Optimal allocation of buffer times to increase train schedule robustness

Jovanović, Predrag; Kecman, Pavle; Bojović, Nebojša J.; Mandić, Danimir

doi:10.1016/j.ejor.2016.05.013

Cited by 56 publications

(25 citation statements)

References 35 publications

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“…Accordingly, several improved methods have been proposed for adjusting the buffer (Bevilacqua, Ciarapica, and Giacchetta 2009;Jovanovic et al 2016;Peng and Huang 2014). However, none of these traditional methods take into account how to get the resource usage and the resource constraints peak, so the result obtained is very limited.…”

Section: Introductionmentioning

confidence: 99%

Critical chain project buffer sizing based on resource constraints

Zhang

Song

Díaz

2016

International Journal of Production Research

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Project scheduling is a complex process involving many types of resources and activities that require optimisation. The resource-constrained project scheduling problem is one of the well-known problematic issues when project activities have to be scheduled to minimise the project duration. Consequently, several methods have been proposed for adjusting the buffer size but none of these traditional methods consider buffer sizing accuracy based on resource constraints. The purpose of this paper is to develop a buffer sizing method based on a fuzzy resource-constrained project scheduling problem in order to obtain an appropriate proportionality between the activity duration and the buffer size. Specifically, a comprehensive resource-constrained method that considers both the general average resource constraints (GARC) and the highest peak of resource constraints (HPRC) is proposed in order to obtain a new buffer sizing method. This paper contributes to the research by considering several different aspects. First, this paper adopts a fuzzy method to calculate and obtain the threshold amount. Second, this paper discusses the resource levelling problem and proposes the HPRC method. Third, the proposed method uses a fuzzy quantitative model to calculate the resource requirement. The findings indicate that the project achieved higher efficiency, providing effective protection and an appropriate buffer size.

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Section: Introductionmentioning

confidence: 99%

Critical chain project buffer sizing based on resource constraints

Zhang

Song

Díaz

2016

International Journal of Production Research

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“…Many factors affect TSSTT. First, the technical conditions of the railway line regarding safety constraints, such as the train's section speed limitations, should be met [1][2][3][4][5][6][7][8][9]. Additionally, the requirements of network operation and various passengers demand should be satisfied [10][11][12][13][14][15].…”

Section: Introductionmentioning

confidence: 99%

Suitability Evaluation of a Train’s Scheduled Section Travel Time

Qing

Yao

et al. 2020

Sustainability

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Two methods used to evaluate the suitability of a train's scheduled section travel time (TSSTT) are theoretical modeling and data analysis. The first is suitable for newly constructed railway projects, the second can reveal the reliability of the train section running time (TSRT) under an instruction of TSSTT in cases where the train operation data are provided. A suitability evaluation method of TSSTT is proposed by calculating the possibility that a train completes a task within the time windows, centering on the TSSTT given in advance. The TSRTs between two adjacent stations are classified into four groups based on whether the train dwells at the two end stations of the railway section, and then subdivided secondly into subgroups by the instruction of TSSTT given. The kurtosis of each subgroup data of TSRT is larger than 3, so Weibull distribution is selected to fit the TSRT distribution of subgroup data due to good fitness based on root measurement of the least square (SRLSM). A busy high-speed railway line in the Wuhan area of China is used to validate the presented approach. Each railway section has its own suitable TSSTT in which TSRT might achieve 96% reliability of arriving within 2.5 minutes centering on suitable TSSTT, otherwise which might not obtain 10% reliability.

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“…One recent paper on robustness methods, that is not mentioned in the included papers, is the work by Jovanovi¢ et al (2016) where the distribution of buer times is dened as a general Knapsack problem in which the total buer time in a timetable is the capacity of the Knapsack. In the same study, the distribution of buer times is based on the priority of locations with respect to delay sensitivity and delay propagation.…”

Section: Purpose Of Solving a Ttpmentioning

confidence: 99%

“…One important aspect of the study by Jovanovi¢ et al (2016) is that in order to reduce the complexity of the problem, the optimization model for robustness is separated from optimization model for timetabling.…”

Section: Purpose Of Solving a Ttpmentioning

confidence: 99%

Optimization-Based Methods for Revising Train Timetables with Focus on Robustness

Khoshniyat¹

2016

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With increase in the use of railway transport, ensuring robustness in railway timetables has never been this important. In a dense railway timetable even a small disturbance can propagate easily and aect trains' arrival and departure times. In a robust timetable small delays are absorbed and knock-on eects are prevented eectively.The aim of this thesis is to study how optimization tools can support the generation of robust railway trac timetables. We address two Train Timetabling Problems (TTP) and for both problems we apply Mixed Integer Linear Programming (MILP) to solve them from network management perspectives. The rst problem is how robustness in a given timetable can be assessed and ensured. To tackle this problem, a headway-based method is introduced. The proposed method is implemented in real timetables and evaluated from performance perspectives. Furthermore, the impact of the proposed method on capacity utilization, heterogeneity and the speed of trains, is monitored.Results show that the proposed method can improve robustness without imposing major changes in timetables. The second problem addressed in the thesis is how robustness can be assessed and maintained in a given timetable when allocating additional trac and maintenance slots. Dierent insertion strategies are studied and their consequences on capacity utilization and on the properties of the timetables are analyzed. Two dierent insertion strategies are considered: i) simultaneous and ii) stepwise insertion. The results show that inserting the additional trains simultaneously usually results in generating more optimal solutions. However, solving this type of problem is computationally challenging. We also observed that the existing robustness metrics cannot capture the essential properties of having more robust timetables. Therefore we proposed measuring Channel Width, Channel Width Forward, Channel Width Behind and Track Switching. This thesis contains three papers which are appended. The results of this thesis are of special interests for railway trac planners and it would support their working process. However, railway trac operators and passengers also benet from this study.iii

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Optimal allocation of buffer times to increase train schedule robustness

Cited by 56 publications

References 35 publications

Critical chain project buffer sizing based on resource constraints

Critical chain project buffer sizing based on resource constraints

Suitability Evaluation of a Train’s Scheduled Section Travel Time

Optimization-Based Methods for Revising Train Timetables with Focus on Robustness

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