Simultaneous train rerouting and rescheduling on an N-track network: A model reformulation with network-based cumulative flow variables

Meng, Lingyun; Zhou, Xuesong

doi:10.1016/j.trb.2014.05.005

Cited by 242 publications

(131 citation statements)

References 35 publications

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“…As stated by Meng and Zhou [33], to improve the competitive advantages of rail operators, providing punctual and reliable train services is a fundamental goal. A train schedule typically contains detailed departure times, arrival times, train orders, and train circulation plan for each train service in the urban rail transit line.…”

Section: Optimal Train Scheduling Problemmentioning

confidence: 99%

A Short Turning Strategy for Train Scheduling Optimization in an Urban Rail Transit Line: The Case of Beijing Subway Line 4

Zhang

Wang

et al. 2018

Journal of Advanced Transportation

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In urban rail transit systems, train scheduling plays an important role in improving the transport capacity to alleviate the urban traffic pressure of huge passenger demand and reducing the operation costs for operators. This paper considers the train scheduling with short turning strategy for an urban rail transit line with multiple depots. In addition, the utilization of trains is also taken into consideration. First, we develop a mixed integer nonlinear programming (MINLP) model for the train scheduling, where short turning train services and full-length train services are optimized based on the predefined headway obtained by the passenger demand analysis. The MINLP model is then transformed into a mixed integer linear programming (MILP) model according to several transformation properties. The resulting MILP problem can be solved efficiently by existing solvers, e.g., CPLEX. Two case studies with different scales are constructed to assess the performance of train schedules with the short turning strategy based on the data of Beijing Subway line 4. The simulation results show that the reduction of the utilization of trains is about 20.69%.

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Section: Optimal Train Scheduling Problemmentioning

confidence: 99%

A Short Turning Strategy for Train Scheduling Optimization in an Urban Rail Transit Line: The Case of Beijing Subway Line 4

Zhang

Wang

et al. 2018

Journal of Advanced Transportation

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“…In [9]have formulated a new technique to obtain an efficient decomposition mechanism through modelling track capacities as side constraints using IP model. These side constraints are then dualised through a new Lagrangianrelaxation solution technique.…”

Section: Several Model Approaches For Rescheduling Have Been Proposedmentioning

confidence: 99%

Priority based technique for rescheduling trains

Alwadood

Shuib

Hamid

2018

J. Fundam and Appl Sci.

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This paper presents a novel approach to solve a railway rescheduling problem using a Mixed Integer Goal Programming (MIGP) model rescheduling timetable based on train priorities whenever a service disruption occurs. The objectives are to minimize the total delay time of all trains in the rail line and maximize the service reliability. The experiments were done on Malaysian double track railway system and the model was solved using a heuristics approach great influence on the total delay time and service reliability. This r more advanced and practical model as it is able to produce the provisional timetable in short computing time and the solution generated satisfies all the restrictions posed by the rail operator. This paper presents a novel approach to solve a railway rescheduling problem using a Mixed KeywordsProgramming (MIGP) model. The model is developed to find a new rescheduling timetable based on train priorities whenever a service disruption occurs. The objectives are to minimize the total delay time of all trains in the rail line and maximize the service reliability. The experiments were done on Malaysian double track railway system and the model was solved using a heuristics approach. The result shows that train priority has a great influence on the total delay time and service reliability. This research has proposed a more advanced and practical model as it is able to produce the provisional timetable in short computing time and the solution generated satisfies all the restrictions posed by the rail rescheduling; mathematical modelling; service disruptions; priority.

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“…This problem has been shown to be NP-hard even in the feasibility case ( Remarkable improvements with respect to the current practice and/or to the basic dispatching rules adopted in most practical applications are reported in these papers. Other approaches to TS based on Mixed Integer Linear Programs (MILPs) are reported, e.g., in Törnquist Krasemann (2011), Lamorgese and Mannino (2014), Meng and Zhou (2014), Pellegrini et al (2014). The goal of all these approaches is to find a train schedule, i.e., a departure/passing time for each train et each relevant point of the railway network, compatible with the real time position of each train and such that a suitable function of the train delays is minimized.…”

Section: Train Schedulingmentioning

confidence: 99%

Rescheduling Railway Traffic Taking into Account Minimization of Passengers’ Discomfort

Corman

Pacciarelli

D’Ariano

et al. 2015

Lecture Notes in Computer Science

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Simultaneous train rerouting and rescheduling on an N-track network: A model reformulation with network-based cumulative flow variables

Cited by 242 publications

References 35 publications

A Short Turning Strategy for Train Scheduling Optimization in an Urban Rail Transit Line: The Case of Beijing Subway Line 4

A Short Turning Strategy for Train Scheduling Optimization in an Urban Rail Transit Line: The Case of Beijing Subway Line 4

Priority based technique for rescheduling trains

Rescheduling Railway Traffic Taking into Account Minimization of Passengers’ Discomfort

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