An integrated rescheduling model for minimizing train delays in the case of line blockage

Shakibayifar, Masoud; Sheikholeslami, Abdolreza; Corman, Francesco; Hassannayebi, Erfan

doi:10.1007/s12351-017-0316-7

Cited by 26 publications

(15 citation statements)

References 50 publications

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“…Constraints (16) define the new weight of fixed arcs as greater than or equal to the predefined one in the MTSM.…”

Section: Min-max Approach Train Rescheduling Model (Mtrm)mentioning

confidence: 99%

“…The disturbances in rail context represents one of the main critical issue due to the possible propagation of the delays in the network which may affect the reliability of the TS [16]. In [16] the authors, proposed an heuristic approach which introduced recovery actions in order to minimize the impact of disturbances to the TS taking into account train capacity, fleet size, the maximum allowed delay for each train and safety constraints.…”

Section: Introductionmentioning

confidence: 99%

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Min-Max Approach for High-Speed Train Scheduling and Rescheduling Models

2021

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This paper focuses on the operational and real time control of railway management. A passengers centric scheduling and rescheduling models are formalized as a linear mathematical model and by a min max technique. The proposed approach determines the train timetables for scheduling rail services along a multiline rail network according to operational constraints related to train capacity, train speed limits, passenger's train transfers, possible conflict in the track section use, with the main objective to minimize the travel time of a set of passengers' groups. The network is formalized as a set of nodes which represent logistic operations of the trains and arcs which define the sequence of tasks to be carried out by trains. Alternative arcs have been added to solve the Conflict Resolution Problem (CRP) which may appears when two trains require simultaneously to cover the same block section. The timetable resulted by the scheduling problem have been used as the input of a rescheduling model where predefined disturbances have been assumed to some nodes of the network. The effectiveness of the proposed approach have been verified comparing its performances with a traditional minimization rescheduling model both based on the minimization of the passengers' discomfort in terms of delay propagation in the travel times. The model guarantees more resilience for trains classified with higher priority. The proposed models are applied to the real case study of the rail network for high-speed trains in the Northern Italy INDEX TERMS High-speed train, Min-Max approach, Train rescheduling, Train scheduling

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“…Constraints (16) define the new weight of fixed arcs as greater than or equal to the predefined one in the MTSM.…”

Section: Min-max Approach Train Rescheduling Model (Mtrm)mentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Min-Max Approach for High-Speed Train Scheduling and Rescheduling Models

2021

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“…The results show significant reductions in the passenger waiting time through the proposed robust model. Shakibayifar et al [49] presented a train rescheduling model to minimize the total travel time of trains in Iranian rail networks. A heuristic approach was proposed to design a disposition timetable in a reasonable time.…”

Section: Literature Reviewmentioning

confidence: 99%

A Multi-objective Optimization Model for Robust Skip-Stop Scheduling with Earliness and Tardiness Penalties

2019

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Inefficient transport systems impose extra travel time for travelers, cause dissatisfaction and reduce service levels. In this study, the demand-oriented train scheduling problem is addressed using a robust skip-stop method under uncertain arrival rates during peak hours. This paper presents alternative mathematical models, including a twostage scenario-based stochastic programming model and two robust optimization models, to minimize the total travel time of passengers and their waiting time at stations. The modeling framework accounts for the design and implementation of robust skip-stop schedules with earliness and tardiness penalties. As a case study, each of the developed models is implemented on line No. 5 of the Tehran metro, and the results are compared. To validate the skip-stop schedules, the values of the stochastic solution and the expected value of perfect information are calculated. In addition, a sensitivity analysis is conducted to test the performance of the model under different scenarios. According to the obtained results, having perfect information can reduce up to 16% of the value of the weighted objective function. The proposed skip-stop method has been shown to save about 5% in total travel time and 49% in weighted objective function, which is a summation of travel times and waiting times as against regular all-stop service. The value of stochastic solutions is about 21% of the value of the weighted objective function, which shows that the stochastic model demonstrates better performance than the deterministic model.

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“…Posing specific attention to railway systems, disruption management is a popular topic and many studies investigate operational planning techniques such as timetabling and rescheduling to reduce the impact of disruptions ( [38][39][40][41][42]). Conversely, when it comes to railway system strategic planning against worst-case disruptions, the literature is still scarce.…”

Section: Systemic Approach To Fortificationmentioning

confidence: 99%

Assessing Protection Strategies for Urban Rail Transit Systems: A Case-Study on the Central London Underground

2019

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Urban rail transit systems are highly prone to disruptions of various nature (e.g., accidental, environmental, man-made). Railway networks are deemed as critical infrastructures given that a service interruption can prompt adverse consequences on entire communities and lead to potential far-reaching effects. Hence, the identification of optimal strategies to mitigate the negative impact of disruptive events is paramount to increase railway systems’ resilience. In this paper, we investigate several protection strategies deriving from the application of either single asset vulnerability metrics or systemic optimization models. The contribution of this paper is threefold. Firstly, a single asset metric combining connectivity, path length and flow is defined, namely the Weighted Node Importance Evaluation Index (WI). Secondly, a novel bi-level multi-criteria optimisation model, called the Railway Fortification Problem (RFP), is introduced. RFP identifies protection strategies based on stations connectivity, path length, or travel demand, considered as either individual or combined objectives. Finally, two different protection strategy approaches are applied to a Central London Underground case study: a sequential approach based on single-asset metrics and an integrated approach based on RFP. Results indicate that the integrated approach outperforms the sequential approach and identifies more robust protection plans with respect to different vulnerability criteria.

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An integrated rescheduling model for minimizing train delays in the case of line blockage

Cited by 26 publications

References 50 publications

Min-Max Approach for High-Speed Train Scheduling and Rescheduling Models

Min-Max Approach for High-Speed Train Scheduling and Rescheduling Models

A Multi-objective Optimization Model for Robust Skip-Stop Scheduling with Earliness and Tardiness Penalties

Assessing Protection Strategies for Urban Rail Transit Systems: A Case-Study on the Central London Underground

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