Managing and Preventing Delays in Railway Traffic by Simulation and Optimization

Suhl, Leena; Mellouli, Taïeb; Biederbick, Claus; Goecke, Johannes

doi:10.1007/978-1-4757-3357-0_1

Cited by 20 publications

(6 citation statements)

References 2 publications

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“…[1,3,4,5,9,10,12]). Most of them aim at one general objective like minimizing 1 This section is an abbreviated version of [21], section 1.…”

Section: Optimization Of Tram Schedulesmentioning

confidence: 99%

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A Robust Schedule for Montpellier’s Tramway Network

Ullrich¹,

Lückerath²,

Speckenmeyer³

2015

SNE

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The city of Montpellier in the Languedoc-Roussillon region of France features a fast growing tram network as a central part of its public service infrastructure. Here, as in many other tram networks, resources like tracks and stations are shared between dierent lines. Because of the resulting dependencies, small inevitable delays can spread through the network and aect its global performance.This article examines whether a robust tram schedule may help to raise punctuality in Montpellier's tram network. To accomplish this, we apply a tool set designed to generate schedules optimized for robustness, which also satisfy given sets of planning requirements. These tools allow to compare time tables with respect to their punctuality and other key indicators.After an introduction to the goals of this paper, we continue with a description of the tool set focusing on optimization and simulation modules. These software utilities are then employed to generate and simulate robust and non-robust schedules for Montpellier's tram network, which are subsequently compared for the resulting delays.

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“…[1,3,4,5,9,10,12]). Most of them aim at one general objective like minimizing 1 This section is an abbreviated version of [21], section 1.…”

Section: Optimization Of Tram Schedulesmentioning

confidence: 99%

“…vehicle delay (see [10,12]) or maximizing robustness to restrict the global impact of small, local disturbances (see [4,5]). Others use a combination of objectives, like operational prot and robustness in [3], or combining social opportunity cost and operational cost in [11].…”

Section: Optimization Of Tram Schedulesmentioning

confidence: 99%

A Robust Schedule for Montpellier’s Tramway Network

Ullrich¹,

Lückerath²,

Speckenmeyer³

2015

SNE

View full text Add to dashboard Cite

show abstract

“…[1,3,4,7,16,17,18]). Most of them aim at one general objective like minimizing vehicle delay (see [16,18]) or maximizing robustness to restrict the global impact of small, local disturbances (see [4,7]). Others use a combination of objectives, like operational profit and robustness in [3], or combining social opportunity cost and operational cost in [17].…”

Section: Optimization Of Tram Schedulesmentioning

confidence: 99%

Simulation and Optimization of Cologne's Tram Schedule

Ullrich¹,

Franz²,

Speckenmeyer³

et al. 2012

SNE

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In many tram networks multiple lines share tracks and stations, thus requiring robust schedules which prevent inevitable delays from spreading through the network. Feasible schedules also have to fulfill various planning requirements originating from political and economical reasons.In this paper we present a tool set designed to generate schedules optimized for robustness, which also satisfy given sets of planning requirements. These tools allow us to compare time tables with respect to their applicability and evaluate them prior to their implementation in the field.This paper begins with a description of the tool set focusing on optimization and simulation modules. These software utilities are then employed to generate schedules for our hometown Cologne's tram network, and to subsequently compare them for their applicability.

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“…Simulation modeling approaches have been used extensively in transportation applications as a exible and powerful method to evaluate the robustness and reliability of the system (see [2,[6][7][8][9][10][11][12][13][14]). However, despite the fact that the train-rescheduling problem has been analyzed extensively, a limited research has been directed to the combination of simulation platforms with advanced search techniques to solve train-rescheduling problems under uncertainty.…”

Section: Introductionmentioning

confidence: 99%

A simulation-based optimization approach to reschedule train traffic in uncertain conditions during disruptions

2017

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Abstract. Delays and disruptions reduce the reliability and stability of the rail operations.Railway tra c rescheduling includes ways to manage the operations during and after the occurrence of such disturbances. In this study, we consider the simultaneous presence of large disruptions (temporary full or partial blockage of tracks) as well as stochastic variation of operations as a source of disturbance. The occurrence time of blockage and its recovery time are given. We designed a simulation-based optimization model that incorporates dynamic dispatch priority rules with the objective of minimizing the total delay time of trains. We, moreover, designed a variable neighborhood search meta-heuristic scheme for handling tra c under the limited capacity close to the blockage. The new plan includes a set of new departure times, dwell times, and train running times. We evaluated the proposed model on a set of disruption scenarios covering a large part of the Iranian rail network. The result indicates that the developed simulation-based optimization approach has substantial advantages in producing practical solution quickly, when compared to commercial optimization software. In addition, the solutions have a lower average and smaller standard deviation than the currently accepted solutions, determined by human dispatcher or by standard software packages.

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Managing and Preventing Delays in Railway Traffic by Simulation and Optimization

Cited by 20 publications

References 2 publications

A Robust Schedule for Montpellier’s Tramway Network

A Robust Schedule for Montpellier’s Tramway Network

Simulation and Optimization of Cologne's Tram Schedule

A simulation-based optimization approach to reschedule train traffic in uncertain conditions during disruptions

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