A mesoscopic simulation modelling methodology for analyzing and evaluating freight train operations in a rail network

Маринов, Марин; Viegas, José M.

doi:10.1016/j.simpat.2010.08.009

Cited by 74 publications

(43 citation statements)

References 13 publications

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“…Simulation models help analyse the impacts of these changes [6,7,11,12,13]. The capacity of a system is defined as its ability to move a certain amount of traffic before reaching saturation with minimal influence to the other parameters of the system.…”

Section: Simulation Modellingmentioning

confidence: 99%

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An Event-based Simulation Model for Analysing the Utilization Levels of a Railway Line in Urban Area

Singhania

Маринов

2017

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Section: Simulation Modellingmentioning

confidence: 99%

“…This approach involves breaking up the system into different segments for research purposes, [7,8]. While using the method of decomposition it is crucial to maintain continuity within the system to extract an accurate analysis from the model.…”

Section: Simulation Modellingmentioning

confidence: 99%

An Event-based Simulation Model for Analysing the Utilization Levels of a Railway Line in Urban Area

Singhania

Маринов

2017

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“…In particular, rail simulation models can be classified into macroscopic, mesoscopic or microscopic models, according to the level of network details adopted; stochastic or deterministic, according to the statistical assumption on analysed variables; synchronous or asynchronous, according to the ability to analyse different classes of trains jointly (such as high speed or regional trains). However, details on rail (or metro) simulation models can be found in Kettner and Sewcyk [33], Prinz et al [34], marinov and Viegas [35], Nash and Huerlimann [36] and Siefer and radtke [37].…”

Section: Introductionmentioning

confidence: 99%

A neighbourhood search algorithm for determining optimal intervention strategies in the case of metro system failures

Botte¹,

Salvo²,

Placido³

et al. 2017

Int. J. TDI

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In high-density contexts, such as urban or metropolitan areas, decision makers and mobility managers have to adopt suitable strategies to reduce the use of private cars and promote public transport. Indeed, such strategies may help abate the negative impacts of transportation systems (congestion, air and noise pollution, etc.). However, appropriate measures are only effective if based on the provision of high-quality public transport services. Such aims can be achieved by organizing public transport within an integrated framework where rail/metro services are the high-performing mobility backbone and bus services have a feeder function, increasing the geographical coverage of rail services. However, since a faulty train cannot be easily removed or overtaken, a rail/metro system is highly vulnerable to system breakdowns which could entail significant reductions in system quality. Suitable intervention strategies therefore have to be developed to manage rail system emergencies. The aim of this article is to provide a method to determine optimal intervention strategies in the case of a metro system failure. Since in real contexts an exhaustive approach has to be excluded due to the huge number of alternative solutions to be evaluated, it is necessary to adopt or develop appropriate algorithms to obtain sub-optimal solutions within suitable computational times. Hence a Neighbourhood Search Algorithm to identify the optimal solution is applied and tested in the case of a real metro line in order to show the feasibility of our proposal.

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“…Transport services must therefore be provided at an appropriate level; otherwise, the potential sender may decide to choose another service provider. Rail carriers, on the one hand, must meet their customers' expectations in a timely, fast, reliable, efficient, economical and secure manner [15]; on the other hand, market expectations are clearly defined. Customer needs are important in terms of both passenger and freight traffic.…”

Section: Introductionmentioning

confidence: 99%

Some Aspects of Heuristic Algorithms and Their Application in Decision Support Tools for Freight Railway Traffic Organization

2017

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Journal homepage: http://sjsutst.polsl.pl Article citation information: Jacyna, M., Gołębiowski, P., Krześniak, M. Some aspects of heuristic algorithms and their application in decision support tools for freight railway traffic organization. SOME ASPECTS OF HEURISTIC ALGORITHMS AND THEIR APPLICATION IN DECISION SUPPORT TOOLS FOR FREIGHT RAILWAY TRAFFIC ORGANIZATIONSummary. Rail traffic organization is a multifactorial decision-making problem. To achieve the best results and reduce the risk of error when deciding on its implementation, appropriate algorithms should be identified and implemented in the form of computer tools, allowing for the optimal solution to be obtained. This paper discusses the process of organizing freight traffic on the rail network. The algorithm of relocating loaded cars in a compact and dispersed system is discussed. In turn, it is been indicated that the movement of empty and loaded cars must follow a strictly defined timetable. A heuristic algorithm supporting decision-making in the area of rail freight traffic management is presented, divided between the concept development stage, the timetable design stage for the developed concept, and its implementation in the form of specialized tools. An example of how the application works is also presented.

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A mesoscopic simulation modelling methodology for analyzing and evaluating freight train operations in a rail network

Cited by 74 publications

References 13 publications

An Event-based Simulation Model for Analysing the Utilization Levels of a Railway Line in Urban Area

An Event-based Simulation Model for Analysing the Utilization Levels of a Railway Line in Urban Area

A neighbourhood search algorithm for determining optimal intervention strategies in the case of metro system failures

Some Aspects of Heuristic Algorithms and Their Application in Decision Support Tools for Freight Railway Traffic Organization

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