Application of a Maintenance Management Model for Iranian Railways Based on the Markov Chain and Probabilistic Dynamic Programming


Department of Civil Engineering,Sharif University of Technology


Abstract. Railway managers have a strong economic incentive to minimize track maintenance costs,
while maintaining safety standards and providing adequate service levels to train operators. The objective
of this study is to apply a procedure for making optimal maintenance decisions in Iranian Railways. This
study consists of two parts. First, a cumulative damage model, based on a Markov process, is applied to
model the deterioration of the track. For this reason, tracks are categorized into six classes, so that those
tracks with similar trac loads and geographical location are collected into one class. The track survey
data from 215 blocks (4,228 km) of the ten divisions of the Iranian Railway system, during 2002-2004,
is used to identify the transition matrix. Secondly, probabilistic dynamic programming is used to nd the
optimal repair for each possible track state in the planning horizon. This approach allows an optimal
maintenance decision to be determined for the track at any point in time within the planning horizon.