Optimal opportunistic tamping scheduling for railway track geometry

Abstract

This study has been dedicated to the optimization of opportunistic tamping scheduling. The aim of this study has been to schedule tamping activities in such a way that the total maintenance costs and the number of unplanned tamping activities are minimized. To achieve this, the track geometry tamping scheduling problem was defined and formulated as a mixed integer linear programming (MILP) model and a genetic algorithm was used to solve the problem. Both the standard deviation of the longitudinal level and the extreme values of isolated defects were used to characterize the track geometry quality and to plan maintenance activities. The performance of the proposed model was tested on data collected from the Main Western Line in Sweden. The results show that different scenarios for controlling and managing isolated defects will result in optimal scheduling plan. It is also found that to achieve more realistic results, the speed of the tamping machine and the unused life of the track sections should be considered in the model. Moreover, the results show that prediction of geometry condition without considering the destructive effect of tamping will lead to an underestimation of the maintenance needs by 2%.

Systems thinking approach for improving maintenance management of discrete rail assets: a review and future perspectives

“…Tamping is considered effective in treating track geometry defects and is widely studied. Several optimisation tools for tamping scheduling have been formulated, such as integer linear programming (Dao, Basten, & Hartmann, 2018), mixed-integer linear/nonlinear programming (Famurewa, Xin, Rantatalo, & Kumar, 2015;Gustavsson, 2015;Khajehei et al, 2020;Vale & Ribeiro, 2014;Wen, Li, & Salling, 2016), and heuristic methods (Khajehei et al, 2020;Zhang, Andrews, & Wang, 2013). The parameters of interest include cost, possession time, the total number of tamping operations over a planning horizon, and track condition captured by TQIs.…”

“…These supporting assets are geographically distributed and limited in length, which can be conceptualised as point assets connecting the open track to support the network functioning. Since the railway track is a linear and non-redundant system, the track safety and availability depend directly on the condition of the individual track sections and point assets (Khajehei, Haddadzade, Ahmadi, Soleimanmeigouni, & Nissen, 2020). Unlike the open track, the construction form of the point assets is not generally consistent.…”

Railway track availability modelling with opportunistic maintenance practice

“…The second group of studies optimise the cost implications of grouping similar maintenance activities from an expected schedule. Famurewa et al, 25 Zhang et al, 20 and Khajehei et al 26 perform optimisation on a predicted volume of maintenance. Optimisation constraints are defined for minimising set-up costs (of a single maintenance action) and the expense of the remaining-useful-life that is lost due to an early intervention.…”

“…This is consistent with working speeds of up to 2 km/h. 26 Maintenance completion The final transitions C1 and C2 of the asset management model handle the delivery of the maintenance WO. On firing, all of the completed track sections are returned to the good condition, resetting asset markings in the other condition places.…”

Optimal track geometry maintenance limits using machine learning: A case study

“…The railway track geometry includes track gauge, rail left and right alignment, rail left and right longitudinal level, cant and twist. 10,18 Generally, the standard deviation of geometry parameters over a certain length (200 m) is used to control the need for preventive maintenance activities. 1 According to UIC, 19 it is usually the short-wavelength of the longitudinal level measurement that drives the need for track geometry maintenance activities.…”