Modeling strategies for effectively routing freight trains through complex networks

Murali, Pavankumar; Ordóñez, Fernando; Dessouky, Maged

doi:10.1016/j.trc.2015.08.022

Cited by 38 publications

(17 citation statements)

References 37 publications

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“…Generally, in scheduling process, the specific structures of railway lines can influence the generated timetables greatly (Murali et al, 2015;Pouryousef et al, 2016). From an economic point of view, Castillo et al (2015) proposed alternate double-single track lines for double-track lines to decrease the total construction cost with only small changes of the timetable, the main idea of which is using the single track at expensive segments and double track at cheaper segments.…”

Section: Literature Reviewmentioning

confidence: 99%

Integrated multi-track station layout design and train scheduling models on railway corridors

Yang

Gao

et al. 2016

Transportation Research Part C: Emerging Technologies

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Section: Literature Reviewmentioning

confidence: 99%

Integrated multi-track station layout design and train scheduling models on railway corridors

Yang

Gao

et al. 2016

Transportation Research Part C: Emerging Technologies

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“…Delay of activity ( , ) ( , ) Disturbance occurred at ( , ) ( , ) random processing times for activities due to the disturbances ( , ) Safety headway before an activity ℎ ( , ) Safety headway after an activity [23]. Each node represents the portion of track segments and other resources of railway network.…”

Section: Modeling Methodologymentioning

confidence: 99%

“…Aggregation. The aggregation concept introduced by Murali et al [23] is adopted to reduce the computational effort for the real-world case. In literature, Corman et al [25] used the same concept for railway traffic management.…”

Section: Modeling Methodologymentioning

confidence: 99%

Increasing Robustness by Reallocating the Margins in the Timetable

Meng

Abid

Jiang

et al. 2019

Journal of Advanced Transportation

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It is a common practice to improve the punctuality of a railway service by the addition of time margins during the planning process of a timetable. Due to the capacity constraints of the railway network, a limited amount of time margins can be inserted. The paper presents a model and heuristic technique to find the better position for the limited amount of time margins (headway buffers and running time supplements) in a train timetable. The aim of reallocating the time margins is to adjust an existing timetable to minimize the sum of train delays at the event of the operational disturbances. The model consists of two basic parts. Firstly, the paper treats the train timetable as a Directed Arc Graph (DAG) with the aggregation concept and proposes a heuristic technique known as Critical Time Margins Allocation (CTMA), which is based on the critical path method (CPM), to reallocate the time margins. Secondly, the paper evaluates the original and modified timetable under different disturbed situations. The case study is developed on a hypothetical small railway network and a practical timetable of single-line train timetable for the track segment of Rawalpindi to Lalamusa, Pakistan. The results show that the timetable modified with the CTMA reduces the total delay time by an average of 3.25% for the small railway network and 5.18% for the large dataset. It suggests that adding the time supplements to the proper positions in a timetable can reduce the delay propagation and increase the robustness of the timetable.

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Section: Introductionmentioning

confidence: 99%

“…Indexes such as degree centrality, betweenness centrality, and closeness centrality have an outstanding ability to identify key nodes from the network [11][12][13][14]. Sheikhahmadi et al [12] proposed an improved high degree centrality index to identify the S. Sun, H. Li, X. Xu: A Key Station Identification Method for Urban Rail Transit: A Case Study of Beijing Subway most influential nodes, which outperformed other indexes on large-scale networks in terms of maximizing the spread of influence with acceptable running time.…”

Section: Introductionmentioning

confidence: 99%

A Key Station Identification Method for Urban Rail Transit: A Case Study of Beijing Subway

Sun

2017

PROMET

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INTRODUCTIONWith the rapid development of urban rail transit network operation technique, the increase of passenger volume leads to congestion in stations [1], causing even safety risk in the network [2]. Besides, the topology of urban rail transit network can also aggravate or relief the congestion situation of subway networks. Therefore, an effective method identified the key station is an imperative to manage the overcrowded urban rail transit.For the factors of the station performance, many of the current approaches focus on the relationship between passenger flow and facility capacity. Xu et al.[3] combined queuing theory with facility utilization evaluation to conduct the station capacity evaluation, according to the gathering and scattering process of a station. Kepaptsoglou and Karlaftis [4] proposed a model to evaluate passenger evolution on subway station platforms, which usually gathered most passengers. Wang et al.[5] also used the passenger evacuation capacity to evaluate the station based on the facility utilization. If the service level of the facility is too low, there are big problems in the station.Besides, passengers' subjective feelings and other factors are also used for evaluation. Matulin et al.[6] proposed a two-level evaluation method to analyze public transport performances from micro and macro levels, using performance indicators and quality of service indicators. Kesten and Öğüt [7] developed a measurement framework of passenger-oriented performance to evaluate rail transportation, using satisfaction and importance ratings obtained from passenger surveys.Meanwhile, there are many approaches employed in the station evaluation. Some typical methods such as Data Envelopment Analysis (DEA) have played their great role in the station assessment. Sancha et al. [8] used the method to estimate the technical, social and environmental efficiency of transit transfer stations. Pjevčević et al. [9] used DEA method to measure and analyze the efficiencies of ports on the Danube River, which can be borrowed for station evaluation. In addition, simulation is also another method, where relevant simulation or operation data are provided. Zhang et al. [10] proposed a cellular automata-based model to simulate passengers' alighting and boarding behaviours in metro stations, aiming to analyze and evaluate the operation performance of stations. However, most works above do not consider the influence of other stations in the subway system, which results in local rather than global conclusions.Fortunately, in recent years, a complex network theory has been introduced to the station evaluation from a global viewpoint. Indexes such as degree centrality, betweenness centrality, and closeness centrality have an outstanding ability to identify key nodes from the network [11][12][13][14]. Sheikhahmadi et al. [12] proposed an improved high degree centrality index to identify the Traffic Management Original Scientific Paper

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Modeling strategies for effectively routing freight trains through complex networks

Cited by 38 publications

References 37 publications

Integrated multi-track station layout design and train scheduling models on railway corridors

Integrated multi-track station layout design and train scheduling models on railway corridors

Increasing Robustness by Reallocating the Margins in the Timetable

A Key Station Identification Method for Urban Rail Transit: A Case Study of Beijing Subway

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