Modeling of Railway Stations Based on Queuing Networks

Among the micro-logistic transport systems, railway stations should be highlighted, such as one of the most important transport infrastructure elements. The efficiency of the transport industry as a whole depends on the quality of their operation. Such systems have a complex multi-level structure, and the incoming traffic flow often has a stochastic character. It is known that the most effective approach to study the operation of such systems is mathematical modeling. Earlier, we proposed an approach to transport hub modeling using multiphase queuing systems with a batch Markovian arrival process (BMAP) as an incoming flow. In this paper, we develop the method by applying more complex models based on queuing networks that allow us to describe in detail the route of requests within an object with a non-linear hierarchical structure. This allows us to increase the adequacy of modeling and explore a new class of objects—freight railway stations and marshalling yards. Here we present mathematical models of two railway stations, one of which is a freight railway station located in Russia, and the other is a marshalling yard in the USA. The models have the form of queuing networks with BMAP flow. They are implemented as simulation software, and a numerical experiment is carried out. Based on the numerical results, some “bottlenecks” in the structure of the studied stations are determined. Moreover, the risk of switching to an irregular mode of operation is assessed. The proposed method is suitable for describing a wide range of cargo and passenger transport systems, including river ports, seaports, airports, and multimodal transport hubs. It allows a primary analysis of the hub operation and does not need large statistical information for parametric identification.

[1]  Norman Weik,et al.  A quasi-birth-and-death process approach for integrated capacity and reliability modeling of railway systems , 2017, J. Rail Transp. Plan. Manag..

[2]  Boris S. Kerner,et al.  Introduction to Modern Traffic Flow Theory and Control: The Long Road to Three-Phase Traffic Theory , 2009 .

[3]  Richard J. Boucherie,et al.  Running times on railway sections with heterogeneous train traffic , 1998 .

[4]  Wang Bao-hua,et al.  Survey of Stage Plan for Railway Marshalling Station , 2011 .

[5]  Stefan Panic,et al.  A stochastic model for estimation of repair rate for system operating under performance based logistics , 2017 .

[6]  Antonio Liotta,et al.  Statistical Assessment of IP Multimedia Subsystem in a Softwarized Environment: A Queueing Networks Approach , 2019, IEEE Transactions on Network and Service Management.

[7]  Petr Alexeyevich Kozlov,et al.  Optimization of Fleet Size and Structure While Serving Given Freight Flows , 2019 .

[8]  Leo G. Kroon,et al.  On solving multi-type railway line planning problems , 2006, Eur. J. Oper. Res..

[9]  David M. Lucantoni,et al.  New results for the single server queue with a batch Markovian arrival process , 1991 .

[10]  Randolph W. Hall,et al.  Railroad classification yard throughput: The case of multistage triangular sorting☆ , 1983 .

[11]  Valery Zubkov,et al.  Elaboration of a Model of Integrated Transport Service in the Segment of Freight Transportation , 2020 .

[12]  A. L. Kazakov,et al.  A Stochastic Model of a Transport Hub and Multi-phase Queueing Systems , 2018, CloudCom 2018.

[13]  M L Zharkov,et al.  Transient process modeling in micrologistic transport systems , 2021 .

[14]  Norman Weik,et al.  Quantifying the effects of running time variability on the capacity of rail corridors , 2020, J. Rail Transp. Plan. Manag..

[15]  Stefan Panic,et al.  A Stochastic Model for Achieving Required Level of Availability Based on the Repair Rate Analysis , 2019 .

[16]  Konstantin E. Samouylov,et al.  Retrial Tandem Queue with BMAP -Input and Semi-Markovian Service Process , 2017 .

[17]  Norman Weik,et al.  Capacity analysis of railway lines in Germany - A rigorous discussion of the queueing based approach , 2016, J. Rail Transp. Plan. Manag..

[18]  Andrei Tchernykh,et al.  Analysis of Mobility Patterns for Public Transportation and Bus Stops Relocation , 2019, Programming and Computer Software.

[19]  Richard J. Boucherie,et al.  A solvable queueing network model for railway networks and its validation and applications for the Netherlands , 2002, Eur. J. Oper. Res..

[20]  I. A. Hansen,et al.  Optimizing capacity utilization of stations by estimating knock-on train delays , 2007 .

[21]  Alexander L. Kazakov,et al.  An intelligent management system for the development of a regional transport logistics infrastructure , 2016, Autom. Remote. Control..

[22]  Michal Dorda,et al.  Modelling of Freight Trains Classification Using Queueing System Subject to Breakdowns , 2013 .

[23]  Ludolf E. Meester,et al.  Stochastic delay propagation in railway networks and phase-type distributions , 2007 .

[24]  E Wendler The scheduled waiting time on railway lines , 2007 .

[25]  M. Markovic,et al.  Effects of the application of conventional methods in the process of forming the pick-up trains , 2007 .

[26]  Erhan Kozan,et al.  Modeling Train Delays in Urban Networks , 1998, Transp. Sci..

[27]  Andrei Tchernykh,et al.  Operating cost and quality of service optimization for multi-vehicle-type timetabling for urban bus systems , 2018, J. Parallel Distributed Comput..

[28]  Michele Pagano,et al.  Modeling of Mathematical Processing of Physics Experimental Data in the Form of a Non-Markovian Multi-Resource Queuing System , 2019, Russian Physics Journal.