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Effect of Railway Track Segmentation Method on the Optimal Solution of Tamping Planning Problem

Autor(en): ORCID



Medium: Fachartikel
Sprache(n): Englisch
Veröffentlicht in: Civil Engineering Journal, , n. 12, v. 7
Seite(n): 1998-2010
DOI: 10.28991/cej-2021-03091774
Abstrakt:

The safety and continuality of the railway network are guaranteed by carrying out a lot of maintenance interventions on the railway track. One of the most important of these actions is tamping, where railway infrastructure managers focus on optimizing tamping activities in ballasted tracks to reduce the maintenance cost. To this end, this article presents a mixed integer linear programming model of the Tamping Planning Problem (TPP) and investigates the effect of track segmentation method on the optimal solution by three scenarios. It uses an opportunistic maintenance technique to plan tamping actions. This technique clusters many tamping works through a time period to reduce the track possession cost as much as possible. CPLEX 12.6.3 is used in order to solve the TPP instances exactly. The results show that the total number of machine preparations increases by increasing the number of track segments. It is also found that the total costs increase by 6.1% and 9.4% during scenarios 2 and 3, respectively. Moreover, it is better to consider the whole railway track as a single segment (as in scenarios 1) that consists of a set of sections during the tamping planning in order to obtain the optimal maintenance cost. 

Copyright: © 2021 Mohammad Daddow, Xinglin Zhou, Hasan A.H. Naji, Mo''''men Ayasrah
Lizenz:

Dieses Werk wurde unter der Creative-Commons-Lizenz Namensnennung 4.0 International (CC-BY 4.0) veröffentlicht und darf unter den Lizenzbedinungen vervielfältigt, verbreitet, öffentlich zugänglich gemacht, sowie abgewandelt und bearbeitet werden. Dabei muss der Urheber bzw. Rechteinhaber genannt und die Lizenzbedingungen eingehalten werden.

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  • Reference-ID
    10647503
  • Veröffentlicht am:
    07.01.2022
  • Geändert am:
    10.01.2022
 
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