. The example of two lines with a transfer station was studied by Niu et al 10 Sivakumaran et al 18 considered an idealized system that delivers its users to a common destination by requiring each transfer from a feeder to a trunk-line vehicle. For reducing transfer time in real time, Chowdhury and Chien 19 optimized dynamic dispatching vehicles at transfer stations by connecting four transit routes.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

A dynamic programming approach to synchronize train timetables

Tian

Niu

2017

Advances in Mechanical Engineering

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This article focuses on synchronizing timetables of train services at a rail transfer station. The main aim is to determine an optimal schedule of train services, given that the departure and arrival times of some particular trains are known. An exponential utility function is introduced to measure the synchronization levels between different train services. A nonlinear integer programming model is proposed to achieve the objective of a synchronized timetable. A dynamic programming approach is then designed to solve the developed model. Finally, a numerical example with real-world datasets is implemented to demonstrate the effectiveness of the proposed approaches.

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Demand-Driven Train Schedule Synchronization for High-Speed Rail Lines

Cited by 63 publications

References 17 publications

Fleet Scheduling Optimization of Hazardous Materials Transportation: A Literature Review

Fleet Scheduling Optimization of Hazardous Materials Transportation: A Literature Review

Scheduling overnight trains for improving both last and first train services in an urban subway network

A dynamic programming approach to synchronize train timetables

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