Scheduling rail track maintenance to minimise overall delays
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In Australian freight operations, maintenance costs comprise between 25 -35 percent of total train operating costs. Therefore, it is important that the track maintenance planning function is undertaken in an effective and efficient manner. This paper focuses on the development of a model designed to help resolve the conflicts between train operations and the scheduling of maintenance activities. The model involves scheduling maintenance activities to minimise disruptions to train services and reduce maintenance costs. The main applicability of such a model is as a decision support tool for track maintenance planners and train planners.
The track maintenance scheduling problem, which involves the allocation of maintenance activities to time windows and crews to activities, is formulated as an integer programming model. The objective is to minimise a weighted combination of expected interference delays and prioritised finishing time of activities. Minimising the first component will ensure a minimum interference between track maintenance activities and scheduled trains when either are delayed. The heuristic solution is obtained in two steps. Firstly, an initial solution is generated, scheduling each of the activities in turn, where the latter are ordered in terms of the importance of finishing time. Each activity is selected and allocated to an available permissible work crew. If there are no available permissible work crews when the activity is chosen, the earliest finishing crew will be selected. The second stage uses the tabu search heuristic.
The model presented here was applied to an 89 km track corridor on the eastern coast of Australia. The schedule constructed using tabu search has a 7 percent reduction in objective function value as compared to the schedule constructed manually. The model was also used to demonstrate the effects of activity schedule and maintenance resource changes. A four day planning horizon was used for which the model was used to test proposed changes. Increasing the time window by moving less important trains was shown to reduce potential delays significantly.
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