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%.