A Fast Approach for Reoptimization of Railway Train Platforming in Case of Train Delays

Zhang, Yongxiang; Zhong, Qingwei; Yin, Yong; Yan, Xu; Peng, Qiyuan

doi:10.1155/2020/5609524

Cited by 12 publications

(10 citation statements)

References 48 publications

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“…Method extensions and practical applications were also discussed. In addition, evaluation work can be further combined with other transportation organization or disruption management research to formulate collaborative optimization strategies, such as robust train timetabling [57], train platforming [58], rolling stock scheduling [59], and energy saving [60]. e method of parameter estimation needs to be improved.…”

Section: Discussionmentioning

confidence: 99%

Evaluating Railway Operation Safety Situation in China Based on an Improved TOPSIS Method: A Regional Perspective

Yan

Peng

Yin

et al. 2020

Journal of Advanced Transportation

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The evaluation of the railway operation safety situation is important for managers to ensure transportation safety and make control decisions. In this study, first, six situation indicators are designed from a regional perspective based on the characteristics of railway operation accidents, and the quantitative methods of these indicators are determined. Second, an improved technique for order of preference by similarity to ideal solution (TOPSIS) method is developed to evaluate the railway operation safety situation against the situation indicators. Based on the set-pair analysis (SPA) theory and cosine similarity measure (CSM), the comprehensive evaluation values and rankings of the safety situation are first calculated from the distance and trend levels for each period. Game theory is then employed to determine a more reasonable combined weight, and the values of the parameters involved in the situation indicators are also estimated. The real-life statistical accident data in a regional area of China from 2016 to 2018 are chosen as a case study to verify the proposed method. A brief analysis is conducted, resulting in suggestions for the evaluation results. Two groups of comparative experiments are designed to demonstrate the feasibility and effectiveness of the method. Finally, the quality of the evaluation results is verified through actual conditions and expert scoring. Some extensions and potential practical applications of this work are discussed.

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Section: Discussionmentioning

confidence: 99%

Evaluating Railway Operation Safety Situation in China Based on an Improved TOPSIS Method: A Regional Perspective

Yan

Peng

Yin

et al. 2020

Journal of Advanced Transportation

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“…(16) D i s (2) i = s (1) i+1 , s (2) i+1 , s (3) i+1 (17) D i s (3) i = s (3) i+1 , s (4) i+1 (18) i+1 = D i s (1) i ∪ D i s (1) i ∪ D i s (2) i = s (1) i+1 , s (2) i+1 , s (3) i+1 , s (4) i+1 (19)…”

Section: I+1unclassified

“…M. Wang et al [18] developed a genetic algorithm based on the particle swarm optimization (PSO) to solve the TRP under primary delays. Y. Zhang et al [19] studied the problem of re-optimization of train platform in case of train delays, where the station is modeled using the discretization of the platform track time-space resources. In addition, for solving the MILP model, an efficient heuristic algorithm is designed to speed up the re-optimization process with good solution precision.…”

Section: Introductionmentioning

confidence: 99%

Multi-stage timetable rescheduling for high-speed railways: a dynamic programming approach with adaptive state generation

Feng

Cui

et al. 2021

Complex Intell. Syst.

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A dynamic programming (DP) approach with adaptive state generation and conflicts resolution is developed to address the timetable-rescheduling problem (TRP) at relatively lower computation costs. A multi-stage decision-making model is first developed to represent the timetable-rescheduling procedure in high-speed railways. Then, an adaptive state generation method by reordering the trains at each station is proposed to dynamically create the possible states according to the states of previous stages, such that the infeasible states can be removed and the search space is reduced. Then, conflicts are resolved by retiming the arrival and/or departure times of trains. Furthermore, the state transfer equation is built and Bellman equation is developed to derive the solution to minimize the total delay time (TT). A series of simulation experiments and a real-world case study are used to evaluate the performance of the proposed method. The simulation experiments indicate that the proposed method is able to find the optimal timetable with appropriate overtaking at right stations and reduce the total delay by 62.7% and 41.5% with respect to the First-Come-First-Serve (FCFS) and First-Schedule-First-Serve (FSFS) strategy that are widely used in practice. Comparing to the intelligent scheduling method (e.g., Ant Colony Optimization and Particle Swarm Optimization), similar objective performance can be achieved at a much lower cost of computation time, which make the proposed method more applicable to the TRP in daily operation of high-speed railway.

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“…Zhang et al. (2020) proposed a mixed integer linear programming model, which minimized the weighted sum of total train delays and the platform track assignment costs, subject to constraints defined by operational requirements [52].…”

Section: Related Workmentioning

confidence: 99%

“…Vansteenwegen et al (2019) proposed a conflict prevention strategy for large and complex networks in real-time railway traffic management based on the analysis of the impact of the unexpected events such as overcrowded platforms or small mechanical defects can cause conflicts [51]. Zhang et al (2020) proposed a mixed integer linear programming model, which minimized the weighted sum of total train delays and the platform track assignment costs, subject to constraints defined by operational requirements [52].…”

Section: Related Workmentioning

confidence: 99%

An integrated model for train rescheduling and station track assignment

Meng

Wang

Xiang

et al. 2020

IET Intelligent Trans Sys

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Both train rescheduling and station track assignment have become hot topics in recent years. It is fundamentally important to do the rescheduling and track assignment work at the same time to avoid the feasibility risk of the re‐scheduled timetable. The purpose of this paper is to design an integrated model for train rescheduling and track assignment in order to provide an integrative plan for the trains to run on the railway sections and go through stations. Based on the existing train rescheduling model, the model is designed by adding the constraints and the optimization goal of track assignment. The goal of track assignment is to maximize the equilibrium of the track usage time, and the constraint is that two trains cannot occupy a same track at the same time. An artificial bee colony algorithm is used to solve the model to get the operation plan. A computing experiment was carried out to prove the effectiveness of the model and the efficiency of the algorithm. The approach presented in this paper can provide a reference for the developers of a railway dispatching system.

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A Fast Approach for Reoptimization of Railway Train Platforming in Case of Train Delays

Cited by 12 publications

References 48 publications

Evaluating Railway Operation Safety Situation in China Based on an Improved TOPSIS Method: A Regional Perspective

Evaluating Railway Operation Safety Situation in China Based on an Improved TOPSIS Method: A Regional Perspective

Multi-stage timetable rescheduling for high-speed railways: a dynamic programming approach with adaptive state generation

An integrated model for train rescheduling and station track assignment

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