The Building And Implementation
Of A Track Unit Selection Model For A
Comprehensive Track Maintenance Plan
Author(s)
J. F. Shen, Y. D. Xu & H. F. Li
Abstract
To make the track comprehensive maintenance plan reasonably is an important
means to ensure the safety of train operation. The track maintenance plan model
analysis shows that making the annual maintenance plan is a process of finding the
global optimal solution in a high dimension space. Reducing the model dimension
is the key to simplify the complexity of a model under the premise of keeping the
integrity of the model, so the maintenance plan model is divided into two parts,
the track unit selection model and MTT job assignment model. In this paper, the
first model will be introduced in detail. In this model, three unit selection
constraints are considered, the optimized object is each lot of units and the
objective function is to get the maximized sum of the maintenance, improving
quantity of all the lots that are included in the selected unit. These selected units
being optimized will be used as the input parameters of the MTT job assignment
model, and this can achieve the purpose of reducing the dimension of the latter
model. In order to solve and verify the first model, a genetic algorithm is
introduced, constraint conditions in the generation phase of the initial population
are pre-processed. The results, based on data from Shanghai-Kunming railway
line, show that the solving efficiency is several times higher than the enumeration
method under the circumstance of ensuring the average error is less than 15%.
This proves that the model is practical and the genetic algorithm is effective in
efficiency and precision, so the model can be used as a rapid and efficient
approach for making a track maintenance plan.
Keywords: railway track, track longitudinal irregularity, comprehensive
maintenance plan, unit selection, genetic algorithm.
Keywords
railway track, track longitudinal irregularity, comprehensive
maintenance plan, unit selection, genetic algorithm.
Related Book
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