A heuristic approach to railway track maintenance scheduling

Abstract

Travelling safely and comfortably on high speed railway lines requires excellent conditions of the whole railway infrastructure in general and of the railway track geometry in particular. The maintenance process required to achieve such excellent conditions is largely complex and expensive, demanding an increased amount of both human and technical resources. In this framework, an optimal scheduling of maintenance interventions is an issue of increased relevance. In this work a method for optimization of the tamping scheduling is presented. It is based on a heuristic algorithm, which finds a very detailed tamping schedule where each planned intervention is fully specified. The algorithm tries to maximize an objective function, which is a quantitative expression of the maintenance process's objectives defined by the railway company. It first finds an upper bound for the objective function value, and then returns the best feasible solution found. The method is validated by means of a case study based on real data of the 240 km track of a French high speed TGV line. The results presented show that the value of the best solution found is very near to the upper bound (the difference is smaller than 1%), with a calculation time of under 1 second using a standard computer, so we think the heuristic has a great performance potential.

Optimizing the Alignment of Inspection Data from Track Geometry Cars

“…Much research has been conducted concerning track quality deterioration analysis. Recent examples include Kawaguchi et al (2005), Liu et al (2010), Meier-Hirmer et al (2009), Quiroga and Schnieder (2010), Veit and Marschnig (2010), and Xu et al (2011). Regarding track renewal and maintenance scheduling, Nemani et al (2010) presented four approaches to the crew planning problem-the design of an optimal annual timetable to complete a given set of repairs and replacements for a given set of crews specialized in rail or tie work.…”

“…The inspection data from track geometry cars play an important role in assessing track quality and accordingly scheduling track maintenance under a maintenance regimen (Esveld, 2001;Selig and Waters, 1994;. Furthermore, it provides quality data for track deterioration analysis and therefore, for investigation of a condition-based track maintenance strategy (Kawaguchi et al, 2005;Liu et al, 2010;Meier-Hirmer et al, 2009;Quiroga and Schnieder, 2010;Veit and Marschnig, 2010;Xu et al, 2011).…”

“…Field surveys reveal that measured milepoint positions can be off by up to 200 m. Accurate location has been shown to both reduce workload intensity for field maintenance-of-way workers and increase the utilization of track windows (Xu, 2012;Xu et al, 2013). Improvement can also provide accurate locations for reliable historical inspection data and track deterioration analyses (Liu et al, 2010;Meier-Hirmer et al 2009;Quiroga and Schnieder, 2010;Xu et al, 2011). Better analysis, in turn, results in life-cycle cost savings (Smilowitz and Madanat, 2000).…”

A stochastic model for railway track asset management

“…Quiroga and Schnieder [8,9] developed a statistical model integrating the deterioration process and maintenance to predict the track condition using data from the French railway operator, SNCF. Different maintenance strategies have then been investigated to determine their cost effectiveness.…”

A Novel Description Method for Track Irregularity Evolution

“…3,4,5 Track condition includes two categories: track geometry condition and track structure condition. 6 Track geometry condition plays a significant role in ensuring train travel safety and passenger comfort 7 and is usually determined by several geometry parameters 5 . These parameters consist of projections of rails in the horizontal, longitudinal and vertical planes and include gauge, G , and cross level, CL , in the horizontal plan, longitudinal level, LL , in the vertical plan, alignment, A , in the longitudinal plane, and twist, T , for measuring uneven running surface.…”